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N400 event-related potentials in 10 and 11 year old boys during the reading of sentences and the categorization of words
Dunn, Denise Ann, Ph.D.
The Ohio State University, 1988
Copyright ©1988 by Dunn, Denise Ann. All rights reserved.
UMI 300 N. ZeebRd. Ann Arbor, MI 48106
N400 EVENT-RELATED POTENTIALS IN 10 AND 11 YEAR
OLD BOYS DURING THE READING OF SENTENCES
AND THE CATEGORIZATION OF WORDS
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
the Degree Doctor of Philosophy in the Graduate
School of The Ohio State University
By
Denise A. Dunn, B.S., M.A.
******
The Ohio State University
1988
Dissertation Committee:
Dr. Marlin L. Languis
Dr. Harold B. Pepinsky
Dr. James E. Kerber Copyright by Denise A. Dunn 1988 Dedication To my husband, my children and my mother.
i i ACKNOWLEDGEMENTS
I would like to express my sincere appreciation to my adviser, Dr. Marlin L. Languis, whose help and guidance made this dissertation possible. I am deeply grateful to Dr.
Harold B. Pepinsky for his friendship, kindness and understanding throughout my doctoral program. I am appreciative of the efforts of Dr. James E. Kerber for his assistance as a committee member.
A very special thanks goes to Dr. Michael W. Torello for his friendship and encouragement during my years of study at OSU and whose technical advise and assistance helped make this research project successful.
The most special appreciation, sincerest gratitude and deepest love are reserved for my husband, Dr. Bruce R. Dunn, whose programing efforts turned a research idea into reality. His continued guidance, belief in my abilities and inspiration helped bring about the completion of my
Doctorate Degree. VITA
June 5, 1946 ...... Born - Highland Park, Michigan
1968 ...... B.S., Wayne State University Detroit, Michigan
1969-1975 ...... Elementary School Classroom Teacher, Alabama and Florida
1983 ...... M.A., University of West Florida Pensacola, Florida
1983-1986 ...... Teaching/Research Associate, The Ohio State University Columbus, Ohio
FIELDS OF STUDY
Major Field: Neurocognitive Science, Dr. Marlin L. Languis
iv TABLE OF CONTENTS
ACKNOWLEDGEMENTS ...... iii
VITA ...... iv
LIST OF T A B L E S ...... vii
LIST OF F I G U R E S ...... ix
CHAPTER PAGE
I. OVERVIEW ...... 1
Introduction ...... 1 Rationale ...... 2 Problem Statement ...... 9 Hypotheses...... 11 Definitions of Terms ...... 13 Limitations and Assumptions .... 17
II. LITERATURE REVIEW ...... 20
Introduction ...... 20 Event-Related Brain Potentials and Language Processing ...... 20 The N400 ERP and Semantic Processing...... 22 Language Related ERPs in Children . 36 Topographic Mapping of Brain Electrical Activity ...... 43
III. M E T H O D ...... 50
Introduction ...... 50 Selection of Subjects ...... 51 Stimuli and Materials ...... 52 Recording System ...... 55 Subject Preparation and Experimental Procedures...... 57 Data Reduction...... 63 Data A n a l y s i s ...... 64
IV. RESULTS...... 71
v introduction ...... 71 Behavioral D a t a ...... 71 Comparison of ERPs to Baseline . . . 73 Comparison of Condition vs Condition E R P s ...... 87 Other ERP Findings...... 119
V. DISCUSSION AND IMPLICATIONS ...... 135
Introduction ...... 135 Baseline Hypotheses ...... 136 Anomalous and Congruent Sentence D a t a ...... 137 Word Categorization and Word Reading D a t a ...... 138 Other Findings...... 153 Implications for Additional Future Research...... 156
LIST OF REFERENCES...... 160
APPENDICES
A. Human Subject's Review Form ...... 172
B. Letter to Parents...... 175
C. Sample T a s k s ...... 177
D. Consent to Special Treatment Form . . . 179
E. List of Ninety S e n t e n c e s ...... 181
F. Word Reading L i s t ...... 185
G. Category L i s t ...... 187
H. Handedness Inventory ...... 190
I. Trial Sentences...... 192
J. Sentence Recognition and Rating Task . 194
K. T - M a p s ...... 207
vi LIST OF TABLES
TABLE PAGE
1. Mean Number of Trials Accepted Per Subject by Condition...... 64
2. Significant Mean Peak Differences (in uv) between Anomalous Sentence Endings and ERP Baseline...... 75
3. Significant Mean Peak Differences (in uv) between Congruent Sentence Endings and ERP Baseline...... 78
4. Significant Mean Peak Differences (in uv) between the Categorization of Words and ERP Baseline...... 81
5. Significant Mean Peak Differences (in uv) between the Categorization of Words and ERP Baseline...... 82
6. Significant Mean Peak Differences (in uv) between the Reading of Words and ERP Baseline...... 85
7. Significant Mean Peak Differences (in uv) between the Reading of Words and ERP Baseline...... 86
8. Significant Mean Peaks and Latencies for Anomalous and Congruent Sentence Endings . . 92
9. Significant Mean Peaks and Latencies for Anomalous Sentence Endings and Categorizationof Words ...... 99
10. Significant Mean Peaks and Latencies for the Categorization of Words and Congruent Sentence Endings ...... 100
vii 11. Significant Mean Peaks and Latencies for the Categorization of words and congruent Sentence Endings ...... 101
12. Significant Mean Peaks and Latencies for the Categorization of Words and Congruent Sentence Endings ...... 102
13. Significant Mean Peaks and Latencies for the Reading of Words and Congruent Sentence E n d i n g s ...... 109
14. Significant Mean Peaks and Latencies for the Reading of Words and Congruent Sentence E n d i n g s ...... 110
15. Significant Mean Peaks and Latencies for the Reading of Words and Congruent Sentence E n d i n g s ...... Ill
16. Significant Mean Peaks and Latencies for Anomalous Sentence Endings and the Reading of W o r d s ...... 117
17. Significant Mean Peaks and Latencies for Anomalous Sentence Endings and the Categorization of Words ...... 120
18. Significant Mean Peaks and Latencies for Anomalous Sentence Endings and the Categorization of Words ...... 123
19. Significant Mean Peaks and Latencies for Anomalous Sentence Endings and the Reading of W o r d s ...... 126
20. Significant Mean Peaks and Latencies for Anomalous Sentence Endings and the Reading of W o r d s ...... 129
21. Significant Mean Peaks and Latencies for Anomalous Sentence Endings and the Reading of W o r d s ...... 131
vi ii LIST OF FIGURES
The International 10-20 system ......
Diagram of the recording system ......
Event-related potentials by recording site for the anomalous ending sentences (-----) and a topographic map showing the distribution [in microvolts (uv)] of the N400 peak amplitudes across the scalp . . .
Event-related potentials by recording site for the congruent ending sentences (-----) and a topographic map showing the distribution (in uv) of the largest positive peak amplitude between 250 and 500 milliseconds (ms) across the scalp . . .
Event-related potentials by recording site for the categorization of words (---- ) and topographic maps showing the distribution (in uv) across the scalp of the largest negative peak amplitudes (top map) between 250 and 500 ms and positive peak amplitudes (bottom map) between 500 and 924 ms . . . .
Event-related potentials by recording site for reading unrelated words (---- ) and topographic maps showing the distribution (in uv) across the scalp of the largest negative peak amplitudes (top map) between 250 and 500 ms and positive peak amplitudes (bottom map) between 500 and 924 ms . . . . 7. Event-related potentials by recording site for the anomalous sentence endings (---- ) and the congruent sentence endings (- - -). The topographic maps show the distribution (in uv) across the scalp of the N400 peak amplitude (in uv) for congruent endings (top map) and anomalous endings (bottom m a p ) ...... 90
8. Event-related potentials by recording site for the anomalous sentence endings (---- ) and the congruent sentence endings (- - -). The topographic map shows the t distribution (in t values x 100) for the comparison of negative peak amplitudes in the 250-500 ms range between the anomalous and the congruent sentence endings ...... 93
9. Event-related potentials by recording site for reading unrelated words (----) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the N400 peak amplitudes for reading words (top map) and categorizing words (bottom map) ...... 96
10. Event-related potentials by recording site for anomalous sentence endings (----) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the N400 peak amplitudes for categorizing words (top map) and anomalous endings (bottom map) ...... 97
11. Event-related potentials by recording site for congruent sentence endings (-----) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the N400 peak amplitudes for categorizing words (top map) and congruent endings (bottom map) ...... 104
12. Event-related potentials by recording site for congruent sentence endings (-----) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the largest positive peak amplitudes between 250 and 500 ms for categorizing words (top map) and congruent endings (bottom map) ...... 106
x 13. Event-related potentials by recording site for congruent sentence endings (-----) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the mean averaged amplitude within the 250-500 ms range for categorizing words (top map) and congruent endings (bottom map) ...... 107
14. Event-related potentials by recording site for congruent sentence endings ( ) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the N400 peak amplitudes for reading words (top map) and congruent endings (bottom map) ...... 112
15. Event-related potentials by recording site for congruent sentence endings (---—) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the largest positive peak amplitudes between 250 and 500 ms for reading words (top map) and congruent endings (bottom map) ...... 113
16. Event-related potentials by recording site for congruent sentence endings (-----) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the mean averaged amplitude within the 250-500 ms range for reading words (top map) and congruent endings (bottom map) ...... 114
17. Event-related potentials by recording site for anomalous sentence endings (---- ) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the mean averaged amplitude within the 250-500 ms range for reading words (top map) and anomalous endings (bottom map) ...... 118
18. Event-related potentials by recording site for anomalous sentence endings (---- ) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the largest positive peak amplitudes between 500 and 924 ms for categorizing words (top map) and anomalous endings (bottom map) ...... 122
xi 19. Event-related potentials by recording site for anomalous sentence endings (---- ) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the mean averaged amplitude within the 500-800 ms range for categorizing words (top map) and anomalous endings (bottom map) ...... 124
20. Event-related potentials by recording site for anomalous sentence endings (-----) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the largest negative peak amplitude between 500 and 924 ms for reading words (top map) and anomalous endings (bottom map) ...... 127
21. Event-related potentials by recording site for anomalous sentence endings (-----) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the largest positive peak amplitude between 500 and 924 ms for reading words (top map) and anomalous endings (bottom map) ...... 130
22. Event-related potentials by recording site for anomalous sentence endings (-----) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the mean averaged amplitude within the 500-800 ms range for reading words (top map) and anomalous endings (bottom map) ...... 133
23. Event-related potentials by recording site for anomalous sentence endings (-----) and congruent sentence endings (- - -). The topographic map shows the t distribution (in t values x 100) for the comparison of mean averaged amplitudes within the 250-500 ms range between the two sentence ending conditions ...... 208
xii 24 . Event-related potentials by recording site for congruent sentence endings ( ) and categorization of words (- - -). The topographic map shows the t distribution (in t values x 100) for the comparison of negative peak amplitudes in the 250-500 ms range between congruent endings and categorizing words ...... 209
25. Event-related potentials by recording site for congruent sentence endings (---- ) and categorization of words (- - -). The topographic map shows the t distribution (in t values x 100) for the comparison of positive peak amplitudes in the 250-500 ms range between congruent endings and categorizing words ...... 210
26. Event-related potentials by recording site for congruent sentence endings (---- ) and categorization of words (- - -). The topographic map shows the distribution (in t. values x 100) for the comparison of mean averaged amplitudes within the 250-500 ms range between congruent endings and categorizing words ...... 211
27 . Event-related potentials by recording site for congruent sentence endings (---- ) and reading unrelated words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of negative peak amplitudes in the 250-500 ms range between congruent endings and reading words ...... 212
28. Figure 28. Event-related potentials by recording site for congruent sentence endings (---- ) and reading unrelated words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of positive peak amplitudes in the 250-500 ms range between congruent endings and reading words ...... 213
xiii 29. Event-related potentials by recording site for congruent sentence endings ( ) and reading unrelated words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of mean averaged amplitude within the 250-500 ms range between congruent endings and reading words ...... 214
30. Event-related potentials by recording site for anomalous sentence endings (---- ) and categorization of words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of the largest positive peak in the 500-924 ms range between anomalous endings and categorizing words ...... 215
31. Event-related potentials by recording site for anomalous sentence endings (---- ) and categorization of words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of the mean averaged amplitude within the 500-800 ms range between anomalous endings and categorizing words ...... 216
32. Event-related potentials by recording site for anomalous sentence endings (---- ) and reading unrelated words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of the largest negative peak within the 500-924 ms range between anomalous endings and categorizing words ...... 217
33. Event-related potentials by recording site for anomalous sentence endings (---- ) and reading unrelated words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of the largest positive peak within the 500-924 ms range between anomalous endings and categorizing words ...... 218
xiv 34. Event-related potentials by recording site for anomalous sentence endings (---- ) and reading unrelated words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of the mean averaged amplitude within the 500-800 ms range between anomalous endings and categorizing words ...... 219
xv CHAPTER I
Overview
Introduction
The purpose of the study was to investigate complex language processing (through the measurement of brain electrical activity) as it actually occurred within the brains of 10 and 11 year old boys. The boys were asked to read declarative sentences, categorize a list of words and read a list of unrelated words while their electroencephalograms (EEG) were recorded and later compared between tasks. This was the first study to investigate event-related potentials (ERPs) in children using complex language stimuli (sentences). This chapter is organized into five sections. The first section, Rationale, presents the underlying reasons for this research study. In the second section, Problem Statement, a statement of the problem is presented along with the research questions to be addressed. The Hypotheses section lists the hypotheses in the order in which they were proposed for this study and in which they will be subsequently addressed in Chapter IV.
Next, Definitions of Terms, defines the terms to be used throughout this dissertation. Finally, the Limitations and
Assumptions section, presents the limitations of this study
1 2
along with the assumptions upon which the study was based.
Chapter I concludes with an overview of the sections to be
addressed in Chapter II.
Rationale
Human beings are able to use sophisticated systems of
language in order to communicate with each other and to
perform complex acts in accordance with that communicated
information (Pepinsky, 1985). Because of its importance in
human interaction, the study of language development and
language processing has moved into a central position in
cognitive psychology (Solso, 1988) and has generated major
interest in the field of education (Languis & Kraft, 1985:
Languis & Wittrock, 1986). Language is a fundamental aspect
of cognition and many forms of human thinking and problem
solving can be viewed as involving language (Solso, 1988).
In education, many of these thinking and problem solving
activities can occur without external responses from the
learner. That is, most of this processing occurs
internally, within the learner, and is not directly
observable using conventional measurement techniques
(Languis & Wittrock, 1986).
The problem of the covert nature of language processing
is echoed by Swinney (1981) who states that if we are to achieve any substantial understanding of language performance, it is necessary to examine the microstructure
of the mental language processes as they occur in "real 3 time" without affecting those processes. In the field of education, Languis and Wittrock (1986) support these notions by pointing out that until recently, covert mental processes were inferred indirectly from a learner's performance on various school related tasks. However, with the advent of high speed computers, certain aspects of the learner's covert mental process can be measured by recording the brain's electrical activity [using electroencephalogram
(BEG) techniques] during the execution of complex cognitive tasks. In order to increase the scope of electrophysiological research to educationally related tasks, Languis and Wittrock (1986) argue that a person's
EEG should be recorded from numerous sites on the brain during the processing of complex information. They specifically suggest that a coherent picture of these subtle covert processes can be found by displaying the EEG activity underlying these processes using the relatively new technology of topographic brain mapping. Topographic brain mapping allows the researcher to condense, analyze and graphically display on a computer monitor selected components of EEG activity collected from a number of scalp sites across the surface of the brain (Duffy, Burchfiel, &
Lombroso, 1979).
One of the more promising electrophysiological measures, which is based on a number of EEG records
(Donchin, 1982; Hillyard & Kutas, 1983; Picton & Stuss, 1984) and Is particularly amenable to display using
topographic brain mapping (Languis & Wittrock, 1986) is the
event-related brain potential. The event-related potential
(ERP) is an averaged brain response which has a fixed
temporal relationship to external stimuli. It is the brain's unique electrical activity pattern to numerous (at
least 16) repetitions of a stimulus of interest (e.g., word presentation). First, the brain's electrical potentials are recorded by scalp electrodes using noninvasive electroencephalogram (EEG) techniques. After recording,
individual trials or epochs of EEG are summed and averaged together. Finally, within the averaged waveform, the ERP components, "time-locked" to recurrent events, become distinguishable from irregularly occurring (inconsistently related to the event) EEG potentials (Goff, 1974).
While trying to advance the work being done with ERP's and language, Marta Kutas and Steven Hillyard (1980a, 1980b,
1980c) made a striking finding. Event related potentials made to the final words of sentences that were meaningful
(e.g. He spread the warm bread with butter.) displayed a positive peak in the averaged waveform. In contrast, ERPs to final words that were semantically anomalous (e.g. He spread the warm bread with socks.) were characterized by a large negative shift in the averaged wave (N400) peaking around 400 milliseconds (ms). This N400 component (range
300-600 ms) is a fairly robust negative potential [amplitudes from -3.3 microvolts (uv) to -5.7 uv relative to prestimulus baseline], which is characterized by a posterior scalp distribution [largest over scalp sites Cz, Pz, Oz,
(see Figure 1 for placement) as well as right and left posterior temporal sites over Wernicke's area and the right hemisphere homologue] and displayed a somewhat greater amplitude over the right (-4.1 uv) than the left hemisphere
(-3.4 uv) (Kutas & Hillyard, 1983).
Early studies (Kutas & Hillyard, 1980a, 1980b, 1980c,) showed that neither physical incongruities (e.g. He spread the warm bread with BUTTER.) nor anomalies of grammar in the sentence (e.g. He spread the warm bread with buttered.) elicited the N400. Only anomalies related to the meaning of the sentence, i.e., semantic incongruities, were sufficient to bring about the N400. The fact that neither physical deviations (letter size, bold type) nor grammatical violations elicited the N400, seemed to indicate that the negative component was dependent upon some aspect of semantic analysis rather than being a general response to aberrant words in text. Extensive work during these early studies (Hillyard & Kutas, 1983; Kutas & Hillyard, 1980a,
1980b, 1980c, 1982, 1983, 1984) initially suggested that the onset of the late negative component may be related to the violation of a semantic expectancy during language processing. 6
THE INTERNATIONAL 10-20 SYSTEM
LEFT RIGHT
NASION
PRE FRONTAL
FRONTAL ANTERIOR VERTEX TEMPORAL
CENTRAL MID VERTEX' TEMPORAL -CENTRAL PARIETAL VERTEX ‘ POSTERIOR TEMPORAL
OCCIPITAL
INION
O RECORDING SITES
Figure 1 . 7
However, recent research casts doubt on previous interpretations of the N400 as merely a sign of
"reprocessing" that is evoked by a semantic anomaly within a sentence (Dunn, Andrews, Santurri, Languis, & Gibson, 1987;
Kutas & Hillyard, 1984; Kutas & Van Petten, in press;
Polich, 1985). Polich (1985), for example, compared the
Kutas and Hillyard (1980b) sentences with a word series reading task to provide physically similar task demands while manipulating semantic congruency in a nonsentence context. In experiment 1, 80 seven word sentences (50% congruent, 50% anomalous i.e., the Kutas & Hillyard paradigm) and 80 different seven word series (e.g. fruit names, flower names) were presented to each subject. In half the word series, the seventh word belonged to the same semantic category as the first six while in the other half of the series the seventh word was from a semantically unrelated category.
The results indicated that the waveform pattern produced by the sentences was identical to the one seen in the Kutas and Hillyard paradigm (1980a, 1980b, 1980c, 1982).
For the word reading series, the anomalous (unrelated category) endings produced a more negative response than the congruous (same category) endings. More importantly, both word series conditions produced a negative waveform around
400 ms followed by a positive-going wave very similar to that of the anomalous ending sentences. Similar results 8
were found in Pollch's experiment 2. Polich concluded by
stating that the "N400 effect” seems to be extremely
sensitive to variations of the semantic appropriateness of
words. In addition, the 400 ms negativity "may be a
reflection of the system's overall capability to comprehend
complex similarities and relationships among stimulus items
rather than a unique response to semantic incongruities" (p.
319). Further, research conducted at the Brain Behavior
Laboratory of Ohio State University, (Dunn et al., 1987)
found that an N400 component was generated during a word
reading task when subjects were merely asked to read
unrelated words and a memory task where the subjects were asked to learn words by placing them into taxonomic
categories for later recall.
Thus far, all of the research on the N400 component
(including that reported above) has utilized only adult
subjects even though notable researchers have stressed the
importance of studying the electrophysiological responses of
children during linguistic processing (e.g., Courchesne,
1983; Friedman, Brown, Sutton, & Putnam, 1982). In addition, the interpretation of the "N400 effect" is not yet
clear. Is the N400 controlled by semantic expectancies and
relationships among words in a sentence context (Kutas,
1988; Kutas, Van Petten, & Besson, 1988), is it the
comprehension of complex relationships among stimulus items,
such as the relationships in a category list as well as that of a sentence, (Polich, 1985) or is there another explanation? Finally, all the investigations of the N400 have made EEG recordings from a limited number of brain sites (a maximum of eight electrodes, e.g., Kutas &
Hillyard, 1983 and a minimum of three electrodes, e.g.,
Polich, 1985).
Problem Statement
In order to expand research on the N400 component and overcome these weaknesses in the literature, the following research study was designed. Briefly, the ERP waveforms produced by 10 and 11 year old boys during the processing of semantically congruent sentence endings were compared to the
ERP waveforms produced by the same boys while processing anomalous sentence endings (Semantic Task 1, i.e., the Kutas
& Hillyard paradigm). In addition, to begin looking at the brain activity associated with the semantic categorization of words by children, a categorization task and a word reading task, similar to the ones developed at Ohio State
University's Brain/Behavior Laboratory, were given to 10 and
11 year old boys.
A comparison was made between the waveforms of the first semantic task (anomalous and congruent sentence endings) and the waveforms in the second semantic task (word categorization and word reading) to establish similarities and differences in the two processes. It was expected that a direct categorization condition (learning words in 10 categories) and a reading condition (reading unrelated words) would help to further differentiate aspects of the
"N400 effect" which may be due to complex processing (i.e., evaluation) of stimulus similarity and dissimilarity
(Polich, 1985) and may also be related to semantic expectancies and relationships among words (Kutas et al.,
1988).
Following the suggestion made by Languis and Wittrock
(1986), topographic imaging of brain electrical activity was used with a complement of 15 scalp electrodes. It was assumed that the use of additional electrode sites would provide a more complete picture of the brain activity occurring during cognitive processing than the limited montage typically used in N400 studies. Also, the use of brain mapping allowed the data to be graphically displayed and the waveforms for the various conditions in the two semantic tasks (e.g., congruent vs anomalous sentence endings and categorizing words vs reading words) to be examined for subtle patterns in the distribution of the N400 component. It was assumed that these patterns are indicative of covert language processes.
Given the above, several questions were addressed in the design of the present dissertation:
1. How does cognitive processing differ when 10 and 11 year old boys are presented with congruent versus anomalous ending sentences? 11
2. Does cognitive processing differ when 10 and 11 year old boys are asked to categorize a list of words as
opposed to simply reading a list of unrelated words?
3. Are the processes of reading congruent and anomalous ending sentences similar or dissimilar from the processes of categorizing or reading a list of words?
4. Will the new technology of topographic imaging of brain electrical activity (through the addition of electrode sites and a graphic display of the data) be a successful technique for studying linguistic processing in children?
Hypotheses
HI: It is expected that sentences with anomalous endings will produce a statistically significant late negative ERP component ranging in amplitude from 3-8 uv and having a latency of 300-600 ms when compared to subjects'
EEG baseline.
H2: Sentences with congruent endings will produce a statistically significant late, positive going ERP component ranging in amplitude from 4-12 uv, and having a latency from
300-600 ms poststimulus relative to subjects' EEG baseline.
H3: There will be a statistically significant difference when comparing the amplitude of waveforms produced while reading sentences ending anomalously and the amplitude of waveforms produced in response to sentences that end congruently at scalp sites Cz and Pz in the interval from 300-600 ms poststimulus. 12
H4: It is expected that In the second semantic task, the categorization condition ERPs will be characterized by a late negative component at Cz and Pz occurring between 300-
GOO ms followed by a late positive component with maximum peak in the 500-900 ms range at Cz and Pz. Both components will be statistically different compared to an EEG baseline.
H5: It is expected that the reading condition ERPs will be characterized by a late negative component between
300-600 ms followed by a late positive component between
500-900 ms which are both statistically different from baseline.
H6: It is expected that the waveform elicited by the categorization condition will contain a significantly greater mean amplitude of the N400 component than will the waveform elicited in the reading condition.
H7: It is expected that the waveform elicited by the anomalous sentences (the first semantic task) when compared to that of the category condition (the second semantic task) will not be statistically different from one another, each showing a late negative component in the 300-600 ms range most prominently peaking at Cz and Pz scalp sites.
H8: It is expected that the waveform elicited by the category condition will be statistically different from the waveform elicited by the congruent sentence endings in the
300-600 ms time frame, with the waveform from the category condition being characterized by a negative component (N400) 13
and the waveform from the congruent sentence endings
condition being characterized by a positive component (P300)
each peaking maximally at Cz and Pz.
H9: It is expected that the reading condition and the
congruent sentences condition will not be statistically
different in mean amplitude from one another in the 300-600
ms range.
H10: It is expected that the waveform of the reading
condition will be statistically different when compared to
the waveform produced by the anomalous ending sentences
condition in the 300-600 ms range.
Definitions of terms
1) Electroencephalogram (EEG): EEG is a measure of
brain electrical activity made through the use of scalp
electrodes. Such EEG activity is the sum of excitatory and
inhibitory post-synaptic potentials generated from the
layers of the cortex (Vaughan, Ritter, & Simson, 1983).
2) Event-Related Potential (ERP): The event-related
brain - potential is a waveform time-locked to a stimulus
event. It is not generally discernable in an
electroencephalogram (EEG) record because it is lost in the vast array of electrical activity generated by the brain as
it performs its many functions. Therefore, the ERP must be
extracted from the EEG record through the use of a technique
known as signal averaging (Dawson, 1951). A stimulus event
(e.g. visual, auditory, tactile) is repeatedly presented 14 while short epochs of EEG, which are time-locked to the stimulus of interest, are collected. The epochs are then computer averaged to enhance the waveforms being examined.
By the law of super imposition in physics, the activity which is random to the event of interest will cancel itself during the averaging process, while the ERP which is related to the event will remain constant and will become more pronounced during averaging. Cognitive researchers and educators have become interested in ERPs because of their documented correlation to perception, attention, and higher cognitive functions (e.g. language, decision processes, etc).
3) P300 Component: The P300 component (also referred to as the P3) is a late, large positive wave or complex of waves with the highest amplitude occurring over central (Cz) and parietal (Pz) scalp locations between 300 and 600 ms poststimulus in adults (Kutas & Van Petten, in press). P300 latency has been shown to vary within linguistic tasks . dependent upon how difficult it is to discriminate target from non-target events (Kutas, McCarthy, & Donchin, 1977).
This waveform appears to be generated at the termination of stimulus evaluation and is used as an index of that evaluation time (Donchin, 1981; Picton & Stuss, 1984). P3 responses are evoked by each word that makes up a sentence.
The more content information the word gives, the longer the latency of the P3. The largest P3 occurs with the last word of a sentence and is interpreted as representative of 15 semantic closure (Friedman, Simpson, Ritter, & Rapin, 1975;
Picton & Stuss, 1-984 ).
4) N400 Component: The N400 is a late, robust negative wave occurring between 300 and 600 msec poststimulus with a posterior scalp distribution which is greater in amplitude over the right than the left hemisphere in adults (Kutas & Van Petten, in press). The N400 seems to be sensitive to processes of language comprehension and can be elicited by such things as semantic violations at the ends of otherwise meaningful sentences (Kutas & Hillyard,
1980a), a lack of relationship between associated words
(Fischler, Bloom, Childers, Roucos, & Perry, 1983), the creation of a mismatch with previous knowledge or expectancy
(Fischler, Childers, Achariyapaopan, & Perry, 1985; Kutas,
Lindamood & Hillyard, 1984), and semantic deviation within a list of words (Polich, 1985). Studies are still underway to clarify the exact meaning of this waveform.
5) Artifacts: Signals that originate from muscle potentials (movement) of the subject rather than brain activity (e.g., gross body movements, head movement, etc.) are unwanted in the EEG record. Artifact can be related to fatigue, tenseness, and general discomfort. Eye movement can also be a source of unwanted artifact e.g., movement of the eyeball or eyelid, movement due to eye blinks. Eye artifact can be specifically monitored by surface electrodes placed near the eyes to detect electrical potentials 16
generated during eye movement (known as electrooculography
or EOG). EEG trials that are contaminated with artifact are
eliminated from the data before averaging the EEG trials.
6) Topographic Brain Imaging: Topographic brain
imaging is a computer-based technique which can condense,
summarize, and then graphically display on a computer monitor temporal, spatial, and spectral information from brain electrical activity that was collected from numerous scalp locations. The data can be statistically compared between subjects to a control group or compared within subjects to a baseline measure. The product of this technology is a topographic map of electrical activity from the entire cerebral cortex (Duffy, Burchfiel, & Lombroso,
1979 ).
Topographic brain imaging is analogous to the construction of an isotherm map, that is, through the use of exact temperatures from various points in a country (e.g., cities) it is possible to predict and display temperature readings for any area of that entire country. Brain mapping works on a similar principle. It constructs an electrical activity map of the brain’s surface through the use of readings from specific recording sites and interpolates those values to produce a kind of iso-EEG map of brain activity (Languis & Wittrock, 1986; Torello & Duffy, 1985). 17
Limitations and Assumptions
The limitations of this study lie primarily in the selection of subjects. Because the phenomenon being investigated (formation of the N400 during semantic anomalies) had never been studied in children, it was important to restrict the population of children to a set of individuals who had the greatest potential of exhibiting this phenomenon, namely right-handed males (Kutas, personal communication; see Levy, 1980 for a review).
Developmental studies show a transition into adult ERP waveforms (P300) occurring in the early to mid-teens
(Courchesne, 1978). To avoid this transition period and also gain a relatively high level of vocabulary development such that the sentences used could be similar (and in many cases identical, taken from Bloom & Fischler, 1980) to those used in the adult studies, fifth grade males (10-11 yrs old) were asked to serve as subjects. The children who participated in this study were right-handed, of normal intelligence and had a functional vocabulary and reading ability at fifth grade level or above. The school from which these subjects were obtained was located in a middle class neighborhood. Thus, the generalizability of this study was limited to the characteristics of the subject sample used in this investigation. Consequently, the results cannot be extrapolated to all 10 and 11 year old males. 18
This study was based on several assumptions. First, that event-related brain potentials are related to cognitive functioning. More specifically, that the N400 is related to semantic processing. Second, that the N400 component, if found in 10 and 11 year old boys, is similar to the N400 component seen with adults. Third, that topographic brain imaging will provide a detailed representation of the distribution of the N400 component across the scalp.
Fourth, that the method of monitoring and editing muscle and eye movement artifact is sufficient to provide noncontaminated EEG data. Finally, that the subject pool is reasonably homogenous in ability level based on school records.
In conclusion, this chapter presented the relevant arguments for this dissertation followed by a statement of the problems to be addressed. The hypotheses for this research were listed and terms to be used in this study were defined. Finally, the assumptions upon which this research was based and it's limitations were given. Chapter II will be a review of the relevant literature for this dissertation. The second chapter will provide a more indepth look at the event-related potential and language processing. Specifically, the topics that will be addressed are the event-related potential and language processing, the
N400 component and semantic processing, language and event- related potentials with children, and finally topographic 19 brain mapping as a new technique. CHAPTER II
Literature Review
Introduction
In this chapter the relevant literature which served as a basis for this dissertation is reviewed. The chapter is divided into four sections. The first section, Event-
Related Brain Potentials and Language Processing, presents an overview of event-related potentials and how they have been related to language processing in the research literature. The second section, The N400 ERP and Semantic
Processing, specifically reviews the N400 ERP component which is the major emphasis of this dissertation. The third section, Language Related ERPs in Children, discusses studies which measured ERPs in children and whose stimuli, although not linguistically complex, could-be considered semantic in nature. The final section, Topographic Mapping of Brain Electrical Activity, explains topographic mapping as a new technique and reviews some of the literature which utilizes this brain imaging procedure.
Event-Related Brain Potentials and Language Processing
The event-related potential (ERP) allows for the investigation of complex information processing as it actually occurs within the human brain (Donchin, 1982;
20 Hillyard & Kutas, 1983; Picton & Stuss, 1984). There Is a current emphasis in the field of electrophysiological research toward the use of ERPs for studying the ongoing mechanisms related to cognition, especially those brain processes underlying the use and comprehension of language
(e.g., Bentin, McCarthy, & Wood, 1985; Fischler, Boaz,
Childers, & Perry, 1985; Harbin, Marsh, & Harvey, 1984;
Kutas & Van Petten, in press; Lovrich, Simson, Vaughn Jr., &
Ritter, 1986; McCallum, Farmer, & Pocock, 1984; Molfese,
1983, 1985; Polich, 1985). Kutas and Van Petten (in press) argue for ERPs to examine language processes because such a nonintrusive technique would allow for a "real-time” examination of at least some of the brain processes that underlie language and cognition. In a critical review of
ERPs in the study of language, Picton and Stuss (1984) state that by investigating language processing as it is actually occurring, psychophysiological studies have an advantage over behavioral studies in that they do not have to wait for a response to a stimulus but provide a window into the cognitive or information processing phenomenon as it progresses.
Specific ERP components, both positive and negative (in polarity), have been identified as relating to various aspects of linguistic processing ranging from the phonological (Rugg, 1984; Rugg & Barrett, 1987a) to the processing of words and sentences (Boddy & Weinburg, 1981; 22
Erwin, 1986; Kutas, 1985). For example, the P300 (P3) or
late positive wave [having a positive polarity and occurring at approximately 300 milliseconds (ms) poststimulus] is elicited in the event-related potential when words are compared phonologically or orthographically in a word matching task (Polich, McCarthy, Wang, & Donchin, 1983). A
P3 is evoked when a target word is to be discriminated within a list of words (Kutas, et al., 1977) or when a word match is required in a string of 5 words for which the fifth word matches the list in identity or category type and an
N400 (having a negative polarity and occurring at approximately 400 ms poststimulus) when the word does not match in category type (Harbin, et al., 1984). [Note, that further investigation of the N400 component is the basis of this dissertation and is discussed at length below.]
Further, Kutas and Hillyard (1980a, 1980b, 1980c) have looked at sentences in which words were presented one word at a time and found that each word of a semantically correct sentence evoked a late positive wave occurring 300-600 ms poststimulus. When this paradigm was first used by
Friedman, Simson, Ritter, and Rapin (1975), the fact that the final word of the sentence always elicited the largest
P3 was interpreted as a representation of semantic closure.
The N400 ERP and Semantic Processing
While trying to advance the work being done with the P3 and language, Marta Kutas and Steven Hillyard (1980a, 1980b, 1980c) made a striking finding. A late negative wave
(N400), with a latency of 400 ms poststimulus consistently occurred when semantically incongruous words were at the ends of otherwise meaningful sentences. This N400 (range
300-600 ms) is a fairly robust negative potential
[amplitudes from -3.3 microvolts (uv) to -5.7 uv relative to prestimulus baseline], which is characterized by a posterior scalp distribution (largest over scalp sites Cz, Pz, Oz, as well as right and left posterior temporal) and a somewhat greater amplitude over the right (-4.1 uv) than the left hemisphere (-3.4 uv) (Kutas & Hillyard, 1983). Extensive work with this negative ERP component revealed initially that the onset of this late negative waveform may be related to the development and violation of semantic expectancies during language processing (Hillyard & Kutas, 1983; Kutas &
Hillyard, 1980a, 1980b, 1980c, 1982, 1983, 1984).
Early studies (e.g. Kutas & Hillyard, 1980a, 1980b,
1980c) indicated that ERPs to the final words of sentences that were meaningful (e.g. He spread the warm bread with butter.) displayed a positive shift (P3). In contrast, ERPs to final words that were semantically anomalous (e.g. He spread the warm bread with socks.) were characterized by a large negative potential (N400) peaking around 400 ms.
Neither physical incongruities in the final word (e.g. He spread the warm bread with BUTTER) nor anomalies of grammar
(e.g. He spread the warm bread with buttered) elicited the 24
N400. Only anomalies related to the meaning of the
sentence, i.e., semantic incongruities, were sufficient to
bring about the N400. The fact that neither physical
deviations (size, bold type) nor grammatical violations
elicited the N400 seemed to be evidence that the negative
component appeared to be dependent upon some aspect of
semantic analysis rather than being a general response to
aberrant words in text.
The experiments done by Kutas and Hillyard (1983)
revealed that the N400 follows a semantic incongruity
irrespective of its serial position in the sentence. They
have shown that it appears to be relatively insensitive to
manipulations of the probability of occurrence of semantic anomalies and has essentially the same amplitude and latency
whether the sentences have a proportion of anomalous to
congruous endings 25% or 50% of the time. Finally, as
mentioned above, the N400 has a marked posterior distribution over the scalp with a slight but consistent
right hemisphere predominance at posterior temporal sites in
both amplitude and duration (waveform area difference with
right greater than left equal to -28 microvolt-mi11iseconds
where microvolt-millisecond equals the summation of the data
points over a specific interval of time in milliseconds, e . g . , 400-700 ms).
Recent research, however, casts doubt on previous
interpretations that the N400 is a sign of "reprocessing" 25 that is engendered by a semantic anomaly. Kutas and
Hillyard (1984) have, for example, published research which expanded their original findings. In this study, they related sentence completion to the degree of expectancy for terminal words (hi, med, lo) [using the "Cloze" procedure
(Taylor, 1953)11 and levels of contextual constraint (hi, med, lo). A word's Cloze probability is defined by the proportion of subjects using that word to complete a particular sentence while contextual constraint is the degree to which the context of a sentence induces an expectation for a particular ending (Bloom & Fischler,
1980). The results indicated that ERP waveforms for highly probable words at the end of highly constrained sentences elicited a late positive complex whereas, low Cloze probability words exhibited a posteriorly distributed
1 The "cloze" method is used in educational research to predict the readability of a particular prose passage (Taylor, 1953). Readers are presented with a number of sentences from which words have been deleted. The reader's task is to fill in the missing words with the most appropriate words for that context. As the context becomes more predictable (reducing the uncertainty about possible alternative completions) the range of responses from a reader becomes smaller. This procedure is used to assess the ability of readers to make use of contextual cues by grade level, (e.g., Rankin & Overholzer, 1969) and by reading level (e.g., Neville & Pugh, 1976-1977) and to assess the amount of information gained from reading a passage (e.g., Rubenstein & Aborn, 1958). In psychology, the cloze procedure can be used to investigate the level of constraint the preceding distribution, number, and structure of words places on a sentence context (e.g., Aborn, Rubenstein, & Sterling, 1959; Miller & Selfridge, 1950) and to look at the effects of context on the latency of word pronunciation (e.g., Stanovich & West, 1979). 26
negative component (N400). The amplitude of the N400 was
found to be inversely related to the subject’s expectancy
for terminal words as measured by its Cloze probability. In
contrast, the level of contextual constraint did not show
significant differences in the N400.
Kutas and Hillyard (1984) stated that if it can be
assumed that the Cloze probability of a word is a measure of
expectancy for its appearance, then it would seem that N400
amplitude may be inversely proportional to word expectancy.
This led them to hypothesize that the N400 may provide a measure of semantic priming, that is, the information in a
sentence activates not only the memory location for the
expected word but also an automatic spreading to nearby semantically related memory networks. The finding of a smaller N400 amplitude for anomalous words that were related
to the most probable (expected) sentence completions would
be anticipated if the spreading-activation process primed the words that were semantically related to the best completions, (i.e., activated them for faster access) even
if those words were nonsensical in that context. Thus,
Kutas and Hillyard concluded that while semantic incongruity
is a sufficient condition, it is not a necessary condition
for the elicitation of the N400.
In order to further investigate the notion of semantic priming, Kutas and Hillyard (1984) reanalyzed their data to
low Cloze probability words that completed highly 27 constrained sentences. They separated the sentences in accordance with whether or not the terminal word was related to the ’’best completion" of the sentence (as rated by 25 subjects on a 5-point scale). The results indicated that
N400 amplitude was indeed sensitive to the semantic relationship between the preceding eliciting words of the sentence and the expected best completion. Significantly larger N400s followed words that were unrelated to the best completion. These results pointed toward a possible reinterpretation of the N400 effect.
Further evidence that the N400 may be related to a more general aspect of semantic processing comes from the work of
Fischler and his colleagues. Fischler et al. (1984) and
Fischler et al. (1985) have pursued the possible relationship between the N400 component and the associational strength between words. Subjects were taught arbitrarily established relationships such as "Diane is a chemist." until the relationships were well learned. Then the relationships were recombined (e.g., Diane is a lawyer.) to make true and false statements and ERPs were recorded while subjects read the statements. False statements elicited an N400 waveform. In the next study, ERPs were recorded to self-referential true and false statements gathered from a subject's own answers on a questionnaire.
Again, results indicated the false statements yielded an
N400 . The results of other recent studies also indicated that
the notion of N400 as an "anomalous reprocessing" ERP
component may be in need of revision. Polich, Vanasse, and
Donchin (1981), for example, compared words in a series in
which the first 6 words belonged to a given category and the
last word either did or did not belong to that category. An
N400 occurred only in response to the last word when it was
not from the same category.
In a later research article, Polich (1985) compared the
Kutas and Hillyard (1980b) sentences with a word-series
reading task to provide physically similar task demands
while manipulating semantic congruency in a nonsentence context. In experiment 1, 80 seven-word sentences (50% congruent, 50% anomalous) and 80 different seven-word series
(e.g. fruit names, flower names) were presented to each
subject. In half the word series the seventh word belonged
to the same semantic category as the first six while in the
other half of the series the seventh word was from a
semantically unrelated category. The results indicated that
for the anomalous sentences a large negative component
occurred at approximately 400 ms but did not occur for the congruent sentences, while both sentence types concluded with a broad, positive-going component. The author stated that the waveform pattern was identical to the one seen in the Kutas and Hillyard paradigm (1980a, 1980b, 1980c). For the word reading series, the anomalous (unrelated category) 29 endings produced a more negative response than the congruous
(same category) endings and both word series conditions produced a negative waveform around 400 ms followed by a positive-going wave very similar to that of the anomalous ending sentences.
In experiment 2, Polich used the same stimulus materials with different subjects. Subjects were required to make a decision (timed button-press) as to whether the ending of each sentence or word series was normal
(semantically congruent) or odd (semantically anomalous).
The results indicated only one major difference between this experiment and the previous one, there was a more enhanced and more precisely defined positive component followed by a reduced or attenuated 400 ms negativity for experiment 2
(imposed decision task) relative to experiment 1 (reading only). In Polich's general discussion, he concludes that the "N400 effect" seems to be extremely sensitive to variations of the semantic appropriateness of words but he also states that the 400 ms negativities "may be a reflection of the system's overall capability to comprehend complex similarities and relationships among stimulus items rather than a unique response to semantic incongruities" (p.
319).
Other studies using single word contexts have revealed
N400 components (Boddy, 1981; Boddy & Weinburg, 1981; Dunn et al., 1987; Sandquist, Rohrbaugh, Syndulko, & Lindsley, 30
1980) although they were not specifically looking for an
N400 as part of their investigations. Sandquist et al.
(1980) presented word pairs to be judged same or different in accordance with semantic, phonemic, or orthographic criteria. Their results illustrated large negative peaks in the 400 ms range for words judged "different" in the semantic condition and smaller negative peaks for
"different" judgments in the phonemic condition. In another study, Neville, Kutas, Chesney, & Schmidt (1986) presented four-word phrases followed by a fifth word which either fit (e.g., "a type of animal. dog") or did not fit
(e.g., "a type of weapon. sheep") the meaning of the phrase. The results indicated that a "no fit" word elicited a significantly larger N400 waveform than a "fit" word. The common element in all these studies is not the occurrence of semantic incongruity per se, but that a semantic analysis is required of words that are unpredictable in the experimental context.
The question could then be asked: Is the N400 due to processing only at the semantic level? Rugg (1984) recorded
ERPs during a task in which subjects discriminated between visually presented, rhyming and nonrhyming, pairs of letter strings that were either word-word or word-nonword combinations. The results indicated a late negative component (N450) over the midline and right hemisphere following nonrhyming words. Since the N450 was observed 31
equally in both nonrhyming word-word and word-nonword pairs,
Rugg suggested that this late negative waveform (N450) might
be generated in response to a "mismatch" of text information
at the phonological level as well as at the semantic level.
However, Rugg also stated that lexical processing, and in
fact lexical processing of a semantic nature, may not be
entirely ruled out as a possible explanation for the
elicitation of the N400 because it is not yet clear by what
process or processes information is extracted from
pronounceable nonwords.
At first glance, it appears that the N400 component has
no clear explanation. However, the common thread that
prevails throughout the literature is that a lack of
semantic context is directly related to the occurrence and
amplitude of the N400. That is, the lack of semantic
context may be the variable that modulates the amplitude of
the N400 and contributes to the N400 becoming a P300 when
the semantic context is not ambiguous. For example, a
sentence that ends anomalously (Kutas & Hillyard, 1982,
1984), word-pairs that are semantically different (Sandquist
et al., 1980), a category word that is not representative of
the given category (Polich, 1985), a false statement
(Fischler et al., 1984, 1985), nonrhyming words and nonwords
(Rugg, 1984), or a word that does not fit the previously
presented phrase (Neville et al., 1986) all elicit a negative component around 400 ms. In contrast, the 32 counterparts in each o£ these aforementioned studies elicit either positive going components or negative components
(N400s) of lesser amplitudes than the most contextually disparate conditions.
In fact, the most recent research supports the idea that the N400 is related to semantic context. For example,
Rugg and Barrett (1987a) compared ERPs elicited by orthographically similar and dissimilar, rhyming and nonrhyming word pairs. Orthographically dissimilar pairs showed an increase in the amplitude of a late negative component (N450) for nonrhyming as opposed to rhyming pairs which was confined almost exclusively to the right hemisphere. In contrast, ERPs to orthographically similar word pairs were smaller in magnitude for the rhyme/nonrhyme comparisons. In their general discussion, Rugg and Barrett conclude that both rhyming relationships and orthographic similarities are sufficient to attenuate the N450 amplitude and when taken together seem to be additive. Whereas, nonrhyming, orthographically dissimilar stimuli
(irrespective of the nature of the orthographic dissimilarity) elicit the N450 with equal facility.
On the basis of several features (latency, topography, and functional criteria), Rugg and Barrett (1987a) suggest that their N450 is closely related to the Kutas and Hillyard
(1982) N400 that is sensitive to semantic relationships between words and has a right hemisphere predominance. Rugg 33 and Barrett (1987b) further suggest that the more extreme distribution observed for the N450 component in rhyme-
judgment tasks results from the lack of a semantic relationship between their word pairs.
Fischler, Jin, Boaz, Perry Jr., and Childers (1987) compared ERP responses to a subject's own name, an assigned
(assumed) name or a false name. The task was to respond positively in a series of statements to the assumed name and reject as false all other names, including the subject's own name. The results indicated the greatest negativity (N380) occurred to false names, followed by the subject's own name and the least negativity to the assigned name. The N380 to a person's own name was more similar (in amplitude) to the false name than the assumed name. Fischler et al. argued that these results indicated the priming of sentence context, through the use of various names, was under the subject's attentional control and that the late negativity can be modulated by that attentional control. This study is important because it demonstrates that subjects can provide their own "internal" semantic context, and that the item which is the most disparate for the task (has the least relation with the context, i. e., false names) causes the greatest negative amplitude.
Van Petten and Kutas (1987) designed a study to explore the use of the N400 ERP component as a measure of semantic priming. Sentences that ended with a homograph were 34 presented one word at a time (e.g., The gambler pulled an ace from the bottom of the deck). Each sentence was followed by a target word that was either contextually related to the homograph at the end of the sentence (e.g., cards), related to the unbiased meaning of the homograph
(e.g., ship), or unrelated to either meaning (e.g., parent).
The results indicated that target words with no contextual relationship to the final word of the sentence elicited the largest N400 component followed closely by contextually inappropriate words. The contextually appropriate words elicited a much smaller N400 compared to the other two conditions.
In their discussion section, Van Petten and Kutas
(1987) conclude that the N400 amplitude reflects "priming across a sentence boundary, as well as priming by a sentence fragment or single word" (p. 199). Since target words with no semantic relationship to the final word of the sentence elicit larger N400 amplitudes than do related target words, it would seem that the N400 amplitude is dependent upon context.
Kutas et al. (1988) looked at ERPs recorded in seven different experiments. They found that when words were sorted as a function of lexical category, content or "open- class" words (e.g., nouns, verbs, adjectives, adverbs) provided greater N400 amplitudes than function or "closed- class words (e.g., prepositions, conjunctions, articles). 35
They then divided the content words in the sentences of various experiments into words that appeared early and those that appeared later (with no first words and no last words included). The results indicated that although both classes of content words (early and late) elicited the N400 component, the early words as opposed to the later words showed a significantly larger N400 . Clearly, the coritent words occurring early in a sentence have "less" context than those that occur later.
Research has related the N400 to other negative ERP components occurring in the same poststimulus time frame and explored the possibilities that one or more of these may have reflected aspects of word phonology or orthography
(Rugg, 1984; Rugg & Barrett, 1987a). Other research attests to the robust nature of the N400 phenomenon. The appearance of the N400 has also been compared in different modalities
(auditory vs visual) (Holcomb, 1985; McCallum et al., 1984), across different populations (congenitally deaf vs hearing)
(Neville, 1985), and in different languages (Besson, Macar,
& Pynte, 1984; Kutas, 1985; Neville, 1985). In all these cases, linguistic processing was required and an N400 type component was found. Although other studies have looked for evidence of an N400 using deviations that are nonlinguistic
(for a review see Kutas & Van Petten, in press), "To date, the N400 response to a deviation within a sequence of stimuli has been obtained only if the context and the 36
deviation are linguistic." (p.16).
Language Related ERPs in Children
Although the N400 has not been specifically
investigated in children, there is a small body of
literature that has studied ERP components with this
population. The following review is provided merely to
illustrate the "flavor" of this type of ERP research since
none of it used complex verbal stimuli (i.e., sentences or
groups of words). Thus, this review is only partially
related to the hypotheses outlined in this dissertation.
However, even though complex linguistic contexts were not
utilized in these studies, (most used pictures, line drawings, simple letters, etc.) it is interesting that several of them did give qualified support to the "context" argument made above.
For example, Kok and Rooijakkers (1985) conducted an
investigation in which ERPs from young children (5-6 yrs old) were compared to those of a group of adults (20-32 yrs old) on both a word reading and a picture recognition task.
For the word reading task, subjects read four different normal or visually degraded three letter words. Whereas,
for the picture recognition task, subjects were given line drawings of either a cat or a dog. One of the two animals served as a target and was shown 35% of the time while the other animal served as background. If a dog was chosen as the target, the cat served as background and vice versa 37
(i.e., the typical odd-ball paradigm).
The results showed that for both the word reading and picture recognition task children produced a positive wave at 280 ms and a long latency negative component (N500). It may be for young children in the picture recognition task, that the target (infrequent stimulus) served as an unexpected event and thus the obtained N500 may be similar to the N400 in adults when the latter receive an unexpected event in a more complex linguistic task (e.g., Kutas &
Hillyard, 1982). It is unclear, however, why the simple task of reading the same four short words repeatedly also produced an N500 component in these children. In contrast, the adult wave forms demonstrated a late positive component
(P340). These differences in waveforms between adults and children are similar to those described by Courchesne (1977,
1978) who used single letters as stimuli and who attributed his findings to differences in the quality or mode of information processing between the groups.
In these studies, Courchesne (1977, 1978) investigated
ERPs in four groups of subjects ranging in age from 6 years to 36 years to ascertain how long-latency ERPs change with age. Subjects counted target slides interspersed among background slides (different slide sets bearing the single letters A or B designated as either target or background).
Also interspersed within the target and background slides and presented to the subjects, were slides designated as 38
either "dim" (a set bearing any one of dimly presented
letters from C to Z) or "novel" (a set bearing different
unrecognizable "novel" color patterns). The results
indicated that targets and backgrounds elicited similar
positive and negative (Nl, P2, N2, and P3) components in
subjects in every age group tested. It was suggested that
the mode and perhaps the neuronal substrates for processing
both target and background stimuli was similar in adults and
children. The latency of the P3 was 300 ms longer in
children (6-8 yr olds, 687 ms) than adults (417 ms) and
reaction time decreased with age (6-8 yr olds 718 ms, adults
430 ms), indicating that the speed of processing these
events may increase with age.
Looking at the results of the "dims" and "novels" seems
to demonstrate a difference in late ERP components between
children and adults when processing unexpected events. All
children in the 6-8 year old range, most children in the 10-
13 year old range, and a few children in the 14-17 year old
range exhibited "Nc" (negative) waves (410 ms and 30 uv) and
"Pc" (positive) waves (900 ms and 30 uv), while most 14-17 year olds and the adult ERPs exhibited an N2 (320 ms) and P3 wave (420 ms and 15 uv) to the same unexpected slides.
Novel slides elicited significantly higher amplitude Nc and
Pc waves than did dims in all age groups. The data seemed to show a transition from childhood wave forms to adulthood wave forms occurring in the mid-teens (14-17 years). It was suggested by Courchesne that the differences in ERP wave
forms between children and adults reflects differences in
the ways children and adults categorize events using their
own internally constructed rules. Whether or not this "Nc"
component in children is related to the N400 described above
(Kutas & Van Petten, in press) is uncertain at this point,
since the context was nonlinguistic and the distribution was
frontal (maximum amplitude at Fz). What is interesting is
that the "novel" stimuli were unexpected by the subject and hence did not "fit" the experimental context they were given.
In addition to the work cited above, Friedman et al.
(1982, 1986) have begun developmental work investigating age-related changes in ERPs spanning subjects as young as 6 years to those in their thirties. These studies also support the argument made earlier, i.e., that increases in
N400 amplitude is inversely related to the amount of semantic context subjects are given or internally produce.
Each subject was presented with a self-initiated sequence of two slides blocked across three conditions, with each of the conditions requiring three different schemes for coding the
information. The slides were pictures that were either physically identical (PID - exactly the same picture), had the same name but could be different parts of the same picture, e.g., a whole zebra and the head of a zebra (NID - name identity), or were in the same category, e.g. a hand 40
and a foot (CID - category identity). Prior to initiating
the testing sequence, the subject was specifically
instructed to look for and match two pictures across three
conditions (same physical, name, or category identity). The
subject then pressed the button and a sequence of two slides
was presented. Subjects were asked to decide whether the
slides were the same or different, relative to the
instructions they were given, by pressing one of two keys.
Preliminary data analyses (Friedman et al., 1982, 1986) showed that all age groups displayed large latency differences between "same" or "different" ERPs in the 400 to
700 ms range. The younger age groups exhibited a late negativity around 400 ms which was much larger for the
"different" than the "same" stimuli across all conditions.
However, the conditions per se produced N400's which differed in amplitude with the category condition producing the largest N400 followed by name and physical identity conditions respectively. In contrast, the older age groups showed a "same-different" effect in a different component and in the opposite direction, i.e., a P300. The authors stated that the positive going portion of the P3 component was smaller in "different" than in "same" ERPs and that the effect was ordered as follows: category had the smallest positive amplitude followed by name and physical identity conditions. The data suggest that in the older age groups, an underlying negative potential may have been responsible 41
for the attenuated P300 for the "different" judgments
relative to the "same" judgments.
The results of the Friedman et al. studies are
supportive of the inverse N400-semantic context argument if
two assumptions are made: First, if it is assumed that even
though pictures were used as stimuli, the naming and the
category instructions produced a linguistic set on the part
of the subject. Second, if it also is assumed that the
instructions subjects were given set up a "mental" semantic
context within the subject. That is, when the two slides
are "different" relative to the instructions to match the
pictures, the mental context produced by those instructions
is no longer valid and an N400 is produced.
Further analyses of these results showed late positive
activity occurring in all age groups (around 500 ms in
adolescents and adults and 700 ms in children). Friedman et
al. (1986) consider this positive activity to be homologous
P300 ERPs in all age groups. P300 activity increased with
age and with complexity of condition (physical identity >
name identity > category identity). The authors noted that
there was a marked discontinuity in latency of the P300
between the 10-11 and the 12-13 year old groups, and they
suggested the possibility of a qualitative shift in
information processing between these groups. Other studies
have also reported morphological (scalp topography or polarity) age-related differences in ERPs when comparing 42 children to adult populations (Kok & Rooijakkers, 1985;
Neville, 1980).
When taken together, these results suggest that there may be differences between the cognitive processing of adults and children. Further, there was some evidence that an "N400 like" component occurred in some of these studies
(Courchesne, 1977, 1978; Friedman et al., 1982, 1986).
However, the fact that such simple stimuli were used may limit the generalizabi1ity of these findings such that they may not relate to more complex linguistic processing. This latter point appears to have some validity based on data recorded from subjects for this dissertation. These data indicated that the 10 and 11 year old subjects produced a waveform pattern similar to that reported in the adult ERP literature (Kutas & Hillyard, 1980a, 1980b, 1982). That is, a negative component with a latency of 350-400 ms and most prominent in amplitude at central sites (Fz, Cz, Pz) was evident in response to anomalous ending sentences while the endings of congruent sentences produced a positive component.
It is surprising that so little language related ERP research has been done with children, given that several notable researchers have stressed the importance of developmentally related work of this type (Courchesne, 1983;
Friedman et al., 1982). As was shown above, what little research has been done, has utilized simple visual 43 discrimination tasks and stimuli (e.g., single letters, pictures, simple objects, line drawings, etc.) when studying children or when comparing children to adults.
Topographic Mapping of Brain Electrical Activity
Electrical activity recorded from the brain is a complex summation of varying frequencies and voltages related to changes in the electrical charge of neurons to internal (within the individual) and external (within the environment) stimuli (Gardner, 1975; Torello & Duffy, 1985).
The measurement of EEG is accomplished by placing numerous electrodes on the scalp above brain areas of interest.
These scalp electrodes are sensors which detect the small summated electrical changes emanating primarily from neuronal cells within the underlying cortex of the brain
(Spehlmann, 1981).
There are two methods of analysis of EEG data typically used in medical, psychological, and educational research.
The first method is frequency analysis which utilizes a Fast
Fourier Transform (FFT) to break the EEG into selected frequency bandwidths in order to determine the amount of activity in a specific frequency band. Several EEG bandwidths have been identified over the years [delta (1-3
Hz); theta (4-7 Hz); alpha (8-13 Hz); beta (>13 Hz) mu etc.]
(Gardner, 1975). The second method is signal averaging
(which was used in the present research) and involves the recording of EEG during multiple presentations of a 44
specific, time-locked, stimulus to the subject. As
mentioned earlier, these separate records can then be averaged together to increase the signal (the specific brain
electrical events related to the stimulus) from the
background EEG noise (unrelated to the stimulus). The
resultant waveform produced by the averaging technique is
called the event-related potential or the ERP (Dawson,
1951).
Even though frequency analysis and signal averaging greatly reduce the data which have to be interpreted, neurologists as well as researchers are still faced with the task of interpreting vast arrays of data, including the spatial and temporal relationships among numerous recording electrodes that are used to measure ongoing brain activity.
From this enormous amount of data, the clinician attempts to determine if these patterns are significantly different from normal patterns, while the researcher tries to relate this activity to ongoing cognitive processes. Obviously, this is not an easy task and requires years of training to become even partially proficient (Languis & Wittrock, 1986; Torello
& Duffy, 19 8 5).
Fortunately, a new computer based technology has been developed to deal with this problem of data reduction and
interpretation, namely topographic brain imaging (Languis &
Wittrock, 1986; Torello & Duffy, 1985). Topographic brain imaging is a new methodological technique which can 4 5
condense, summarize and display on a computer monitor
spectral, spatial, and temporal information from brain
electrical activity (EEG) that was collected from numerous
scalp locations. The data can be statistically compared to a control group or compared within subjects to a baseline
measure. The product of this technology is a topographic
map of electrical activity from the entire cerebral cortex
(Duffy, Burchfiel, & Lombroso, 1979; Duffy & McAnulty 1984).
Topographic brain imaging has been compared to the construction of an isotherm map, that is, through the use of exact temperatures from varying points in a country (e.g.,
towns) it becomes possible to predict and display temperature readings for any area of that entire country.
Brain imaging works on an analogous principle. It constructs an electrical activity map of the brain's surface through the use of readings (voltages) from specific recording sites and interpolates those values (based on the three or four nearest actual electrode values) to produce a kind of iso-EEG map or picture of brain electrical activity
(Languis & Wittrock, 1986; Torello & Duffy, 1985).
Topographic imaging of brain electrical activity has proven to be a successful tool in clinical diagnosis of, for example, brain tumors. Duffy et al. (1979) compared seven tumor patients and seven controls using topographic imaging of visual evoked potentials. The results indicated that tumor sites showed a depression or absence of electrical 46 activity. In addition, there was abnormally persistent late electrical activity overlying the tumor site along with an asymmetrical spread of activity. Topographic imaging was able to differentiate the two groups of patients (tumor from normal control) even though the tumor patients had normal
"classical" EEG recordings.
Psychiatric research has also successfully used topographic imaging of brain electrical activity in the study of schizophrenia to differentiate schizophrenics from normal controls (McCarley, Torello, Shenton, & Duffy, 1985;
Morihisa, Duffy, & Wyatt, 1983; Morstyn, Duffy, & McCarley,
1983; Torello & McCarley, 1986). In a recent chapter, Duffy et al. (1984) have discussed research areas, in addition to psychiatry, in which topographic brain imaging has been used. For example, topographic imaging has played a role in cerebral vascular disease (Nagata & Mizukami, 1981), basic auditory physiology (Wood & Walpow, 1982), the localization of cerebral processing (Gevins, Schaffer, & Doyle, 1983) and the topographic signature of epilepsy (Lombroso & Duffy,
1980 ) .
The diagnostic utility of brain imaging has demonstrated that dyslexia is a neuropsychological problem with specific areas of brain dysfunction (Duffy, Denckla, &
Sandini, 1980; Duffy, Denckla, Bartels, Sandini, &
Keissling, 1980). In fact, when diagnostic rules are developed using the numerical values of topographic mapping, 47
Duffy and his colleagues have shown that subjects can be
successfully classified as normal or dyslexic 80 to 90 per
cent of the time.
In addition to the work being done in the medical and
neuropsychological fields, utilization of topographic brain
imaging has begun in the field of education. Work has been
done at Ohio State University's Brain Behavior Laboratory
that explores the use of brain mapping as a tool to teach
students varying cognitive strategies to improve their
learning and exercise greater control over the learning
process (Languis & Wittrock, 1986; Andrews, 1985). Naour
and Languis (1986) designed a study to evaluate topographic
brain mapping as an assessment tool for the identification
of learning disabled students within the schools. From the
Naour and Languis work, a reclassification of learning
disabled students and controls was begun using Kaufman's
WISC-R scores. The purpose of this research is to more
effectively classify problem learners in accordance with
their brain electrical activity patterns (Miller & Languis,
1988. Finally, developmental differences have been reported between the 6-8 and 10-12 year old ranges using a brain mapping assessment protocol developed by Languis and his colleagues (Wilson, Naour, & Languis, 1988; Miller &
Languis, 1988 ) .
Topographic brain imaging has also been used to differentiate among different cognitive processing 48 strategies within the same individual (Dunn et al. 1987; B.
Dunn, Languis, Dunn, & Andrews, 1988; Schaff, Languis, &
Russell, 1988). In the Dunn et al (1987) study, for example, adult male subjects were given three tasks varying in cognitive complexity ranging from simple reading of randomly chosen words as they flashed on the screen, to memory tasks which required subjects to learn and recall words in the order they were presented (serial order) or to place words into categories for later recall. The topographic maps produced showed that different patterns of cortical EEG activity were generated as subjects performed each task. This was confirmed by subsequent statistical analysis. In a later study (Dunn et al., 1988), topographic mapping was able to differentiate among men and women as they performed identical reading and memory tasks, particularly in the N400 range.
In conclusion, the above studies suggest that topographic brain imaging could be used to investigate the
N400 component in 10-11 year old boys as they processed anomalous and congruent sentence endings, read words, and encoded words into categories for later recall. Thus, the literature reviewed in this chapter served as the basis for this dissertation and lead to the rationale and hypotheses stated in Chapter I. Since these hypotheses were described in detail in that chapter, they will not be reiterated here.
The next chapter describes, in detail, the method and 49 procedures used in this dissertation. In addition, the data reduction and data analysis techniques are explained and discussed. CHAPTER III
METHOD
Introduction
This chapter is organized into six sections. The first section, Selection of Subjects, discusses the sample population, how that sample was chosen, and relevant demographics regarding subjects that participated in the research. In the second section, Stimuli and Materials, the two types of semantic tasks that were presented to the subjects and the sources for the construction of those stimulus materials are discussed. In the third section, the
Recording System, the technical equipment used for both displaying the stimulus materials and collecting the EEG data generated is described. The fourth section, Subject
Preparation and Experimental Procedures, presents a detailed chronology of the research, from the time the subject was transported to the laboratory to the completion of his participation as a subject. The fifth section, Data
Reduction, describes how the individual EEG trials were converted to a summated, artifact-free ERP waveform ready for statistical analysis. In the sixth and final section of this chapter, Data Analysis, the statistical procedures used for analysis of the research data are explained and
50 51
discussed.
Selection of Subjects
A research proposal was submitted to the Director of
Curriculum for a suburban school district within the
Columbus, Ohio area along with Ohio State University's Human
Subject's Approval Form on file under approved Protocol
#85B0143 and #81H0312 (Appendix A). After permission Was
granted from the Director of Curriculum to conduct research
in an elementary school within the proposed school district,
an elementary school principal was contacted. The principal
arranged for school personnel to assist in identifying
possible participants for the study using the guidelines
specified in the research proposal (referred to above). A
letter was sent home to the parents of prospective
participants (Appendix B) informing the parents about the
study, asking permission for their child's participation as
a subject, and requesting the presence of the parents and
their child at a meeting to further explain the procedural aspects of the research. Subsequently, parents were
telephoned and a convenient day and time was arranged for
their child's participation as a subject. Prior to their
child's participation in the research, parents were given a
sample of the tasks their child would be asked to perform
(Appendix C). They were asked to read and sign a "Consent to Special Treatment and Procedure" form (Appendix D), and they were asked to sign a permission form to obtain scores 52 on their child from school records. These efforts resulted in the participation of 12 right-handed, fifth grade students. Two additional subjects (from a comparable suburban school) were the stepson and neighbor of the coordinator of the Ohio State University's Brain-Behavior
Laboratory. One of these students attended the fifth grade and the other the sixth grade. Thus, 14 right-handed male students from two suburban elementary schools in the
Columbus, Ohio metropolitan area volunteered as subjects in this study.
The subjects ranged in age from 10.58 to 11.75 years
(M = 11.17), had intelligence quotients that were normal to above normal (range 110 to 143, M = 122, SD = 10), and had vocabulary and reading scores on or above grade level
(reading range 45% to 98%, M = 74.3%, vocabulary range 53% to 95%, M = 75.6%, respectively). Scores were obtained from school records after parental consent was given.
Stimuli and Materials
Two different semantic tasks were presented to the subjects, beginning with semantic task one (recognizing anomalous and congruent sentence endings), followed by semantic task two (the reading of a list of unrelated words and the categorizing of a list of words into two groups).
Semantic Task 1 -- Congruous and Anomalous Sentence
Endings. Ninety declarative sentences ranging in length from 5 to 9 words were constructed (Appendix E). The 53
sentences were derived from Bloom and Fischler's (1980)
"Completion Norms for 329 Sentence Contexts" and from fourth
and fifth grade spelling and English texts published by
McDougal, Littell and Company (Bell, Dossa, Paden, &
Schaffrath, 1984; Bohen & McConnell, 1984).
Half of the sentences ended with a congruent word
(bringing a meaningful conclusion to the sentence). The
other half ended with an anomalous word (thereby terminating
the sentence in a confusing manner). The mean number of
words contained in the congruent and anomalous sentences
were 6.8 and 6.9 words, respectively. Pilot work prior to
this dissertation, suggested that fatigue was a factor in
the first semantic task (anomalous and congruent ending
sentences). Based on this information, the sentences were
divided into six blocks of 15 sentences (rather than the
three blocks of 30 sentences used in the pilot study) in
order to allow subjects to have shorter periods of
concentration and additional time periods to rest.
The congruent and anomalous sentences were ordered
quasi-randomly across all sentence blocks. The final word
of every sentence was presented with an asterisk beside it
(a period was not as easily seen on the computer screen) which would indicate to the subject that the sentence had ended.
Semantic Task 2 -- In the second semantic task, the reading condition was presented prior to the categorizing 54 condition to prevent the confounding of instruction with condition, i.e., in the reading condition the subject was asked to silently read the words while in the categorizing condition the subject was asked to memorize and recall the words into categories. Presenting the categorizing condition prior to the reading condition might have caused the subject to inadvertently memorize and categorize the reading list.
Reading Condition. Two word reading lists (reading list 1 and reading list 2) were derived from Posnansky's
(1978) "Category Norms for Verbal Items in 25 Categories for
Children in Grades 2-6" (Appendix F). The two lists were compiled by selecting one word from each of 16 different categories. The words in the lists (list 1 and list 2) were then placed in quasi-random order three times to allow for three separate presentations of that word list.
Categorizing Condition. Four 8-word categories were derived from Posnansky's (1978) "Category Norms for Verbal
Items in 25 Categories for Children in Grades 2-6" (Appendix
G). They were combined to make up two equivalent category word lists (category list 1 and category list 2). Each list consisted of 16 words, eight words from each of two different categories. As with the reading word lists discussed above, each of the category word lists (1 and 2) were placed in quasi-random order three times for three separate presentations of that list. The category word 55
11sts were presented in alternating categories such that two words from one category would not follow one another in sequence. This presentation order followed that used by
Dunn et al. (1987, 1988) with adult subjects.
Recording System
Figure 2 diagrams the complete EEG recording and analysis system. All recordings were made on-line using a
16 channel Beckman Accutrace polygraph with the low and high frequency cut- offs being set at .5 Hertz (Hz) (time constant at .30 seconds) and 30 Hz, respectively.
Preceding each experimental session all EEG channels were calibrated and adjusted to ensure equal gains and direct current (DC) offset. A calibration signal of 50 microvolts
(uv) was recorded before and after each data collection session. The polygraph was coupled to a Digital Equipment
Corporation's Model PDP 11/34 computing system. The EEG data were digitized via a 12 bit analog to digital (A to D) converter and were stored directly on RK05 hard disks for later processing. Sixteen channels of data were sampled once every 2 milliseconds (ms) for 1024 ms (one trial or epoch), resulting in 512 data points being collected and digitized during an epoch. While the digitized data were being stored on hard disk, they were also fed into a digital to analog (D to A) converter for the purpose of monitoring the subject's EEG on a Tectronics Model 524 oscilloscope, while it was being collected. PDP1 1 /34 COMPUTER
R K 0 5 D is k tE G C o n ve rte r Data
16 Channel A ccutrace Polygraph •• Com puter C o n ve rte r Display CPU M o n ito r
Aa / SUBJECT
FT inter Com puter Oscilloscope O p o ta tc rs Term inal
Figure 2. Diagram of the recording system. 57 subject Preparation and Experimental Procedures
Each subject was transported to and from the Ohio State
University's Brain-Behavior Laboratory by either their parents or by the experimenter. Half of the subject's participated during a two hour period in the morning while half participated during an equivalent period in the afternoon.
Upon arrival at the laboratory, each subject was given a tour of the facility then guided to a seat where the experiment was explained. Questions were answered regarding the equipment and procedures which would follow, then preparation of the subject began.
A modified Edinburgh Handedness Inventory (Oldfield,
1971) was administered to the participant to confirm the right handedness of the subject using a 16-item inventory
(right handedness, M = 14.5, SD = 1.4). Health related questions were asked the subject to establish normal well being, i.e. was the subject currently ill, was he on medication, how much sleep had the subject had during the previous night (Appendix H). The subject was then fitted with an Electrocap containing 21 tin electrodes nine millimeters in diameter. [The use of an Electrocap, rather than individually placed electrodes, has been demonstrated to be a reliable way of collecting EEG data (Languis,
Miller, Alter, Brown, Cobbs, Drake, Dunn, Monk, Pocius,
Roberts, & Wilson, 1987; Neville et al., 1986; Polich & 58
Lawson, 1985)]. Fifteen of these electrodes were used as
active recording sites (Fpl, Fp2, F7, F8, Fz, T3, C3, Cz,
C4, T4, T5, T6, Pz, 01, 02) referred to linked ears, with
site Fpz serving as subject ground (see Figure 1, Chapter I,
page 6). All placements were in accordance with the
International 10/20 System (Jasper, 1958).
After the cap was placed on the child's head, an
abrasive paste (Omni-prep) was used to clean the scalp under
the sensors and a water soluble gel (Electro Gel) was
inserted through a hole in the sensors to improve contact
with the subject's scalp (thereby reducing electrical
impedance) to improve the signal to noise ratio. Eye
movements and blinks were recorded from an electrode placed
on the infraorbital ridge of the left eye (below the left
external canthus), which was referred to another electrode
placed above the right eye on the supraorbital ridge (above
the right external canthus). Impedances for all electrodes did not exceed 5 kohms. Further the difference between any
two electrodes did not exceed 3 kohms. Impedances were
recorded before and after each data collection session and were checked prior to each of the experimental tasks.
The child was then connected to a polygraph and was
shown his own brain waves as they appeared on an
oscilloscope. It was explained to each subject that movement of the eyes, mouth or any large muscle would result
in peaks of electrical activity (spikes) called artifacts which would not allow the use o£ the brains electrical activity that coincided with that muscle movement. The subject was then asked to blink his eyes, move his mouth, wrinkle his forehead, and clinch his teeth and was shown on the oscilloscope what an artifact would look like as he was producing it. The subject was asked to refrain from making such large movements, if possible, during the recording of brain activity and was told he would have an opportunity to rehearse remaining very still while he was reading practice sentences on the computer screen.
The distance from the subject's nose to the center of the computer monitor was 61 centimeters and the incandescent lights were adjusted to a dimly lit position. The level of luminance both in the room and of the stimulus materials remained constant across subjects. The subjects received practice on five trial sentences (Appendix I) prior to the experimental data collection, as pilot work found this number to be sufficient to instruct the subjects.
Words were presented one at a time in the center of the computer screen at the subject's eye level. Stimulus presentation was computer controlled with each word being presented on a high resolution, black and white computer monitor (Peritec) for 160 ms following a 100 ms prestimulus baseline. EEG recording was time-locked to the stimulus presentation. The interword interval was 2048 ms for all tasks (sentences, reading, and categorizing). For the 60
sentence conditions, the intersentence interval was 3072 ms.
Due to the storage limitations of the computing system, data
were collected on only the last word of each sentence, i.e.,
the congruent or anomalous ending, but were collected during
the presentation of every word for the reading and
categorizing tasks.
After the five practice sentences, each subject was
given Semantic Task 1, i.e, the anomalous and congruent
sentence task. Subjects were instructed to silently read
the sentences one word at a time as the word appeared on the
screen. They were told that each sentence would end with an asterisk and that some of the sentences would "make sense" and some would "not make sense." They were also told to
remember as many sentences as they could since they would be
given a printed list of "old" and "new" sentences and asked
to indicate with a check by the word "yes" or "no" whether
or not they remembered reading the sentence. In addition,
they were told that they would be asked to rate the ending
words of the sentences as to their unexpectedness or "how
much sense" the ending word made.
After every two blocks of 15 sentences, the subject
completed a sentence recognition and rating task (see
Appendix J for the written behavioral measure). Subjects
read the sentences and indicated "yes" or "no" with a check mark whether or not they had seen the sentences previously.
This procedure helped assure that the sentences were read 61
and processed during the recording o£ EEG. In addition,
subjects rated each sentence on a 5-point Likert Scale as to
how "likely" or "unlikely" the sentence ended. This rating
indicated whether or not the anomalous and congruent endings
were perceived by the subject as they were intended. These
written behavioral measures were modeled after those used by
Kutas and Hillyard (1980c, 1982). The behavioral measure
for the sentences consisted of six sets of 20 sentences.
For every two blocks of 15 sentences viewed by the subject,
there was a sentence set A and a sentence set B. Each set A
and set B consisted of 16 "old" sentences from the two
blocks just seen and 4 "new" sentences that were not in the
blocks. Each subject received either set A or set B. The
sets (A and B) were counterbalanced across subjects such
that every subject had a chance to recognize and rate 1/2 of
the sentences they had just seen. This behavioral measure
was constructed in such a manner (with each subject rating
only 1/2 of the sentences) to reduce the amount of time the
subjects participated in the study.
As mentioned in the Stimulus and Materials section above, after completing Semantic Task 1, each participant received Semantic Task 2. For all subjects, however, the word reading portion of that task was always presented prior to the categorization portion.
For the reading condition, each subject received either reading list 1 or reading list 2 (counterbalanced across 62 subjects). Subjects were instructed to silently read the words as they appeared on the screen. They were told that no written task would follow these lists but that they would be reading the same list of words three times in varying word order. The reading condition controlled for the perception and recognition of words.
When the reading task was completed, each subject received either category list 1 or category list 2. As with the reading word lists, lists were counterbalanced across subjects.
The instructions to the subjects for the category condition were to read the words silently and remember them in categories. The subjects were told that they would be asked to write down as many of the words as they could remember after each of three different presentations of the same category word list. They were also told that they should try to remember the words in two separate categories and write them down in those categories. This written behavioral measure assured that the words were recalled and categorized into groups as intended.
All subjects were debriefed following the data collection procedure and all electrodes were removed. Each subject observed a portion of the data editing on his own data. Topographic imaging of his edited and averaged data were demonstrated to the subject who was then allowed to create maps of his choosing through the use of a computer 63
mouse. The maps along with a "Certificate of Participation"
were given each subject prior to his departure from the
Brain Behavior Laboratory.
Data Reduction
Prior to data analysis, a given subject's raw EEG data
were edited one trial or epoch (1024 ms) at a time to remove any epoch which included muscle or eye movement artifact
from the data. This was accomplished by reconverting the digitized EEG data to analog form using the computers D to A converter (described earlier) for the purpose of displaying the data on the oscilloscope. A specially written computer program displayed each epoch individually in order that it could be examined for artifacts. If the epoch was acceptable, the experimenter saved it in the subject's edited data file. If the epoch contained artifacts, the experimenter deleted it from the subject's file. The epochs that were free of artifact then were averaged together for each subject for that condition. According to theory, by averaging EEG data time-locked to a specific stimulus (in the present case, a word on the computer screen), the random noise in the EEG record will sum to zero, whereas the brain's unique response to the stimulus (e.g., a word) will remain in the resulting averaged signal or waveform. Again, this unique response is termed an event-related potential
(ERP). 64
The above editing and averaging process was repeated, to produce an ERP for each condition. That is, each subject had an ERP file for both anomalous and congruent sentences, an ERP file for word reading, and an ERP file for the categorization of words. Table 1 shows the means and standard deviations for the trials accepted per subject within each condition. A one-way repeated measures ANOVA indicated there were no differences among these four means
[F (3, 36) = 1.16, p. > .34.
Table 1
Mean Number of Trials Accepted Per Subject by Condition
Anomalous Congruent Reading Categorization
M 35.54 32.15 34.92 36.07
SD 6.05 8.36 8.81 6.96
Each subject's ERP file for each condition was then adjusted to baseline for the purpose of removing any DC offset. This was accomplished by averaging the first fifty data points (collected during the prestimulus baseline).
The resulting average was then subtracted from each of the
512 data points contained in each ERP file. 65
Data Analvs Is
While editing each individual's data, it became
apparent that one subject's EEG data contained numerous
artifacts which were produced during data collection on the
first semantic task (congruent and anomalous sentences).
Because of this artifact contamination, the EEG data from
that subject were not included in the data analysis for that
task. However, the EEG data produced by that subject for
the remaining tasks (reading and categorization of words),
were acceptable (over 50% of the EEG trials were free of artifacts). Consequently, these data were included in these
latter analyses.
The EEG data were analyzed using a series of T-tests
for each sample point for each channel which is an accepted analysis procedure for brain imaging data and is similar to
the procedure described by Duffy et al. (1979). In the case
of the present data, a channel corresponds to 512 sampled points (A-D values collected every two ms) for each brain site (15 channels of EEG and a channel to monitor eye movements) collected over each epoch (1024 ms). The actual statistical package that was used was developed by Robert
Norman, Ph.D. of Neuroscience Systems, located at Los Altos,
Cali fornia.
After all subjects' data for each experimental condition were edited and reduced to averaged waveforms (one
for each channel), the data for a given condition (e.g. 66 anomalous sentence endings) were subjected to a program called VSTAT which computed the sums and sums of squares for each data point of the subjects' averaged waveforms (one for each site) for that condition. The result was 16 channels
(one for each recording site) containing 512 sums and 16 channels containing 512 sums of squares collapsed across subjects.
When VSTAT was completed, the resulting sums and sums of squares were then subjected to two other programs. The first of these was VMEAN, which computed either channel means or channel standard deviations. The second program was called TWAVE and has been the traditional method of testing the significant differences of a channel against either the EEG baseline, or the comparison of particular waveforms from two experimental conditions (e.g. anomalous sentence endings versus congruent sentence endings) (e.g.,
Duffy et al., 1979).
However, recently there has been a controversy concerning the use of analyzing EEG data using statistical packages like TWAVE since they produce large numbers of t values. Some researchers (Oken & Chiappa, 1986) argue that such methods produce numerous alpha errors since so many of those t's would be significant by chance. Because of this controversy, a much more conservative approach was taken in this dissertation. In order to explain the rationale for being more conservative (and thereby deviating somewhat from 67
the previously submitted dissertation proposal) it is
necessary first to describe the "traditional" multiple t
method which was originally going to be used as well as the
critique of this method.
The use of TWAVE would result in 8192 t values being
computed for each of the hypothesis tested in this dissertation. That is, t values for each of 512 sample
points by each of the 16 channels (electrode sites) would
have been computed. Where channels would have been compared
to the EEG baseline (Hypotheses 1, 2, 4, and 5), the t's
would have represented the significance test of the difference of the mean value of a given site (e.g., Pz) at a given sample point (e.g., 400 ms) being tested against the mean ERP prestimulus baseline. The scores comprising the
latter mean were computed by taking the average of each subject's 100 ms prestimulus baseline.
When any two experimental conditions would have been compared (Hypotheses 3, 6, 7, 8, 9, and 10), a given t value
for any channel (site) would have been the significance test of the mean difference of condition 1 (e.g., anomalous sentence endings) versus the mean difference of condition 2
(e.g., congruent sentence endings) for that channel at a given sample point (e.g., 400 ms). Thus, for example, a value of 2.9 at 400 ms for channel or site Pz, would have represented the obtained t value resulting from the significance test of the mean difference in ERP amplitudes 68
produced by the subjects while reading the anomalous endings
of sentences versus the congruent endings of sentences.
Obviously/ 8192 t tests (512 sample points X 16
channels) for each of the experimental hypotheses was
unacceptable and might have supported criticism of the
traditional method. Several suggestions have been made by
critics of the method in order to reduce the possibility of
making alpha errors. Which in this case would result in 405
significant t tests at the .05 level by chance.
Oken and Chiappa (1986) note, among other things, that
researchers should:
1. Decide prior to the study to analyze a limited
number of variables. This was anticipated in the present dissertation and only a priori comparisons were planned (see
listing of hypotheses).
2. Focus only on those variables that are particularly relevant to the study. In the present case the area relating to the 250-500 ms (N-400) and the 500-924 ms ranges best described the data.
Examination of each subjects ERP's indicated that an
N400 type waveform occurred earlier in the 10-11 year old boys used as subjects in this study than in adult subjects
(e.g., Kutas & Hillyard, 1982). Therefore the ranges reported in the proposal for the present dissertation were changed in order to better describe the data. That is, a range of 250-500 ms was used instead of the originally 69
proposed 300-600 ms range. The other range used to test
all the hypotheses reported earlier was 500-924 ms.
3. Variables may be pooled or data combined into one
overall measure to reduce the number of t tests considered.
In order to more fully comply with suggestions 1, 2,
and 3 above, the data were reduced further using a specially
written computer program. First, the program searched and
stored the most negative peak amplitude and the most
positive peak amplitude for each electrode site within a
given range (e.g., 250-500 ms) for each subject. It then
stored the latency of those positive and negative peaks.
Further, the average mean amplitude for each recording site
within a given range (250-500 ms, 500-800 ms, and 800-924
ms) was calculated by summing the value of each data point
within each range and dividing that sum by the total number
of points stored i.e., an arithmetic mean. This latter
measure is a highly conservative measure and is in keeping
with suggestion 3 above. The program then was run on each
subject's ERP data for each of the experimental conditions,
thereby producing the data used for all subsequent
statistical analyses (peak amplitudes, peak latencies, and
average mean amplitudes for each electrode site in specific
ranges).
By reducing the amount of data to be analyzed, the
number of t tests was greatly reduced when TWAVE was run.
For example, the number of t tests that would have been run 70 to test each of the experimental hypotheses using the traditional method would have been 5392 over the ranges of
250-500 and 500-924 ms (i.e., 125 data points for the first range + 212 data points for the second range X 16 channels).
This was reduced to a maximum of 160 t tests and in some cases only 80 t tests for each of the hypotheses using the method described above [i.e., 5 t tests for each of the ranges (one negative peak, one positive peak and their respective latencies, followed by one average amplitude for each range) by 2 ranges maximally, 1 range for some hypotheses by 16 channels or sites]. Besides the ranges used to test the hypotheses, other ranges were examined on a post-hoc basis, merely to serve as a basis for future research.
In conclusion, this chapter gave a detailed look at the methodology involved in obtaining subjects, the construction of the semantic tasks and the setting up of technical equipment to present stimuli and collect data. In addition, this chapter explained the procedures involved in preparing subjects for EEG data collection as well as the experimental instructions and written behavioral measures they were given. Finally, the techniques used for the reduction and analysis of the EEG data were described. In the next chapter the results of the data analyses for both the written behavioral data and the EEG data will be presented. Chapter IV
RESULTS
Introduction
This chapter is organized to present the results of the
data under four major headings or sections. The first
heading entitled Behavioral Data, presents the results of
the written behavioral measures. The second heading,
Comparison of ERPs to Baseline, describes the results of
four hypotheses (1, 2, 4, and 5). The third heading,
Comparison of Condition vs Condition ERPs. lists the results
from the six remaining hypotheses (3, 6 , 7, 8, 9, and 10).
The final heading, Other ERP Findings, presents significant post hoc comparisons (not previously discussed) for two
hypotheses (7 and 10).
Behavioral Data
In order to be certain that subjects were properly attending to the experimental tasks, behavioral measures
(mentioned earlier) were taken. As reported below, all measures indicated that subjects attended to the tasks they were given. Consequently, differences in ERPs recorded during these tasks were assumed to be indicative of differential cognitive processing.
71 72
Semantic incongruity ratings. Written behavioral measures were given each subject to assess the degree to which the ending words of the congruent and anomalous sentences were perceived as "making sense" or "not making sense" at the end of that sentence. On a 5-point Likert scale, the number 1 indicated a very "likely" ending to the sentence while the number 5 indicated a highly "unlikely" ending. Over all subjects, the mean rating for the congruent ending sentences (M = 1.10, SD = .116) contrasted sharply with the mean rating for the anomalous ending sentences (M = 4.80, SD = .171). This difference was highly significant [t (12) = 50.40, a < .001], strongly indicating that subjects were able to distinguish between anomalous and congruent sentence endings.
Recognition of sentences. To assure that the subjects were reading and recognizing the sentences they had previously seen, each subject was asked tocheck "yes" or
"no" on a behavioral written measure. Each answer indicated whether or not the written sentence on the page was one that the subject remembered as being within the list of sentences he had read on the computer monitor. The subjects correctly identified an average of 90% (M = 90.4%,
SD = 8.4%) of the sentences that they had previously seen.
They were also able to indicate, on the average, 81% (M =
81.4%, SD = 18.7%) of those sentences that were new to them and had not been part of the list they had been given. A t 73
test showed no difference in the recognition of the items in
or out of the list [t (12) = 1.90, p. > .08). This indicates
that the subjects read and recognized the sentences they had
seen during the experiment.
Category recall. The subjects were able to correctly
recall and categorize an average of 72% (M = 71.9%, SD =
1 0 .6%) of the words they had been shown in the
categorization condition. The Ratio of Repetition average
across all subjects for the categorization of a list was a
high .856, suggesting that the subjects recalled the words
into categories as instructed.
Comparison of ERPs to Baseline
ERP data. When many subjects' data are analyzed to
produce an ERP for any given experimental condition (as is
typically the case in ERP research) individual variation is averaged together. If this variation is large, it is
possible for the obtained mean or group ERP to be so small
that it is not significantly greater than a chance ERP
baseline. For this reason (as was mentioned earlier) each
of the ERPs for each of the experimental conditions was
tested against baseline, thereby generating hypotheses 1 , 2,
4, and 5. If the experimental conditions were not different
from baseline, it would be meaningless to test differences among them. Fortunately, as will be shown below, each of the areas of interest for each hypothesis was significantly greater than baseline. 74 Hypothesis 1: It is expected that sentences with anomalous endings will produce a statistically significant late negative ERP component ranging in amplitude from 3-8 microvolts (uv) and having a latency of 300-600 milliseconds
(ms) when compared to subjects' ERP baseline.
As can be seen in Table 2 there were 12 channels or sites having a negative component (N4) which was significantly different from baseline in the 250 to 500 ms range. The largest peak amplitudes occurred at sites Fz (-
10.33 uv) and Cz (-10.0 uv). The significant mean peak amplitudes ranged from -3.0 uv at site 01 to -10.33 uv at site Fz. Mean latencies of the significant amplitudes ranged from 332 ms at site Fz to 428 ms at site 01.
Figure 3 shows the waveform for each site as well as a topographical map of the N400 amplitude distribution across the cerebral cortex for the most negative peak between 250 and 500 ms across all 15 scalp sites. The analyses of the data, as shown in the table and depicted in the figure, supported Hypothesis 1. Therefore, Hypothesis 1 was accepted.
Note, that the computer can generate a separate topographic map for each data point sampled. Thus, in the present case 512 separate maps could be drawn, since 512 data points were collected across the 15 scalp sites. The computer generates a map at a particular time point, e.g.,
300 ms, by taking the amplitude for each of the sites at 75
Table 2
Significant Mean Peak Differences (in uv) between Anomalous
Sentence Endings and ERP Baseline
Anomalous Endings
Site M SD T Value
Fpl -8.33 7.62 3 tg****
Fp2 -8.0 8.13 3.e**«*
F7 -7.67 6.70 4.1****
F8 -5.67 5.04 4.1****
Fz -10.33 6.85 5 .4****
Cz -10.0 5.60 6 .5****
Pz -6.0 6.35 3.5***
T3 -6.67 5.48 4 .5****
T4 -4.33 2.35 7.1****
C3 -9.33 6 . 44 5 .3****
C4 -7.67 4.55 6 .2****
01 -3.0 3.30 3.2***
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Figure 3. Event-related potentials by recording site for the anomalous ending sentences (---- ) and a topographic ma showing the distribution [in microvolts (uv)] of the N400 peak amplitudes across the scalp. 77 that time point and doing a linear 4-point interpolation to generate a topographical map of the entire cortical surface.
This interpolation procedure allows a map to be drawn at any point of interest. In the present case, all maps were drawn using ERP data collected after the stimulus word was presented. Additionally, the maps in the figures corresponding to these dissertation hypotheses were based on the program which sought out the most negative and most positive peaks within a specified range of milliseconds (ms) or calculated a mean amplitude over a specified range of latencies (explained in the Data Analysis portion of Chapter
III) .
Hypothesis 2: Sentences with congruent endings will produce a statistically significant late, positive going ERP component ranging in amplitude from 4-12 uv, and having a latency from 300-600 ms poststimulus relative to subjects'
ERP baseline.
As can be seen in Table 3, all 15 scalp sites were found to be significantly different from the baseline in the
250-500 ms range. The mean peak amplitudes varied from 3.0 uv at site F7 to 16.67 uv at sites 01 and 02. One of the highest mean amplitudes occurred at site Pz (16.0 uv). The mean latencies for these significant amplitudes ranged from
282 ms to 392 ms at sites Fpl and T3 respectively. 78
Table 3
Significant Mean Peak Differences (in uv) between Congurent
Sentence Endings and ERP Baseline
Congruent Endings
Site M SD T Value
Fpl 4.67 3.17 —5.3****
Fp2 5.67 4.71 -4.5****
F7 3.0 2.41 — 4.7****
F8 4.33 4.21 — 3. 9****
Fz 6.67 5.52 — 4 . 3****
Cz 9 .67 4.74 -7.4****
Pz 16.0 7.34 -7.8****
T3 7.0 4.66 -5.4****
T4 7.0 3.67 -7,o****
C3 10.0 5.12 —7.1****
C4 9.67 5.13 -6 .9****
T5 12.0 5.34 -8 . 2****
T6 12.0 5.19 - 8 .5****
01 16.67 5.41 -11.3****
02 16.67 7.05 -8.5****
****a < .001 79
Figure 4 displays the waveform for all recording sites and the topographical map illustrating the distribution for the most positive peak between 250-500 ms which occurred at each of the 15 scalp sites. Since both the figure and the tabled data show that the analyses of the data supported the hypothesis, Hypothesis 2 was accepted.
Hypothesis 4: It is expected that in the second semantic task, the categorization condition ERPs will be characterized by a late negative component at Cz and Pz occurring between 300-600 ms followed by a late positive component with maximum peak in the 500-900 ms range at Cz and Pz. Both components will be statistically different compared to an ERP baseline.
Table 4 lists the significant amplitudes in the N400 range where 13 scalp sites were significantly different from baseline. The mean peak amplitudes varied from -3.0 uv at
02 to -11.67 uv at Fz. While mean latencies of the significant amplitudes ranged from 352 ms at both T4 and C4 to 408 ms at 01.
Table 5 shows significant mean positive peaks (P4) which occurred in all 15 scalp sites between 500 and 924 ms poststimulus and ranged from 3.33 uv at F7 to 9.0 uv at Pz.
The mean latencies of these significant peak amplitudes varied from 612 ms at T5 to 826 ms at Fpl. 80
N-400 CHILD 5TUDV
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Figure 4. Event-related potentials by recording site for the congruent ending sentences (----) and a topographic map showing the distribution (in uv) of the largest positive peak amplitudes between 250 and 500 milliseconds (ms) across the scalp. 81
Table 4
Significant Mean Peak Differences (in uv) between the
Categorization of Words and ERP Baseline
Categorization
Site M SD T Value
Fpl -8.0 2.94 10.4****
Fp2 -8.33 3.85 8 .2****
F7 -8.33 2.88 1 1 .2****
F8 -7.33 3.35 8 .1****
Fz -11.67 3.95 11.3****
Cz -11.0 5.80 7.o****
Pz -6.33 7.07 3 .4***
T3 -6.33 2.18 10.9****
T4 -4.33 2.62 g.5****
C3 -9.67 5. 41 5.41****
C4 -9.0 4.86 7.0****
Ol -4.0 4.15 3 .7***
02 -3.0 4.75 2.4*
*p < .05 ***£ < .01 ****£ < .001 82
Table 5
Significant Mean Peak Differences (in uv) between the
Categorization of Words and ERP Baseline
Categorization
Site M SD T Value
Fpl 4.33 3.22 —5.3****
Fp2 4.33 3.59 -4.6****
F7 3.33 3.03 -4.1****
F8 3.67 3.09 -4.6****
Fz 3.67 3.04 -4.6****
CZ 6.0 2.76 -8.5****
Pz 9.0 3.86 -8.9****
T3 5.33 3.86 -5.2****
T4 5. 33 2.68 -7.8****
C3 6.67 2.70 -7.9****
C4 6.0 3.36 _6 .8****
T5 4.0 2.65 -5.9****
T6 5.67 3.43 _ 6 .5****
01 5.0 5.29 -3.5***
02 6.33 4.98 -4. 9****
***E. <.01 ****£ < .001 83
Figure 5 depicts the waveform for all sites across the
ERP for the categorization condition. The two maps on the figure display the cortical surface topography for the most negative amplitudes (within the 250-500 ms range) and the most positive amplitudes (within the 500-924 ms range) across all scalp sites. As can be seen from the two tables and the figure, the analyzed data supported the hypothesis.
Hypothesis 4 was therefore accepted.
Hypothesis 5: It is expected that the reading condition
ERPs will be characterized by a late negative component between 300-600 ms followed by a late positive component between 500-900 ms which are both statistically different from baseline.
Table 6 shows that all 15 scalp sites had significantly greater than baseline mean peak amplitudes for the late negative component (N4) referred to in this hypothesis. The highest mean amplitudes occurred at Cz (-11.67 uv) and Fz (-
11.0 uv) while the lowest mean amplitude was at T5 (-3.33 uv) in the 250 to 500 ms range. The mean latencies for these amplitudes range from 356 ms at F7 to 422 ms at 01.
Table 7 contains the significant mean peak amplitudes for the late positive component (P4) in the 500-924 ms time frame. Mean amplitudes range from 3.0 uv at 01 to 7.33 uv at Pz while mean latencies for these peaks span a time frame 84
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Figure 5. Event-related potentials by recording site for the categorization of words (---- ) and topographic maps showing the distribution (in uv) across the scalp of the largest negative peak amplitudes (top map) between 250 and 500 ms and positive peak amplitudes (bottom map) between 500 and 924 ms. 85
Table 6
Significant Mean Peak Differences (in uv) between the
Reading of Words and ERP Baseline
Reading
Peak Site M SD T Value
N4 Fpl -8.33 4.96 6.3****
Fp2 -8.67 5.59 5.8****
F7 -7.0 3.52 7 .4****
F8 -6.67 3.37 7.6****
Fz -11.0 4.4 g . 4****
CZ -11.67 3.99 10.9****
Pz -9.0 5.57 6 .2****
T3 -7.0 5.04 5.2****
T4 -5.0 3.8 5.2****
C3 -9.67 3.95 9.2****
C4 -8.33 4.18 7 .7****
T5 -3.33 4.54 2.9***
T6 -4.0 4.26 3.5***
01 -6.0 7.57 3.0***
02 -5.33 9.5 2 .1*
*E. < .05 ***p. < .01 ****& < .001 86
Table 7
Significant Mean Peak Differences (In uv) between the
Reading of Words and ERP Baseline
Reading
Peak Site M SD T Value
P4 Fpl 4.67 2.98 - 6 .2****
Fp2 4.33 3.56 -4.7****
F7 4.67 2.81 -6 . 3****
F8 4.33 2.83 - 6 .1****
Fz 5.0 3.99 -4.8****
Cz 6.33 4.36 -5.6****
Pz 7.33 5.02 -5.4****
T3 5.67 4.17 -5.1****
T4 5.33 2.68 —7.8****
C3 6.0 2.89 -7 .9****
C4 5.67 3.45 -6 .2****
T5 3.33 3.16 —3.9****
T6 4.33 3.58 -4.7****
02 4.67 6.48 -2.7**
**& <.02 ****j3 < .001 87
from 644 ms (01) to 840 ms (Fpl).
Figure 6 illustrates the ERPs for the reading condition across all sites. The two brain maps in the figure provide a visual display of the microvolt variation across the scalp for each mean peak amplitude of interest to this hypothesis.
The top map illustrates the most negative peak (N4) between
250-500 ms and the bottom map shows the most positive peak
(P4) between 500-924 ms. Each of the tables and the figure show that the data analyzed supported the hypothesis.
Therefore, Hypothesis 5 was accepted.
Given that the peak amplitudes within selected ranges were statistically different from the EEG baseline across most of the sites of interest (ranging from 12 to all 15 scalp sites), it was assumed that any obtained differences in ERP components between selected conditions would be meaningful.. Consequently, each of the following hypotheses
(3, 6, 7, 8, 9, and 10) tested a given condition against another condition, e.g., congruent vs. anomalous sentence endings.
Comparison of Condition vs Condition ERP's
Hypothesis 3: There will be a statistically significant difference when comparing the amplitude of waveforms produced while reading sentences ending anomalously and the amplitude of waveforms produced in response to sentences 88
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Figure 6 . Event-related potentials by recording site for reading unrelated words (---- ) and topographic maps showing the distribution (in uv) across the scalp of the largest negative peak amplitudes (top map) between 250 and 500 ms and positive peak amplitudes (bottom map) between 500 and 9 2 4 ms. 89
that end congruently at scalp sites Cz and Pz in the
interval from 300-600 ms poststimulus.
This hypothesis was the focus of the present dissertation. Generally, the results were supportive of an
N400 type waveform being found in 10 and 11 year old boys.
This was confirmed by subjecting each participant's maximum negative and positive amplitude, latency of those amplitudes, and averaged amplitude within the 250-500 ms range (VM2) to the Twave program described previously in
Chapter III.
The N400 mean peak amplitude data will be discussed first. For ease of interpretation, Figure 7 shows the waveform produced by the anomalous sentences (solid line) overlaid with the congruent sentences waveform (dashed line) for each recording 3 ite. It appears from the waveforms in the figure that in the 250-500 ms range, the anomalous sentence endings produced more negativity than the congruent sentence endings. Also on the figure are two maps. The top map shows the maximum mean peak negativity in the 250-500 ms range for the congruent endings. The bottom map shows the maximum mean peak negativity for the anomalous endings within the same latency range. These maps coupled with the waveforms suggest that the anomalous ending sentences produce more negativity than the congruent ending sentences especially at sites Fz, Cz, Pz, C3, and C4. This was 90
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Figure 7. Event-related potentials by recording site for the anomalous sentence endings (----) and the congruent sentence endings (- - -). The topographic maps show the distribution (in uv) across the scalp of the N4C0 peak amplitudes (in uv) for congruent endings (top map) and anomalous endings (bottom map). 91 confirmed by subjecting these data to the multiple t test
(Twave) procedure described earlier.
The top third of Table 8 contains the t values, the means, and the standard deviations of those sites that were significantly different across the two sentence conditions for the N4 peak amplitude data. As can be seen from the table, sites Fz, Cz, Pz, T4, C3, and C4 produced significantly greater mean maximum negative amplitudes (N4) in the anomalous condition compared to the congruent condition, in Figure 8, the map on the right is a t map showing the distribution of t values for the comparison between the anomalous and congruent sentence endings N400 peak amplitudes described in Table 8 . This t map is similar to Duffy’s t statistic significance probability map [t statistic SPM (Duffy, Bartels, & Burchfiel, 1981)] and depicts (by virtue of an image) the statistical differences between the two conditions across the surface of the scalp.
Figure 8 shows the largest significant differences to be prominently central as well as located in the right central and right temporal area. These results are similar to those of Kutas & Hillyard (1982) using adult subjects.
In order to aid the reader, these "t" maps will be included with the reporting of all subsequent data relevant to the major hypotheses in this dissertation. However, since these maps are redundant to the tabled data, and the continual reporting of them would break up the continuity of 92
Table 8
Significant Mean Peaks and Latencies for Anomalous and
Congruent Sentence Endings
Anomalous Congruent
Peak Site M SD M SD 1 Value
Peak Amplitude in Microvolts N4 Fz -10.33 6.85 -5.67 3.43 2.09*
Cz -10.0 5.60 -5.33 4.82 2.25*
Pz -6.0 6.35 0.00 5.69 2.69**
T4 -4.33 2.35 -2.33 2.94 2 .20*
C3 -9.33 6.44 -4.0 5.56 2.27*
C4 -7.67 4.55 -2.67 4.32 2.98***
VM2 Cz -2.33 3.92 1.0 4.64 2 .22*
T4 0.00 1.47 2.0 2.57 2.24*
C3 -2.0 4.91 2.0 4.99 2.09*
C4 -0.67 3.16 2.67 4.82 2 .21*
Peak Latency in Milliseconds
N4 FZ 332 17.63 414 31.81 4.01****
Fpl 366 30.26 424 32.90 2.38*
Fp2 368 31.88 430 29.42 2.63**
*p <-05 **p <.02 ***£ <.01 ****£ <.001 93
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Figure 8 . Event-related potentials by recording site for the anomalous sentence endings (----) and the congruent sentence endings (- - -). The topographic map shows the t distribution (in t values x 100) for the comparison of negative peak amplitudes in the 250-500 ms range between the anomalous and the congruent sentence endings. 94 this section, they will be included in Appendix K from this point on.
The second third of Table 8 shows that the mean averaged amplitude (VM2) in the 250-500 ms range was 3.33-
4.0 uv lower in the anomalous compared to the congruent sentence endings at sites Cz, C3, and C4. There was a 2 uv mean difference between the two conditions at site T4 with the anomalous endings having a lower peak amplitude than the congruent endings (see Appendix K, Figure 23 for t map).
Finally, the bottom third of Table 8 , shows that the mean latency of the (N4) negativity was significantly shorter at frontal sites Fpl, Fp2, and Fz in the anomalous as opposed to the congruent condition.
These findings, as presented in Table 8 and Figures 7 and 8, are similar to the results of Kutas and Hillyard
(1982) showing a central and slight right hemispheric preponderance of negativity in the anomalous sentence condition. Therefore, Hypothesis 3 was accepted.
Hypothesis 6 : It is expected that the waveform elicited by the categorization condition will contain a significantly greater mean amplitude (more negative) of the N400 component than will the waveform elicited in the reading condition.
To make this comparison, all of the categorization data were combined to look at the difference between categorizing 95 a list of words and reading a list of unrelated words. As can be seen from Figure 9 the waveforms are very similar.
Although the categorization wave (dashed line) was slightly higher (more positive) at Pz than the reading wave (solid line), there were no significant differences between any mean peaks, latencies, or averaged amplitudes. The maps in the figure, both the top map (reading unrelated words) and the bottom map (categorization of words), show very similar distributions of negative activity. Since the data analyses show no significant differences between the two conditions which is further confirmed by the ERP waveforms and the maps, Hypothesis 6 was rejected. Further, no t maps for this comparison are included in Appendix K.
Hypothesis 7: It is expected that the waveform elicited by the anomalous sentences when compared to that of the category condition will not be statistically different from one another, each showing a late negative component in the
300-600 ms range most prominently peaking at Cz and Pz scalp sites.
Figure 10 shows the averaged waveforms of the anomalous sentence endings (solid line) superimposed on the averaged waveforms for the category condition (dashed line). The waves are very similar up to 500 ms and indeed there were very few significant differences up to that point (listed in 96
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Figure 9. Event-related potentials by recording site for reading unrelated words (---- ) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the N400 peak amplitudes for reading words (top map) and categorizing words (bottom map). 97
0 N-4-00 CHILD STUDV
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Figure 10. Event-related potentials by recording site for anomalous sentence endings (----) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the N400 peak amplitudes for categorizing words (top map) and anomalous endings (bottom map) . 98
Table 9). Hence, no t maps are Included In Appendix K.
However, there were other significant differences beyond the
500 ms range as can be clearly seen from the ERP waveform
portion of the figure. These later differences (500-924 ms)
are discussed under the heading "Other ERP Findings" later
in this section.
The two maps in Figure 10 illustrate the N400 component
for each condition. The categorization of words was shown
in the top map, while the anomalous sentence endings
condition was pictured in the bottom map. The negativity
featured in the two maps was similar. Since the two
conditions were very similar across the N400 range as predicted, Hypothesis 7 was accepted.
Hypothesis 8 : It is expected that the waveform elicited by the category condition will be statistically different from the waveform elicited by the congruent sentence endings in the 300-600 ms time frame, with the waveform from the category condition being characterized by a negative component (N400) and the waveform from the congruent sentence endings condition being characterized by a positive component (P300) each peaking maximally at Cz and Pz.
As can be readily seen in Tables 10, 11, and 12, there were many significant differences within the predicted ranges and, in the predicted direction. (Also see relevant 99
Table 9
Significant Mean Peaks and Latencies for Anomalous Sentence
Endings and the Categorization of Words
Anomalous Categorization Endings
Peak Site M SD M SD T Value
Peak Amplitude in Microvolts P3 T3 6.67 3.61 3.76 2.76 2.46*
T4 5.33 2.55 3.33 2.18 2.30*
Peak Latency in Milliseconds
N4 Fz 332 17.63 376 25.37 2.60**
P3 T5 342 34.55 302 11.25 2.14*
*D <•05 **D <•02 100
Table 10
Significant Mean Peaks and Latencies for the Categorization
of Words and Congruent Sentence Endings
Categorization Congruent Endings
Peak Site M SD M SD T Value
Peak Amplitude in Microvolts N4 Fp2 -8.33 3.85 -5.67 2.46 2.07* ■
F7 -8.33 2.88 -5.33 2.47 3.08***
F8 -7.33 3.35 -4.0 2.82 2.61**
Fz -11.67 3.95 -5.67 3.43 4.20****
Cz -11.0 5.80 -5.33 4.82 2 .66**
Pz -6.33 7.07 0.00 5.69 2.62**
T4 -4.33 2.62 -2.33 2.94 2.09*
C3 -9.67 5. 41 -4.0 5. 56 2.61**
C4 -9.0 4.86 -2.67 4.32 3.60***
*E. < .05 **p. < -02 ***£ < .01 101
Table 11
Significant Mean Peaks and Latencies for the Categorization of Words and Congruent Sentence Endings
Categor ization Congruent Endings
Peak Site M SD M SD T Value
Peak Amplitude in Microvolts P3 F8 1.67 2.13 4.33 4.21 2.33*
Fz 2.33 3.10 6.67 5.52 2.49**
Cz 5.0 3.82 9.67 4.74 2.74**
T3 3.67 2.76 7.0 4.66 2 .21*
T4 3.33 2.18 7.0 3.67 3.29***
C3 4.67 3.41 10.0 5.12 3.18***
C4 4.33 4.28 9.67 5.13 2 .92***
Peak Latency in Milliseconds
P3 T5 302 11.25 368 37.0 3.20***
*p. < .05 **p. < .02 ***2. < .01 102
Table 12
Significant Mean Peaks and Latencies for the Categorization of Words and Congruent Sentence Endings
Categorization Congruent Endings
Peak Site M SD M SD T Value
Peak Amplitude in Microvolts VM2 Fpl -3.0 2.63 -1.0 2.29 2.29*
Fp2 -3.0 3.47 -0.33 2.48 2 .20*
F7 -4.0 2.85 -1.33 1.95 2.87***
F8 -2.67 2.49 0.0 2.72 2 .66**
Fz -6.0 3.44 -0.33 2.86 4.50****
Cz -3.67 4.04 1.0 4.64 2 .95***
Pz 1.33 5.81 7.0 6.28 2.41*
T3 -1.33 1.82 1.0 4.25 2 .21*
T4 -0.67 1.94 2.0 2.57 3.32***
C3 -3.67 3.95 2.0 4.99 3.28***
C4 -2.67 4.1 2.67 4.82 3.28***
01 4.0 4.27 7.67 4.07 2.34*
tp. < .05 **p. < .02 ***p. < .01 ****£ < .001 103
t maps in Appendix K, Figures 24, 25, & 26). In the case
of the N400 amplitude (Table 10), there were ninesites that
were significantly different from one another in the two
conditions. The largest mean amplitude differences were at
central sites Fz, Cz, and Pz (6 uv, 5.67 uv, and 6.33 uv
respectively) with the most negativity occurring during the
categorization of words.
The P300 amplitude showed statistical differences at
seven scalp locations (Table 11). Mean amplitude differences ranged from 2.66uv at site F8 to 5.34 uv at
site C4. Again, the largest differences were centrally
located (Cz, C3, and C4) with the congruent sentence endings
having a higher amplitude (more positive) than the categorization of words.
The averaged amplitude across a range [in the present case, the mean across 250-500 ms, (VM2)J had the largest number of significant differences, with 12 scalp sites exhibiting a statistical difference between the two conditions (Table 12). The average mean amplitude was always higher (more positive) for congruent sentence endings than for categorization of words. The largest peak differences were at Fz, Pz, C3, (all 5.67 uv) and C4 (at
5.34 uv).
Figure 11 illustrates the two waveforms. The category wave is lower in amplitude than the congruent sentence wave across the 250-500 ms range with the category wave showing a 104
0 N-4-00 CHILD STUDS'
10UV
12UV
Figure 11. Event-related potentials by recording site for congruent sentence endings (----) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the N400 peak amplitudes for categorizing words (top map) and congruent endings (bottom map) . 105
significantly more negative component to the congruent
sentence endings' more positive component. The two maps depicted in Figure 11 show the distributional difference in microvolts for the most negative peaks across all scalp sites for the two conditions. The top map depicted the categorization of words and showed more negativity than the bottom map which illustrated congruent sentence endings.
Figure 12 showed the same waveforms as Figure 11 but exhibited different maps. The maps in Figure 12 showed the distribution of the most positive peaks across all scalp sites in the 250-500 ms range for both conditions.
Congruent sentence endings (bottom map) was more positive across the scalp than was the categorization of words (top map) .
Figure 13 illustrates the same waveforms as the previous two figures but the maps show the distribution of the averaged mean amplitude for the 250-500 ms range across all scalp sites. As can be seen from the maps, the categorization of words (top map) showed negativity while the congruent sentence endings (bottom map) showed positivity for the average amplitude over the same range.
The analyses of the data as shown in the tables and figures support Hypothesis 8 . Therefore, the hypothesis was accepted. 106
N-400 CHILD STUDS'
a a a I l f M
1I3UV
i Figure 12. Event-related potentials by recording site for congruent sentence endings (----) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the largest positive peak amplitudes between 250 and 500 ms for categorizing words (top map) and congruent endings (bottom map). 107 0 N-400 CHILD STUDV lfllJV 10UV Figure 13. Event-related potentials by recording site for congruent sentence endings (----) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the mean averaged amplitude within the 250-500 ms range for categorizing words (top map) and congruent endings (bottom map). 108 Hypothesis 9 : It is expected that the reading condition and the congruent sentences condition will not be statistically different in mean amplitude from one another in the 300-600 ms range. Contrary to prediction, these two conditions were statistically very different from one another. The possible explanations for these differences are addressed in the discussion section. As can be seen from Table 13, 14, and 15, and Figures 14, 15, and 16 (as well a relevant t maps in Appendix K, Figures 27, 28, & 29), there were a substantial number of peak amplitude differences in the N400, P300, and the averaged mean peak across the 250-500 ms range (VM2) as well as a small number of statistically different latencies. The N400 component (Table 13) exhibited statistically different peak amplitudes over eight scalp sites. The mean amplitude difference was largest at Pz (9.0 uv) followed by other central sites Cz (6.34 uv), C3 (5.67 uv), C4 (5.66 uv) and Fz (5.33 uv). There was a significant mean latency difference at scalp site Fz with the reading unrelated words condition showing an earlier peak than congruent sentence endings. Figure 14 shows the ERP's for both conditions, congruent sentences (solid line) and reading unrelated words (dashed line), across all sites. The waveforms show the 109 Table 13 Significant Mean Peaks and Latencies for the Reading of Words and Congruent Sentence Endings Reading Congruent Words Endings Peak Site M SD M SD T Value Peak Amplitude in Microvolts N4 F8 -6.67 3.37 -4.0 2.28 2.24* FZ -11.0 4.40 -5.67 3.43 3.35*** Cz -11.67 3.99 -5.33 4.82 3.62*** Pz -9.0 5.57 0.0 5.69 4.31**** T4 -5.0 3.80 -2.33 2.94 2.26* C3 -9.67 3.95 -4.0 5.56 3.01*** C4 -8.33 4.18 -2.67 4.32 3.61*** 01 -6.0 7.57 -0.67 4.82 2.18* Peak Latency in Milliseconds N4 Fz 360 19.77 414 31.81 2.62** *p. < .05 **2. < .02 ***£} < .01 ****£ < .001 110 Table 14 Significant Mean Peaks and Latencies for the Reading of Words and Congruent Sentence Endings Reading Congruent Words Endings Peak Site M SD M SD T - Value Peak Amplitude in Microvolts P3 Fz 2.0 5.12 6.67 5.52 2.18* Cz 3.67 4.86 9.67 4.74 3.15*** Pz 9.33 6.19 16.0 7.34 2.45* T4 3.33 3.59 7.0 3.67 2.62** C3 6.0 4.45 10.0 5.12 2 .20* C4 4.33 5.68 9 .67 5.13 2.64** Peak Latency in Milliseconds P3 Fz 258 10.64 324 50.96 -2.38* T5 316 23.31 368 37.0 -2.13* 01 276 14.02 300 13.86 -2.29* *2. < .05 **2 < .02 ***£ < .01 Ill Table 15 Significant Mean Peaks and Latencies for the Reading of Words and Congruent Sentence Endings Reading Congruent Words Endings Peak Site M SD M SD T Value Peak Amplitude in Microvolts VM2 Fpl -3.33 2.99 -1.0 2.29 2.37* Fp2 -3.67 3.71 -0.33 2.48 2.53** F8 -2.33 3.15 0.0 2.72 2.07* Fz -5.33 3.38 -0.33 2.86 4.19**** Cz -4.33 3.21 1.0 4.64 3.63*** Pz 0.0 4.12 7.0 6.28 3.58*** T4 -1.0 2.94 2.0 2.57 2.89*** C3 -2.67 3.07 2.0 4.99 3.07*** C4 -2.67 4.15 2.67 4.82 3.15*** 01 3.0 6.18 7.67 4.07 2.38* *E. < •05 **p. < .02 ***j3 < .01 ****£ < .001 112 *£) N-4-00 CHILD STUDV liauv 10IJV 12UV Figure 14. Event-related potentials by recording site for congruent sentence endings (----) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the N400 peak amplitudes for reading words (top map) and congruent endings (bottom map). 113 N-4-00 CHILD STUDS' f•M V r a m m d i£uw 10IJV »)>&}&& 10UV Figure 15. Event-related potentials by recording site for congruent sentence endings (----) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the largest positive peak amplitudes between 250 and 500 ms for reading words (top map) and congruent endings (bottom map). 114 0 N-400 CHILD STUDS' ij'jy ^ •: i ,;|SSSi | 1I3UV skSwmH fet«! lflUV Figure 16. Event-related potentials by recording site for congruent sentence endings (----) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the mean averaged amplitude within the 250-500 ms range for reading words (top map) and congruent endings (bottom map). 115 greatest difference in the 250-500 ms range with reading unrelated words displaying much more negativity than congruent sentences at central scalp sites (Fz, Cz, Pz, C3, C4). The two maps depict the topographic distribution of the most negative peaks in the 250-500 ms range across the scalp sites for both conditions. Reading unrelated words (top map) showed more negativity across the scalp than the congruent sentence endings (bottom map). The P300 component (Table 14) displayed differences between the conditions, again, primarily at central scalp sites (Fz, Cz, Pz, C3, and C4). The significant mean peak differences ranged from 6.67 uv at Pz to 3.67 uv at T4. P300 mean latencies were significantly earlier in the reading condition than in the congruent sentence endings condition for three scalp sites (Fz, T5, and 01). Figure 15 shows the same ERP waveforms discussed above but the maps show the distribution of the most positive peaks in the 250-500 ms range across all scalp sites in both conditions with congruent sentence endings (bottom map) displaying a more positive distribution than reading unrelated words (top map). The mean averaged peak amplitude over the 250-500 ms range (VM2) (Table 15) showed significant differences at 10 scalp sites. The largest mean amplitude difference occurred at Pz (7.0 uv), followed by C4 (5.34 uv), Cz (5.33 uv), and Fz (5.0 uv). The waveforms in Figure 16 are the same as 116 those discussed above but the two maps clearly show the distribution of the averaged mean amplitude differences across all sites in the 250-500 ms range between the two conditions, particularly at sites Fz, Cz, and Pz which were more negative for reading (top map) than for congruent sentence endings (bottom map). The data analyses showed many statistical differences between the two conditions in the 250-500 ms range when none were predicted. Therefore, Hypothesis 9 was rejected. Hypothesis 10: It is expected that the waveform of the reading condition will be statistically different when compared to the waveform produced by the anomalous ending sentences condition in the 300-600 ms range. In the range considered for this hypothesis, only two findings were significant, a P300 mean latency at site F8 and an averaged mean peak at site Pz. The specifics of both can be seen in Table 16. Hence, no t map is included in Appendix K. Figure 17 shows the ERP waveforms for the anomalous sentence endings (solid line) overlaid by the waveforms for the reading of unrelated words (dashed line). The two maps show the distribution of the averaged mean amplitude across a range (250-500 ms) for both conditions over all scalp sites. 117 Table 16 Significant Mean Peaks and Latencies for Anomalous Sentence Endings and the Reading of Words Anomalous Reading End 1 ngs Words Peak Site M SD M SD T Value Peak Amplitude in Microvolts VM2 Pz 3.67 4.75 0.0 4.12 2 .21* Peak Latency in Milliseconds P3 F8 340 56.35 272 21.94 2 .12* *p. <.05 118 0 N-4-00 CHILD STUDV gfrgSEW mmpt 1£UV IfllJV mmm »m*>3 10UV Figure 17. Event-related potentials by recording site for anomalous sentence endings (----) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the mean averaged amplitude within the 250-500 ms range for reading words (top map) and anomalous endings (bottom map). 119 Since the analyzed data did not support the hypothesis for the range predicted (250-500 ms), Hypothesis 10 was rejected. There were many additional significant findings beyond the 500 ms range which were observable in the ERP waveforms shown in Figure 17 and were discussed in "Other ERP Findings". Other ERP Findings Two of the previously discussed hypotheses (7 and 10), had relatively few significant findings in the ERP waveform from a latency of 250-500 ms poststimulus and in fact, Hypothesis 7 predicted no significant differences in the mid-range of the waveform. However, across the remainder of the averaged wave (500-924 ms poststimulus) there were several areas showing significant differences that were looked at post hoc. Hypothesis 7. As can be seen from Table 17, Hypothesis 7 which compared anomalous sentence endings and the categorization of words showed a number of significant differences in the 500-924 ms (poststimulus) range. The N5, which was an arbitrary designation for the most negative peak amplitude in the 500-924 ms range, had three sites which were significant (Fz, T3, T4). All three sites were significantly lower for the categorization of words than for the anomalous sentence endings. These three sites were also significant in three other peak amplitudes [P4, Vector Mean 3 (500-800 ms) and Vector Mean 4 (800-924 ms)]. For every 120 Table 17 Significant Mean Peaks and Latencies for Anomalous Sentence Endings and the Categorization of Words Anomalous Categorization Endings Peak Site M SD M SD T Value Peak Amplitude in Microvolts N5 FZ -3.0 4.58 -7.33 4.14 2.62** T3 0.67 3.77 -2.0 2.48 2.53** T4 -0.33 2.06 -2.0 2.15 2.18* P4 F7 6.67 3.52 3.33 3.03 2 .66** Fz 8.0 4.28 3.67 3.04 3.03*** Cz 10.33 4.82 6.0 2.76 2.77** T3 10.33 3.69 5.33 3.86 3 .43*** T4 7.67 3.02 5.33 2.68 2.07* C3 10.0 4.08 5.67 2.70 3.45*** C4 9.33 3.25 6.0 3.36 2.58** T5 7.67 4.89 4.0 2.65 2.40* *E. <.05 **a <.02 < .01 121 amplitude, all sites were again significantly lower (more negative) for categorization of words as compared to anomalous ending sentences. The P4 (also in Table 17 with t map in Appendix K, Figure 30), which was an arbitrary designation for the most positive peak amplitude in the 500-924 ms range, showed eight significant sites. Mean differences in amplitude between conditions ranged from 5.0 uv at T3 to 2.34 uv at T4 with all mean peaks having greater positive amplitude in the anomalous sentence endings condition compared to the categorization of words. Figure 18 showed the ERP waveforms by scalp site. The amplitude differences between the two conditions were clearly visible particularly at sites Fz, Cz, T3, and C3. The two maps in the figure visually display the distribution of the most positive peaks for both conditions in the 500-924 ms range. Table 18 shows the significant differences between conditions for vector means 3 (VM3) (see relevant t map in Appendix K, Figure 31) and 4 (VM4) , which were each an average peak amplitude within a range for every site. As can be seen from the table, VMS had significant differences at seven scalp sites while VM4 showed significance at six sites. Anomalous sentence endings always had a higher mean amplitude than the categorization of words across all findings (N5, P4, VM3, and VM4). Figure 19 again shows the ERP waveforms for both conditions across all scalp sites. 122 ^ N-4-00 CHILD STIJDV 10UV Figure 18. Event-related potentials by recording site for anomalous sentence endings (----) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the largest positive peak amplitudes between 500 and 924 ms for categorizing words (top map) and anomalous endings (bottom map). 123 Table 18 Significant Mean Peaks and Latencies for Anomalous Sentence Endings and the Categorization of Words Anomalous Categorization Endings Peak Site M SD M SD T Value Peak Amplitude in Microvolts VM3 F7 0.67 2.92 -1.0 2.09 2.07* FZ 2.33 3.47 -2.0 3.20 3.71** T3 5.0 2.74 1.33 2.10 3.97*** T4 3.67 2.25 1.67 2.10 2.40* C3 4.33 3.53 0.67 3.55 2.63** C4 4.0 2.86 1.0 3.28 2.34* T5 2.33 3.88 0.0 2.33 2.18* VM4 F7 4.0 3.46 1.33 2.46 2.52** Fz 4.0 3.81 1.0 2.69 2.30* Cz 5.33 4.90 2.0 2.42 2.33* T3 6.0 2.81 1.0 2.95 4.37**** C3 5.67 4.51 1.33 3.18 2.87*** C4 4.67 3.46 2.0 2.79 2.14* *p < •05 **p. <.02 ***p. < .01 * * * * j j < . |001 124 N-4-00 CHILD STUDV [Ui i s t'ii s: r ;.;i « £si»i I 1£UV p M e m n liSUV Mk^;: ^i2®^®Srassc8s*fflr lifeiaiBI 'iB !U V p ii‘ 3uv illl r'vv<< mimmmmmmk ►'*!*>+;*■, iauv Figure 19. Event-related potentials by recording site for anomalous sentence endings (----) and categorization of words (- - -). The topographic maps show the distribution (in uv) across the scalp of the mean averaged amplitude within the 500-800 ms range for categorizing words (top map) and anomalous endings (bottom map). 125 The top map displays the distribution of the mean averaged peak within a range (VM3) for the categorization of words condition while the bottom map illustrates the distribution for anomalous sentence endings. Hypothesis 10. Although differences were predicted within the mid-range of the ERP waveform for this hypothesis, only two findings were significant (see Hypothesis 10 above). In the latter portion of the ERP waveform however, there were a number of significant differences between the two conditions (Anomalous Sentence Endings and Reading Unrelated Words). Table 19 lists the mean peak amplitudes and latencies by scalp site that were significantly different between the two conditions for the N5 or largest negative peak between 500 and 924 ms poststimulus (see relevent t map, Appendix K, Figure 32). Six scalp locations showed a difference in mean peak amplitude with the reading of words having more negativity than anomalous sentence endings across all sites. The latency of the N5 peak was significantly earlier for the reading condition than for the anomalous endings at sites Fz and Pz but significantly later at site T3. Figure 20 shows the ERP waveforms for reading unrelated words (dashed line) and anomalous sentence endings (solid line) across all scalp sites. The reading condition showed more negativity across the waveform than the anomalous sentence endings condition. The two maps show the 126 Table 19 Significant Mean Peaks and Latencies for Anomalous Sentence Endings and the Reading of Words Anomalous Reading Endings Words Peak Site M SD M SD T Value Peak Amplitude in Microvolts N5 Fz -3.0 4.58 -7.33 3.33 2.81*** Cz -2.0 2.93 -5.0 3.83 2. 34* T3 0.67 3.77 -2.67 2.57 3.12*** C3 -1.0 4.78 -5.0 3.44 2.45* C4 -0.67 2.43 -4.0 4.01 2.45* T5 -3.33 4.39 -7.33 5.41 2 .10* Peak Latency in Milliseconds N5 Fz 614 68.97 534 18.10 2.09* Pz 816 63.67 632 76.35 3.38*** T3 614 72.11 738 65.63 2.32* *p <.05 **£ < .02 ***£ < .01 127 N-4-00 CHILD STUDY liauv iuv M S Iffis IUV MvMIT nauv Figure 20. Event-related potentials by recording site for anomalous sentence endings (----) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the largest negative peak amplitude between 500 and 924 ms for reading words (top map) and anomalous endings (bottom map). 128 topographic distribution of the N5 peaks over all scalp sites for each condition, reading (top map) and anomalous endings (bottom map) with reading showing a more negative distribution than anomalous sentence endings. Table 20 lists the scalp sites which showed significant differences between the most positive mean peak amplitudes (P4) of the anomalous ending sentences and those of reading unrelated words in the 500-924 ms range (see relevent t map, Appendix K, Figure 33). The differences ranged from 2.34 uv at T4 to 4.66 uv at T3 over seven sites with anomalous sentence endings having the more positive (thus higher) peak amplitudes than reading unrelated words. Figure 21 again, shows the ERP waveforms for the two conditions as mentioned for Figure 20. The two maps illustrate the scalp distribution of the P4 amplitude over all sites in both conditions with the top map (reading words) showing less positivity than the bottom map (anomalous sentence endings). The average peak amplitudes within a range [VM3 (500- 800 ms) and VM4 (800-924 ms)] for which there were statistically significant differences between the anomalous sentence endings and reading of words were listed in Table 21 (see also t map, Appendix K, Figure 34). There were eight significant scalp sites for VM3 and five for VM4 with anomalous sentence endings having a higher average peak amplitude than reading unrelated words across all 129 Table 20 Significant Mean Peaks and Latencies for Anomalous Sentence Endings and the Reading of Words Anomalous Reading Endings Words Peak Site M SD M SD T Value Peak Amplitude in Microvolts P4 Cz 10.33 4.82 6.33 4.36 2.18* Pz 11.67 3.52 7.33 5.02 2.73** T3 10.33 3.69 5.67 4.17 3.05*** T4 7.67 3.02 5.33 2.68 2.09* C3 10.0 4.08 6.0 2.89 3.07*** C4 9.33 3.25 5.67 3.45 2.82*** T5 7.67 4.89 3.33 3.16 2.85*** *D <.05 **D < .02 ***D < .01 130 0 N-4-00 CHILD STUDV ,UEb liauv Figure 21. Event-related potentials by recording site for anomalous sentence endings (----) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the largest positive peak amplitude between 500 and 924 ms for reading words (top map) and anomalous endings (bottom map). 131 Table 21 Significant Mean Peaks and Latencies for Anomalous Sentence Endings and the Reading of Words Anomalous Reading Endings Words Peak Site M SD M SD T Value Peak Amplitude in Microvolts VM3 Fz 2.33 3.47 -2.0 2.95 3.68*** Cz 3.67 3.52 0.0 3.42 2 .66** Pz 5.33 2.95 1.0 5.07 2.64** T3 5.0 2.74 1.33 2.64 3 .68*** T4 3.67 2.25 1.33 2.13 2.75** C3 4.33 3.53 0.0 2.70 3.47*** C4 4.0 2.86 0.33 3.21 3.02*** T5 2.33 3.88 -2.0 3.85 3 .15*** VM4 Cz 5.33 4.91 1.33 3.07 2.55** T3 6.0 2.81 1.0 2.34 4.99**** T4 3.0 2.61 1.0 1.98 2.15* C3 5.67 4.51 1.67 2.75 2.72** C4 4.67 3.46 1.33 3.06 2.60** *2. <.05 **£ < .02 ***2 < -01 ****£ < .001 132 significant sites. Figure 22 showed the ERP waveform for anomalous ending sentences and the reading of unrelated words across all sites. The two maps display the distribution over the scalp of the average mean peak in the 500-800 ms range (VM3) for the reading condition (top map) and the anomalous sentence condition (bottom map). The reading condition map shows a more negative distribution compared to the anomalous endings condition map which has a higher (positive) distribution. In conclusion, Chapter IV presented the results of the behavioral written measures indicating that the subjects attended to the semantic tasks and perceived the tasks appropriately: i.e., either sentences "made sense" or "did not make sense", sentences were recognized as having been "seen" or "not seen" previously and, words were recalled and placed into categories. Results of the four ERP to baseline comparisons indicated, that for the areas of interest (250- 500 ms and 500-900 ms), there were a large number of significant t ’s. Therefore, Hypotheses 1, 2, 4, and 5 were accepted. For the planned comparisons which looked at condition against condition, Hypotheses 3, 7, and 8 were accepted while Hypotheses 6 , 9, and 10 were rejected. In the final section of this chapter, robust post-hoc findings that were not part of the planned comparisons were reported. In Chapter V, a discussion of the findings of this dissertation will be presented along with how this research 133 N-400 CHILD STUDV g l p j W w l 1 2 JV n r i0,jv Figure 22. Event-related potentials by recording site for anomalous sentence endings (----) and reading unrelated words (- - -). The topographic maps show the distribution (in uv) across the scalp of the mean averaged amplitude within the 500-800 ms range for reading words (top map) and anomalous endings (bottom map). 134 can lead to future ERP language related work with children. Chapter V DISCUSSION AND IMPLICATIONS Introduction In this chapter the results of the experiment and implications for future research in psychology and education are discussed. The chapter is organized into five major sections. In the.first section, entitled Baseline Hypotheses. the data comparing subjects’ EEG baseline against each of the four experimental conditions, i.e., anomalous sentences, congruent sentences, word categorization, and word reading, is discussed. The second section, Anomalous and Congruent Sentence Data, describes the data which is the focus of this dissertation, namely the replication of the N400 phenomenon in young boys. The third section Word Categorization and Word Reading Data, presents the word reading and categorization data and compares it with the anomalous ending data. This comparison is used to argue that the amplitude of the N400 may be inversely related to the amount of semantic context subjects are given and implications for future research are suggested for testing this argument. The fourth section. Other Findings, discusses post hoc results related to previously presented arguments concerning the N400. The final section, 135 136 Implications for Additional Future Research, suggests possibilities for additional future studies in education and psychology which utilize the N400 as a semantic processing variable. Baseline Hypotheses As mentioned in Chapter I, subjects1 ERP baseline was compared to each of the experimental conditions in order to determine if the ERP generated by each of these conditions was significantly different from the subjects' prestimulus baseline for that condition. In review, Hypothesis 1 compared subjects' average prestimulus amplitude with each poststimulus amplitude data point for anomalous sentence endings. Hypothesis 2 compared the congruent sentence endings ERP with its baseline. Similar comparisons were made for word categorization (Hypothesis 4) and word reading (Hypothesis 5). If the ERPs were not different from their respective baselines, then it would have suggested that any obtained ERP was not related to the cognitive processing needed to perform the task. Not surprisingly, the results showed that for each experimental condition nearly all scalp recording sites (12 to 15 sites) differed from their prestimulus baseline across the data points of interest for this dissertation (250 - 900 ms). Thus, these data (coupled with the written behavioral data reported earlier) strongly suggest that the ERP's generated during the performance of each of the experimental tasks were related to the cognitive 137 processing relevant to those tasks. Consequently, Hypotheses 1, 2, 4, and 5 were accepted. Because acceptance of these hypotheses allows further discussion of the results, it is not necessary to discuss these data further. Anomalous and Congruent Sentence Data A concern of the present dissertation was whether the N400 that is typically produced when adult subjects read a sentence having an anomalous ending (Kutas, & Hillard, 1982) could be replicated using younger subjects (Hypothesis 3). Generally, the results showed that an N400 component was generated by 10 and 11 year old boys. The N400 for the anomalous ending sentences was centrally located (Fz, Cz, and Pz) and occurred in more right hemispheric sites (C4 and T4) than left hemispheric sites (C3) when compared to the congruent sentence endings. The maximal difference between the two conditions occurred at Pz (-6.0 uv) . These results followed a pattern similar to that found with adult subjects in the Kutas and Hillyard (1982) research. That is, a central site (Cz) produced the greatest amplitude difference between conditions relative to the other sites used. (Note, that Kutas and Hillyard (1982) did not record from Pz). Further, the present data, like previous adult data (Kutas & Hillyard, 1982, 1983), showed a slight right-hemispheric preponderance of negativity. The only minor difference found between the present study and previous work using adults (Kutas & Hillyard, 138 1982) is that In the present case the maximal difference in N400 amplitude between the anomalous and congruent endings occurred slightly later for the boys (maximal at 394 ms) than the N400 typically reported for adults (maximal at 380 ms). This finding is in keeping with past ERP research which suggests that children's ERP components tend to have longer latencies than adults (Courchesne, 1978; Kok & Rooijakkers, 1985). This latency difference could be due to maturational factors between the brains of 10 to 11 year old boys and adults, since studies that have compared children to adults directly (e.g., Courchesne, 1977, 1978) have found that ERP latency seems to decrease with age. Taken as a whole the present results suggest that a robust N400 component did occur in 10 and 11 year old boys replicating (with children) the findings of Kutas and Hillyard (1982) using adults. Therefore Hypothesis 3 was accepted. Word Categorization and Word Reading Data Hypotheses 6-10 were predicated on earlier research which suggested that the N400 is caused by a complex cognitive evaluation of similar and dissimilar stimuli (e.g., Dunn et al., 1987; Polich, 1985; Polich, Vanasse, & Donchin, 1981). Thus, based on this research, it was assumed that categorizing a list of words requires a more extensive evaluation (thereby producing a greater N400 amplitude) than merely reading a list of unrelated words 139 (Hypothesis 6 ). That is, during categorization the subject would have to decide if the word flashed on the screen was similar to category 1 items (e.g., body parts) or category 2 items (e.g., transportation), whereas the mere reading of unrelated words would not require a comparison of each word on any apparent dimension of similarity. It was also assumed that both word categorization and reacting to an anomalous sentence ending would require similar amounts of evaluation and therefore would produce similar N400 amplitudes (Hypothesis 7). Since it was previously predicted that a negative (N400) component would be produced to an anomalous sentence ending versus a positive component for a congruent sentence ending (Hypothesis 3) and that both word categorization and processing anomalies requires «:he evaluation of similar and dissimilar stimuli (Hypothesis 7), it was argued that word categorization would produce an N400 component while reading congruent sentence endings would be characterized by a positive (P300) component (Hypothesis 8 ). Finally, it was assumed that reading unrelated words, like reading congruous sentence endings, would not require differentiation between semantic similarities and dissimilarities. Consequently, it was predicted that the amplitude of the ERP component produced during word reading, as well as the more positive component produced during processing congruent sentence endings, would not differ from 140 one another In the 300-600 ms range (Hypothesis 9). In contrast, word reading should differ from processing anomalous sentences because of the more extensive processing required by the latter task (Hypothesis 10). The results, however, showed that word reading, categorization and processing anomalies produced similar, large N400 amplitudes across the critical Fz, Cz, Pz, C4, and T4 sites. The only significant amplitude difference that occurred favored the reading condition where a more negative averaged amplitude (VM2) (in the 250-500 ms range) was produced relative to the anomalous sentence condition. Therefore, Hypotheses 6, 9, and 10 had to be rejected. The results did show that processing anomalous sentence endings did not differ significantly in N400 amplitude from categorizing words, thus confirming Hypothesis 7. Also, there was a significant difference in averaged amplitude (VM2) in the critical 250-500 ms range between categorizing words and processing congruent sentences, with the congruent sentence endings producing relatively greater positivity at the predicted (Cz, Pz) sites. These results allowed the acceptance of Hypothesis 8 . It is important to note that the latency data in the N400 range only indicated scattered differences across the experimental conditions, i.e., no patterns or regularities were found. Therefore these data will not be discussed further. 141 At first glance the data, showing that simple word- reading produced as large an N400 amplitude as the anomalous sentences and the categorization task, is highly puzzling given that it was predicted to be the least cognitively demanding of all the experimental tasks based on recent studies (Dunn et al., 1987; B. Dunn et al., 1988). That is, all the present subjects had to do is merely read the words as they were flashed on the screen. The subjects were explicitly instructed to read the words and were told they would not be asked to recall any words in the list. Further, this task was never given prior to the word categorization task, therefore it is doubtful that the boys had any expectation other than that they were merely to read the words. Assuming that the word reading task (and perhaps the processing of congruent sentence endings) was the least cognitively demanding, and did not require the complex evaluation of similar and dissimilar stimuli (Polich, 1985) one has to ask the question of why does the seemingly innocuous task of reading unrelated words produce such a large N400 amplitude? As mentioned in Chapter II, the common thread that prevails in the most recent literature is that a lack of semantic context may be directly related to the occurrence and amplitude of the N400. This lack of context, may in fact be the variable that modulates the amplitude of the N400 and contributes to the N400 becoming a P300 when the 142 semantic context is readily apparent. Specifically, it was argued that the amplitude of the N400 component may be inversely related to the amount of semantic context a subject is given. That is, if little context is presented (and the subject has to provide his own meaning) a large N400 is produced. On the other hand, if greater context is given a smaller N400 or a positive component is produced (Kutas et al., 1988; Neville et al., 1986; Van Petten & Kutas, 1987). This notion appears to have some validity, as Kutas et al. (1988) have pointed out that, a significantly larger N400 is produced when the subject reads the first content word (subject, verb etc.) in the sentence as compared to a later content word. The point is, that when the first content word is presented, the subject has been provided with little semantic context [e.g., The barber.. (first content word)] as opposed to a later content word having more semantic context [e.g., The barber is cutting my brother1s .. (later content word)]. Thus, it appears that semantic context is inversely related to the production of the N400 component. The "inverse semantic context" argument describes the present data reasonably well. Little semantic context was presented to the boys when they were asked to merely read unrelated words as they were presented on the screen. As noted earlier, this condition produced as large an N400 amplitude as the categorization task and the anomalous 143 sentence ending condition. A possible problem with this argument is that it has to be assumed the boys semantically processed the words at a fairly complex level (Craik & Lockhart, 1972), even though they were told that they would not have to remember the words for recall. This assumption may not be too far fetched as there is a wealth of early verbal learning literature showing that subjects attempt to create their own cognitive structure [sometimes called subjective organization (Tulving, 1962)] when presented with randomly chosen words for later recall (McConkie & Dunn, 1971; Mandler, 1967; Mandler & Pearlstone, 1966; Tulving 1962, 1967; Tulving & Osier, 1967; Tulving & Pearlstone, 1966). These studies all suggest that subjects create cognitive organization when no organization is apparent in the material to be learned. Although these studies support the arguments made in Chapter II (and immediately below) concerning the word categorization condition used in this dissertation, they are not directly comparable to the word reading condition because in all studies (cited above) the subjects were informed that they would be given a free-recall task. A study more related to the word reading task was conducted by Hyde and Jenkins (1969) who used an incidental (not informed) as well as an intentional (informed) recall task. It is important to note that incidental learning instructions are similar to the word reading instructions in 144 that the subjects were not asked to actively organize the words. Specifically, Hyde and Jenkins (1969) presented subjects with lists of words and various orienting tasks to perform on each word. One of the groups of subjects had to make a pleasantness rating, another had to check for the presence of the letter E, and the third group had to count the number of letters in each word. Half of the subjects were told that they would be asked to recall the words later (intentional learning). The other half were not told that there would be a subsequent recall task (incidental learning). The results showed that those subjects given the standard intentional learning instructions and those incidental learning subjects who were charged with making pleasantness ratings produced the greatest levels of recall. The authors argued that when the incidental learning subjects were making their pleasantness ratings they were processing (organizing) the words semantically and it was this semantic processing that lead to the high levels of recall. Taken together, the results from the verbal learning literature strongly suggest that subjects impose a semantic context on material even when they are not asked to do so. Thus, it could be argued that when the boys in the present study read the words, they created their own subjective organization thereby providing their own "context". 145 It also could be argued that the anomalous sentence condition provided subjects with a limited "semantic context". That is, during sentence presentation the subject was given a specific semantic context (The boy hit the ball with a ...). When the anomaly (e.g., sock) was presented, the original context was no longer valid and the subject was forced to provide his own context or. as a minimum, reevaluate the semantic context of that sentence. Finally, it could be argued that subjects had to provide their own context, in part, when they performed the word categorization task. As words were flashed on the screen, subjects had to discover the two categories built into the list and then had to decide which category (or context) each word belonged to. That is, after discovering the general semantic context (the category names) they had to provide the context for any given word. The view that context affects N400 amplitude may be related to recent work by Kutas et al. (1988) which suggests that the N400 component varies as a function of the amount of semantic priming a subject is given. Basically, Kutas argues that if a subject is given a strong semantic context (e.g., a congruent sentence with an unexpected ending), a small N400 is generated. However, if there has been little semantic priming [e.g., the first content word in a sentence) or a violation of a preceding context (e.g., an anomalous ending to a sentence, or an incongruent word 146 presented after a phrase), a relatively large N400 component is produced. It is the opinion of the present author that lack of, or violation of semantic context is similar to the notion of semantic priming. The present use of the term "lack of semantic context", may be a more preferable term to "semantic priming" (Kutas et al, 1988) because it handles any condition where the subject has to provide his own semantic context including cases where the context is never given directly by the experimenter (word reading), is internally generated by the subjects (making up a story from a series of words) or is caused by a violation of an experimentally induced semantic context (anomalous sentence ending). There is one possible caveat to the above explanations of variations in N400 amplitude, however. Kutas (personal communication) pointed out that it could be argued that the word reading and categorization ERP data are not directly comparable to the anomalous and congruent sentence ERPs because they come from different tasks. In other words it is like comparing "apples and oranges". A preferable way (according to Kutas) is to study semantic priming or context using the same type experimental paradigm. For example, to study the N400 components to the various words in the sentence, with the assumption that words presented early in the sentence have less context than words presented later in the sentence. Obviously, such a variation may provide 147 better experimental control and would be the best way to study Kuta's notion of semantic priming. The problem of limiting study within a particular experimental paradigm and not studying the N400 phenomenon across various semantic tasks (as was done here) limits the generalizability of the results and the importance of the N400 phenomenon. Perhaps, given her notion of semantic priming such control is necessary, but if the N400 phenomenon is to have use in educational research, it will have to be shown to occur in other semantic tasks as in the present dissertation. In a recent address, Kutas (1988) argued that N400 type components do occur in other tasks, but that these "N400s" may not be the same as the ones generated in a semantic incongruity paradigm. She argued in a recent review of the literature (Kutas et al., 1988) that these "other” N400 like components have a different waveform morphology and distribution across the cortical surface of the brain than does the N400 component which presents itself in silent reading (semantic incongruity) paradigms. The present data were reexamined in this light. The distributions of each of the conditions that produced an N400 component (anomalous sentence endings, word reading and word categorization) were compared by examining those conditions when they were based on a common reference. The data chosen for the examination were those statistical comparisons of each of the conditions with the congruent sentence data, the latter of which served 148 as the common reference or baseline. Examination of the N400 data in Tables 8 , 10, and 13 shows that in all cases the critical central Fz, Cz, and Pz sites as well as the right hemispheric sites C4 and T4 were significantly more negative than the congruent sentences at those sites. Since these sites were so consistently negative across conditions and are the scalp areas that typically show the N400 in adults (e.g., Kutas & Hillyard, 1982, 1983, 1984; Kutas et al., 1988), it is difficult to believe that the N400 components produced by the categorization and word reading conditions were substantially different from the "real" N400 found with the anomalous sentence endings. This of course supports the notion of "semantic context" developed earlier and suggests that the N400 can be studied across differing semantic tasks as in the present study. The above discussion concerning the context issue highlights the need for studies which vary semantic context more systematically than in the present dissertation. Only in this manner, can the hypothesized notion of the inverse relationship between semantic context and N400 amplitude be confirmed. One possible approach to varying semantic context is suggested by research which induced differing cognitive sets within the subject thereby affecting the amount or type of processing that the subject imposed upon an item. For example, Craik and Tulving, 1975) as well as Hyde and Jenkins (1969) used varying types of instructions 149 to manipulate the amount of cognitive processing a subject used on a given item. In the Craik and Tulving (1975) study, subjects were given different types of instructions which were assumed to vary the "level of processing" a subject placed on the item. For example, Craik and Tulving had subjects simply rate words as to their structural, phonemic, or semantic features. Typically, a question was given prior to the presentation of a particular word. These questions varied in the level (type) of processing a subject was required to use on the word. A "low" level of processing was induced by a structural question: Is the word in capital letters? A "medium" level was generated by a phonemic question: Does the word rhyme with WEIGHT?. A "deep" level was induced by: Would the word fit in the sentence "He met the _____ in the street."? This study strongly suggests that instructions could be used to vary the type or amount of semantic context internally generated by a subject as they process a series of words. Some of these "induced contexts" could require considerable processing on the part of the subject (thereby producing a relatively large N400 component) whereas other instructions could induce a context requiring little cognitive processing by the subject (thereby producing a relative small N400 or even a P300 component). For example, sets of randomly chosen words from the same word- frequency norms (Kucera & Francis, 1967) could be presented 150 to subjects one at a time while EEG is being recorded. The independent variable would be the types of instructions subjects were given prior to being shown the list. These instructions would be designed to vary the a type of internal semantlc-context used by the subject. One type of instruction could be similar to the word reading condition in the present dissertation where subjects are asked merely to read the words as they appear on the screen. As was argued earlier, it is assumed that at least some subjects would impose their own semantic context or "subjective organization" on the information. This condition would serve as a "noninstructed" baseline condition. The other conditions would have specific instructions used to induce a specific internal context. One condition, similar to that used by Craik & Tulving, (1975), would generate a limited semantic context by asking the subject to look for words that contain a specific letter (e.g., "D"). This would require the subject to attend to the word and to decide whether or not the word meets the limited criterion induced by the contextual instructions (i.e., the word did or did not contain the letter "D"?). Another condition which would require the subject to generate a more involved context, would be to instruct the subject to rate the "emotional content" of a word after it is flashed on the screen [similar to the task used by Hyde & Jenkins (1969)1. Here, a subject would first have to decide 151 whether or not the word had "emotional" content. If it did, s(he) would have to "fit" that word into some subjective categorical scheme of emotions. Finally, another instructional condition could require the application of even more context by requiring the subject to make up a story using as many of the words flashed on the screen as possible. Given the "inverse relation" argument developed here, it would be predicted that the simple context of monitoring a letter would produce the smallest N400 amplitude, while the story context would produce the largest N400 amplitude. The "emotional content" should produce an intermediate N400 component since it required more of an application of semantic context than the letter monitoring task, but was less elaborate than the induced story context. Inherent in the "inverse context relationship" argument above is the notion that the N400 occurs when the subject begins to provide his own subjective context. An alternative, although not necessarily incompatible, explanation is that the N400 is produced when the subject becomes aware that there is no context and/or that s(he) will have to produce a context because one has not been provided. If the N400 is a function of the subject becoming aware that there has been a violation of semantic context or that s(he) will have to provide a context, then it is likely that the actual production or utilization of a semantic context 152 appropriate to processing the stimulus items (e.g., word) occurs later in time, say 2-3 seconds after the word has been presented. If so, it suggests that some reliable change in the ERP waveform would occur when the subject either generates or utilizes a semantic context to process the word 2 or 3 seconds poststimulus. However, in the typical N400 study (including the present study), recordings are made for 1 to 2 seconds. Consequently, if the context is utilized by the subject 1.5 to 3 seconds poststimulus, past researchers have missed any late ERP component related to the process of context utilization since it would have occurred during the interstimulus interval (time between stimulus presentations) when recordings typically are not made. Thus, if the N400 amplitude is due to awareness that a stimulus does not fit a given context rather than the actual production or use of an appropriate semantic context, then it would be predicted that some later ERP component should be found to reliably covary with the N400 amplitude. That is, if a large N400 amplitude correlates with a subjects awareness that an elaborate semantic context will have to be generated or used to process an item, there should also be a large deviation in some later ERP component (1.5-3) seconds later which corresponds to the production/utilization of an elaborate semantic context which is actually used to process that item. 153 If on the other hand, changes in N400 amplitude are indicative of both awareness and the actual generation and utilization of a semantic context to process that item (i.e., both processes occur in the 250-500 ms N400 time interval) then no late ERP component should be found. A possible test of these alternatives could be conducted using the proposed experiment just described above. Since the above experiment is already designed to vary subject generated semantic-context, all that would have to be done is to extend the recording time of the EEG to the 3 second poststimulus range. Then the later portions of subjects' ERPs could be examined for the occurrence of reliable components that vary with the semantic context induced by the differing instructional sets given to the subjects. Other Findings: Although the N400 component did not distinguish among the anomalous endings, word reading and word categorization conditions, several other results with the P4 (defined as the most positive peak in the 500-924 ms poststimulus range) and N5 (defined as the most negative peak in the 500-924 ms poststimulus range) data suggest that word reading and word categorization may differ quantitatively from the anomalous sentence condition. These results are important because they suggest that later ERP components may be related to the generation and utilization of semantic contexts although, as argued earlier, the most reliable "processing" components 154 may reside In the 1.5 to 3 second range. If so, then these data suggest that the N400 may be more a function of the awareness that a context has been violated or that a different semantic context is needed rather than being indicative of the actual generation or utilization of a more appropriate context. It should be noted, however, that the discussion of these data is post hoc since this dissertation did not make specific predictions based on them. Therefore, the following should be viewed with caution and is meant only to provide a basis for future research. The N5 peak amplitude, the vector mean 3 (average amplitude in the 500-800 ms range), and the vector mean 4 data (average amplitude in the 800-924 ms range) showed that at sites Fz, T3, and T4 the word categorization condition produced values that were more negative than the anomalous sentence task. Further the P4 peak amplitude data showed that the categorization condition was always less positive (more negative) than the anomalous condition at even more sites (F7, Fz, Cz, T3, T4, C3, C4 and T5). Similar results were found with the vector mean (VM3 and VM4, averaged amplitude) data. Overall, between 500 and 924 ms the ERP waveform of the categorization condition was more negative than the anomalous endings condition. Comparison of the word reading and anomalous sentence data revealed a similar pattern. The N5 peak amplitude data showed the word reading condition to have produced more 155 negative values than the anomalous sentence condition at sites Fz, Cz, T3, C3, C4 and T5. The P4 data always found that the word reading condition yielded less positive values than the anomalous condition at sites Cz, Pz, T3, T4, C3, C4 and T5. Similar patterns were again found with the vector mean data. The ERP waveform for the reading condition was shown to be more negative, throughout the 500-924 ms range, than the anomalous endings condition. Comparison of the word reading and word categorization N5 and P4 data found no significant differences of Interest. Taken together, these results help to support the context argument made earlier. It could be argued that of all of the conditions, word reading provided the least context (the subject had to provide his own) followed closely by the word categorization task where a subject had to provide a context for a word as it flashed on the screen [i.e., decide whether it belonged in category (context) 1 or in category (context) 2 1. In the anomalous sentence condition more of a context was provided for the subject. That is, the previous portions of the sentence lead the subject to expect a certain word. It was only at the point when the anomaly actually occurred that the subject was forced to reevaluate the context, hence the production of a smaller N400 relative to the word reading and categorization tasks in the earlier portions of the recording epoch (250- 500 ms). In later portions of the epoch (500-924 ms), the 156 hierarchy continued with word reading and word categorization remaining more negative than anomalous sentence endings. The fact that later positive components have recently been found to be related to short-term memory (Fabiani, Karis, & Donchin, 1986) and late negative components to semantic priming (Van Petten & Kutas, 1987) coupled with the findings just reported, suggests that the relation of these later ERP components to complex cognitive processing may be a fruitful area for future research. Other suggestions for further research are provided below. Implications for Additional Future Research If the N400 is truly inversely related to semantic context as argued above, several suggestions for additional future research can be given. First and foremost, the N400 component could be used as a diagnostic measurement in developmental psychology and in education where specific learning problems or disorders could be diagnosed. As mentioned earlier other ERP components have been able to differentiate dyslexics from normals (Naour & Languis, 1986; Miller & Languis, 1988) as well as distinguishing between varying age groups (Wilson et al., 1988) The N400 component may also prove useful in detecting differences between these groups, if semantic context could be established as a differentiating variable. That is, groups of subjects having different learning abilities or disabilities could be 157 given tasks like those proposed in the semantic context experiment outlined above, or in the inference experiment described below. It could be predicted, for example, that normal children may be more able to generate appropriate semantic contexts than learning disabled children. Hence, they should show more differentiation of N400 amplitude and possibly latency as a function of instructions than would the learning disabled children. Measurement of the N400 and related components could be used in developmental psycholinguistics to determine at what age or stage of development a certain class of words can be understood in context or complex inferences can be made. For example, students of various ages could be given logical syllogisms similar to those used by Bransford & Franks (1971). In the Bransford and Franks paradigm subjects are given three line premises (which set the context): The ant ate the jelly The jelly was on the table The table was in the kitchen They are then asked to choose between true and false inferences, i.e., The ants were in the kitchen (T), or The ants were in the grass (F). The problem with just having the student report whether a specific premise is true or false, does not distinguish between whether he or she made a correct inference or a lucky guess on that particular item. Measurement of the N400 component could make that 158 differentiation. If the student truly understood the inference (The ants were in the kitchen) then a less negative amplitude to the word "kitchen" should be generated compared to the false inference word "grass". That is, since the "kitchen" fits in the context set up by the premise and "grass" does not, "grass" should produce a more negative component than "kitchen" given the inverse context argument. Other complex cognitive tasks could be developed within a particular grade or age group in order to diagnose individuals with specific learning difficulties or to chart developmental progress. For example, basic elementary school materials could be designed to look at concept (semantic context) development using ERP's as the dependent variable. In social studies, a place could be named (e.g., a hospital), followed by three professions which either fit or did not fit the context (e.g., a plumber, a salesman, or a doctor) and the subject would have to make a forced "fit" or "no fit" decision. If the "inverse semantic context" argument prevails, then the "fit" decision (e.g., doctor) would show a very small N400 or a possible P300 to that word. Whereas, the "no fit" decision (e.g., salesman) would produce a large N400 component. If this latter task does produce changes in the N400, then younger aged children who cannot read could be diagnosed or developmentally tracked using pictures or auditory presentation instead of visual 159 presentation of words. Materials of a similar nature could also be constructed to study science topics, basic memory strategies (Dunn et al., 1987), chemistry problems (Schaff et al., 1988) or a host of other educationally relevant stimuli amenable to utilization of the ERP (particularly the N400) as an on-line method of measurement. Further, a more varied population should be studied (as suggested above). It is possible that the relationship between semantic context and the N400 in the present study is applicable only to right handed boys at a specific developmental or maturational stage which typically occurs during the age range from 10 to 11 years. Given these limitations, the data generated by this dissertation strongly suggest that the event-related potential, and the N400 component in particular, can be used to study complex cognitive processing in children and is worthy of further research. 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"Cloze" procedure: A new tool for measuring readability. Journalism Quarterly. 30. 415- 433. 170 Torello, M. W., & Duffy, F. H. (1985). Using brain electrical activity mapping to diagnose learning disabilities. In M. L. Languis (Ed.), Learning and the brain: Vol. 24. theory into practice (pp. 95-99). Columbus, OH: The Ohio State University. Torello, M. w., & McCarley, R. w. (1986). The use of topographic mapping techniques in clinical studies in psychiatry. In F. H. Duffy, (Ed.), Topographic mapping of the brain (pp. 383-389). Boston: Butterworth Publishers. Tulving, E., & Osier, S. (1967). Transfer effects in whole/part free-recall learning. Canadian Journal of Psychology. 21. 253-262. Tulving, E., & Pearlstone, Z. (1966). Availability versus accessibility of information in memory for words. Journal of Verbal Learning and Verbal Behavior. 5, 381- 391. Tulving, E. (1966). Subjective organization and effects of repetition in multi-trial free recall learning. Journal of Verbal Learning and Verbal Behavior. 5,, 19 3- 197. Tulving, E. (1962). Subjective organization in free- recall of "unrelated" words. Psychological Review. 69. 344-354. Van Petten, C. & Kutas, M. (1985). An electrophysiological study of ambiguity. Psychophysiology. 22. 618. Van Petten, C. & Kutas, M. (1987). Ambiguous words in context: An event-related potential analysis of the time course of meaning activation. Journal of Memory and Language. 26. 188-208. Vaughn, H. G., Ritter, W., & Slmson, R. (1983). Neurophysiological considerations in event-related potential research. In A. W. K. Gaillard & W. Ritter (Eds.). Tutorials in ERP research: Endogenous components (pp. 1-7). Amsterdam: North Holland Publishing Co. 171 Wilson, M. A., Naour, P. J., & Languis, M. L. (1988, April). Brain mapping on a letter reversal task between learning disabled and control males at 6-8 years and 10-12 years of age. In P. J. Naour (chair), Brain/behavior relationships in specific learning disabilities. Symposium conducted at the annual meeting of the American Educational Research Association, New Orleans, LA Wood, C. C. & Walpow, J. R. (1982). Scalp distribution of human auditory evoked potentials. II. Evidence for overlapping sources and involvement of auditory cortex. Electroencephalography and Clinical Neurophvsiology. 54, 25-38. APPENDIX A Human Subject's Review Form 172 173 BEHAVIORAL AND SOCIAL SCIENCES HUMAN SUBJECTS REVIEW COMMITTEE Ortgiml Review THE OHIO STATE UNIVERSITY X Continuing Review Research Involving Human Subjects ACTION OF THE REVIEW COMMITTEE With regard to the employment of human subjects In the proposed research p ro to c o l: B5B0U3 NEUKOCOGNITIVE STUDY OF LEARNING, M a rlin L. L an gu is, E d ucation al Theory and P ra c tic e THE BEHAVIORAL AND SOCIAL SCIENCES REVIEW COMMITTEE HAS TAKEN THE FOLLOWING ACTION: X APPROVED DISAPPROVED APPROVED WITH CONDITIONS* WAIVER OF WRITTEN CONSENT GRANTED * Conditions stated by the Committee have been met by the Investigator and, therefore, the protocol la APPROVED. It Is the responsibility of the principal investigator to retain a copy of each signed consent form for at least four (4) years beyond the termination of the subject's participation in the proposed activity. Should the principal investigator leave the University, signed consent forms are to be transferred to the Human Subjects Review Committee for the required retention period. This application has been approved for the period of one year. You are reminded that you must promptly report any problems to the Review Committee, and that no procedural changes may be made without prior review and approval. You are also reminded that the identity of the research participants must be kept confidential. Date: November 7, 1986 Signed (Chairperson) HS-025B (Rev. 3/85) 174 BIOMEDICAL SCIENCES REVIEW COMMITTEE ____ Original Review RESEARCH INVOLVING HOMAN SUBJECTS X C o n tin u in g Review THE OHIO STATE UNIVERSITT ____ Five-Year Review ACTION OF THE REVIEW COMMITTEE With regard to the employment of human subjects in the proposed research: 81H0312 OSU MULTIDISCIPLINARY TEAM FOR RESEARCH IN LEARNING AND HUMAN DEVELOPMENT COGNITIVE PATTERNS AMONG DEAF. LEARNING DISABLED, EDUCABLE MENTALLY RETARDED AND NORMAL PERSONS: AN EEG AND EYE MOVEMENT PATTERN STUDY - (NEUROCOGNITIVE STUDIES IN LEARNING), Marlin L. Languis, Educational Theory and Practice THE BIOMEDICAL SCIENCES REVIEW COMMITTEE HAS TAKEN THE FOLLOWING ACTION: X APPROVED ______DISAPPROVED APPROVED WITH STIPULATIONS* ______WAIVER OF WRITTEN CONSENT GRANTED ♦Stipulations stated by the Committee have been met by the investigator and, therefore, the protocol is APPROVED. It is the responsibility of the principal investigator to retain a copy of each signed consent form for at least four (4) years beyond the termination of the subject's participation in the proposed activity. Should the principal investigator leave the University, signed consent forms are to be transferred to the Human Subjects Review Committee for the required retention period. This application has been approved for the period of one year. You are reminded that you must promptly report any problems to the Review Com m ittee, and th a t no p ro ced u ral changes may be made w ith o u t p r io r re v ie w and a p p ro v a l. You are also reminded that the identity of the research participants must be kept confidential. Date: September 21, 1987 Signed: irp e rs o n HS-025H (Rev. 3/85) APPENDIX B Letter to Parents 175 176 March 9, 1987 Dear Parent, My name is Denise Santurrl. I am a parent of two children who attend Riverside Elementary School and am currently completing my Ph.D. dissertation research in the College of Education at Ohio State University. I am looking at the brain activity of normal children while they are Involved in such tasks as reading sentences and remembering li3 ts of words. Dublin Public Schools have given me permission to request the participation of fifth grade students at Riverside School. Your child, ______, has been identified by school personnel as a possible participant. Each child who participates In the study, will be asked to wear an elastic cap with 16 sensors to pick up his brain waves, while reading words and sentences. Brain activity is recorded during these language tasks and is converted into brain maps. It should be stressed that brain imaging is a noninvasive technique that is not harmful in any way to your child. When the tasks have been completed, your child will be asked about the strategies he used during the tasks. Before each child leaves, he will be given a map of his brain activity and an explanation will be given concerning how his brain was working during the mapping process. The brain mapping procedure will take place at Ohio State University's Brain Behavior Laboratory in room 488 at the Nisonger Center. We will schedule a time after school hours. It will require about 2 hours to complete, which includes time for breaks. I will arrange appointments and transportation in advance to meet your convenience as much as possible. For all parents and children who are interested in this project, an evening meeting will be held at Riverside Elementary School Library on Wednesday, March 18 at 7:00 P.M. for me to demonstrate and explain brain imaging. I will answer any questions and show a videotape of the brain mapping procedure. Participation in this project is entirely voluntary. If you grant permission for your child to participate and later decide to withdraw your child, your request will be honored at any time. Sincerely, Denise A. Santurri Child's Name ______ Address______Phone______ I give permission for my child to participate in the study. I will be able to attend the demonstration meeting. I will not be able to attend but want additional information. Parent Signature APPENDIX C Sample Tasks 177 SAMPLE TASKS 1. The baby shouldn't be left alone. 2. Mom took my temperature with a thermometer. 3. John was fired but he couldn't tell his leg. 4. Alexander Graham Bell invented the rock. 5. Greg's mother writes a column for the newspaper Set I Set II pear shoes yellow doll apple jacket blue boat grapes pants red ball APPENDIX D Consent to Special Treatment Form 179 180 III u . u l...i ■■ I p ro to co l 4 011103)2 SocBch Sc ca*u«r to in r m ci m -chiu 'U S b IO BtoMed B el Mar 1 in Languis ■ . I, • *•>•*» •»«»•*«•• •» «!••«« or d esig n a te " ••••«!■>•• ***i*-.*m •' * *i >n ♦* y t »• U* UlU«tD| trailsftl «r pvactiJvra »*4 BtacK iH litanil <> lk»f **r «*a m tiM klr aKiiiK) I* ii* P»r*n*«* (--.I Ilk* I t.r**> Recording of hraln elecrr I ml -ertlul ry and r u f H n . time to a ilmole decision meklnR cognitive task. ______ «*«« ...... (BjHlTfr NM ml Ik* ■■*•*■■•• 1*1 Ira******) a r l l H •» Ike l*a*la*M .» K«II«* ill Deterrr.! nlH nn nf nenrnpSi-a I tilnnlf correlate* of learning and performance via attachment of brain activity im inr cap to the heaJ. ______;______;______n«i* u <**• ** a**i •• •• im niiuin ucituei Heurorhvslplotlcel >s»e««ment of Learning. I. r****** *1 ik* a t tr**t~»ii t s s m n r n t of nenrnphvalolog 1 r, j n tttrm Hrmnnsrrflred w h i t e performing a variety nf rnjntftv* reslta L-hlrh require a derlclnn The < nfnr-mr I on la to be used to determine Individual and VTOun variability In several conppnenti- o f b r l l n activity and lt» rciatlon tp.rejction time.______ I. N ilb l* appragrlait altaraaclva •( iM iuini: Kong I. II« « I|||| ••* tiaka r***«*kly «• b* Mild tenderness nf a r a lp frnn plare^.enr nf hraln activity aenanr , may occur Infrequently.______ a. raaaiki* k*n*riia far *.*w «i*/*M i*iri The developmenr nf diagnostic m m w n t methodology___ Slhlch v lll enhance more completely the under-Standlng nf Individual varlahl llry . ln_ laarnlrn characterlatlca .or cognitive dyafur.cc.lnn ______- S. k iiiie n i aatatta* *r *»k)*ct'* K nicl**n**i Apprnx.1 mare i y one H I hour v l l l he reg.-lced for a n Individual protocol aesalon. Several i m t c m may he required of rtrriln a n h j e c r a - Ihankf tm baa rri*U«4 «Wa« ^tKduft 4ntriW4 aW*«. |Wvt d|k(i m « Mkjm, tat irm iwI all tw itlM i it mr itililK tU *. 1 w tiriiw it tkat I m r ( n i h i fkwU t ktft ililU iM l tM iilM . b/IM Ikii i m U 1 m 4 Ik* ritki OacrifcW itovt iM I tbaa; ba/aba ba« I»M as asflala «U paaaUla dika ar i m M(( i i1n i. I bit tltt lafavMtln atiatMt Ira m , mr fr«n (ta pafaaa 1 m auiharln4 la taam aali *111 lo aU caafUanllai «l»M 1 lia d fiu llf airaa trM nrfM If pU«la| ay taltd U bar* ______• 1 «M«ratiM that, nbtra aaftairiau, lb V.l. 0N*4 m 4 M ilM atnila* atf lu fait tatadt *f lilt viMarth prajid* I aaiaraiaM tkai I mm (tmm W vtiM ria *p eaaaiat mm4 p a n id p ttla la ckta pfa)ac( at at>| tl« aflar aatifflH lb prajatl U tatlH altlaai pn]«aUUft (m m i mat a. la p u riK tii baa Wt« gtva* la mm caararalag «bla trrataaat ar fm a d N . I W n n il M l I.U r aMarataae Ilf1*! > W ltM*«(«*) ______^ i t " * ‘ ^fifaw Aotiiariii4 la Camaac l*r - If l««wtr«a) ” " fta*«ira4 • I aarilly tKai | Mvt paraaaally catpUud atl blaaba la thii far* lb la iW lakjad ar bl»/>*r npi«Maiail»a ta|M iit»| IN aabjact at M i/N r v*»r**»at«cl»* eo atgi lu / ) ^ S' / / / liiftil|^#ivW ^*rV»oJatr"Vrr«( vaf ^ r^fwihtar t i*a lapr »*#-f •! i * t V f«r» iff- m ' s ' b m APPENDIX E List of Ninety Sentences 181 SENTENCE TASK Block 1 The old house will be torn down. You write your name on your hair. The boy fell down and skinned his knee. The sailboat passed under the bridge. He did not want to work at night. He spread the warm bread with socks. He added his name to the list. He played his stereo too loud. The baby was fed some warm knee. They raised pigs on their door. The mother bear protected her cub. They left the dirty dishes in the book. He swept the floor with a broom. Sunday morning people pray in their sugar. The hot sun made Judy's popsicle melt. Block 2 The dough was put in the hot scissors. Don't touch the wet story. The child had a serious illness. The argument was settled by the tooth. Don't believe everything you chew. I can't remember his rust. The children went outside to play. They washed the dishes after dinner. She punched him in the aquarium. The parents asked their daughter tocome home. The teacher wrote the problem onthe thread. His job was to mow the sidewalk. Dad bought milk at the store. She awoke after a bad lemon. Her new shoes were the wrong size. Block 3 He liked cream and sugar in his letter. She laid down and took a nap. Judy shoved her way through the crowd. Fire burned the house to the ground. The captain stayed with his sinking tone. She dried the dishes with the floor. He kept his horse on a tomato. Fred put the worm on a hook. John's mom refused to give him a cloud. The gambler had a streak of bad coat. Nancy lit the candles with a match. Water and sunshine help plants fly. A candy bar is sweet to giggle. We can see Mars through a telescope. At night the woman locked the leaf. Block 4 Please put some milk in the miracle. The horse galloped back to the barn. The door won't open with the wrong key. Julie is a new student in our bush. Scary movies give me bad dreams. Chicago is a very busy city. John tried to fix the chain on his bike. Shark attacks occur close to size. A rose is a kind of doorway. I put my pictures in a photo album. Potatoes grow under the ground. She called her dad at his pencil. The old milk tasted very sour. Sally grows flowers in her garden. Father carved the turkey with a cap. 184 Block 5 The pigs wallowed in the mop. The pizza was too hot to eat. The children held hands and formed a minute. George must keep his dog on a finger. Motorcycles can be very noisy. They sat together without saying a wheel. The Pilgrim's ship landed at Plymouth Rock. A thief once robbed that inch. He mailed the letter without a drill. Cathy is liked by all her friends. My dog catches a ball in her mouth. None of his books made tape. Tall is the opposite of short. It is hard to admit a bathtub. All the guests had a good time. Block 6 The dog chased the cat up the tree. The rude waiter was not given a sky. The wealthy child attended a private frog. She weighed the bananas on a scale. Goldilock's fell asleep in the baby bear's bed. Cheetahs can run very fast. He scraped the cold food from his chain. She loosened the laces in her rain. Most cats see very well at court. A dog has a good sense of smell. The raft floated down the dryer. Santa lives at the north pole. The child fed the ducks some stale chair. The barber is cutting my brother's hair. The piano was out of tune. APPENDIX F Word Reading List 185 READING CONDITION List 1 Run A Run B Run C pear game uncle robin carrot spider hammer tulip hammer snow chair game motel snow blue carrot uncle dime tennis robin tulip dime socks chair socks pear snow game dime pear pine hammer robin uncle pine carrot chair tennis pine tulip blue tennis spider motel socks blue spider motel List 2 Run A Run B Run C sparrow yellow fly wrench ball rain door oak ye11ow rain penny wrench hotel rose ball peas peas penny soccer desk door penny boots sparrow boots sparrow rose ball hotel hotel oak fly oak aunt door peas desk rain soccer rose aunt aunt fly wrench desk ye 11ow soccer boots APPENDIX G Category List 187 CATEGORIES Set 1 Set 2 Spoon Dog Leg Car Fork Cat Head Truck Stove Horse Hand Bus Pan Deer Eye Bike Bowl Pig Nose Train Oven Lion Feet Boat Mixer Cow Toe Wagon Knife Bear Finger Plane CATEGORIZING CONDITION List 1 Run A Run B Run C spoon pan knife dog deer dog fork stove mixer cat lion cat stove fork oven horse cow horse pan spoon bowl deer bear pig bowl bowl stove pig pig deer oven oven pan lion horse lion mixer mixer fork cow cat cow knife knife spoon bear dog bear List 2 Run A Run B Run C leg eye finger car train car head hand toe truck boat bus hand head feet bus wagon truck eye leg nose bike plane bike nose feet hand train bike train feet toe eye boat bus boat toe nose head wagon truck wagon finger finger leg plane car plane APPENDIX H Handedness Inventory 190 191 Brain Behavior Laboratory Name_ Edinburgh Hundedness Inventory (modified) Date_ Time R ight L e ft 1. (back side) write your name ______ 2. (back side) draw a happy face ______ 3. open th is box ______ k. show me how you would throw th is b a ll ______ 5. show me how you would use these scissors ______ 6. show me how you would use th is toothbrush ______ 7. show me how you would cut cheese w ith th is kn ife ______ 8. show me how you would use th is spoon ______ 9. show me how you would s tr ik e th is match ______ 10. show me how you would open th is ja r ______ 11. show me how you would use th is tube i f i t were a telescope ______ 12. show me how you would look through the hole at this "X" ______ 13. I'm going to whisper something to you softly;close your eyes, you may turn your head to hear better if you like, repeat what I whisper 11*. use th is broom 15. k ick a football (simulate) 16. step on a bug (sim ulate) PERSONAL INFORMATION A. State of well being ( ) excellent ( ) average ( ) fair record any current illness ______ B. Sleep la s t n ig h t ______hours C. Food intake last 2k hours ( ) average ( ) unusual record unusual eating ______ 0. Smoking ( ) yes ( ) no record type and extent E. Alcohol consumed ( ) yes ( ) no in last 2k hrs. record type and amount F. Drugs, medication ( ) yes ( ) no record type and amount, when last taken APPENDIX I Trial Sentences 192 193 TRIAL SENTENCES 1. The baby shouldn't be left alone. 2. Mom tookmy temperature with a thermometer. 3. John was fired but he couldn't tell his leg. 4. Alexander Graham Bell invented the rock. 5. Greg's mother writes a column for the newspaper. APPENDIX J Sentence Recognition and Rating Task 194 195 Sentences ID Set A Subject #______ 1. The old house will be torn down. YES NO 1.___ 2.____ 3.__ 4.___ 5.___ Likely Unlikely 2. The children went outside to play. YES NO 1.___ 2.____ 3.__ 4.___ 5.___ Likely Unlikely 3. The teacher wrote the problem on the thread. YES NO 1.___ 2.____ 3.__ 4.___ 5.___ Likely Unlikely 4. The school year began in the fall. YES NO 1.___ 2.____ 3.__ 4.___ 5.___ Likely Unlikely 5. Don't touch the wet story. YES NO 1.___ 2.____ 3.__ 4.___ 5.___ Likely Unlikely 6. His job was to mow the sidewalk. YES NO 1.___ 2.____ 3.__ 4.___ 5.___ Likely Unlikely 7. Dad bought some milk at the store. YES NO 1.___ 2.____ 3.__ 4.___ 5.___ Likely Unlikely 8. Her new shoes were the wrong size. YES NO 1.___ 2._____ 3.__ 4.___ 5.___ Likely Unlikely 9. He played his stereo too loud. YES NO 1.___ 2.____ 3.__ 4.___ 5.___ Likely Unlikely 10. She was glad the test was over. YES NO 1.___ 2.____ 3.__ 4.___ 5.___ Likely Unlikely 196 Sentence ID Set A Subject # 11. They left the dirty dishes in the book. YES NO 1. 2 . 3. 4. 5.___ Likely Unlikely 12. The baby was fed some warm knee. YES NO 1 . 2 . 3. 4. 5. Likely Unlikely 13. The child had a serious illness. YES NO 1.___ 2.___ 3.___ 4. 5.___ Likely Unlikely 14. The ship sailed into the thick broom. YES NO 1. 2 . 3. 4. 5. Likely Unlikely 15. Pete won the bicycle thread. YES NO 1 . 2 . 4. 5. Likely Unlikely 16. The mother bear protected her cub. YES NO 1. 2 . 3. 4. 5.___ Likely Unlikely 17. The sailboat passed under the bridge YES NO 1 . 2 . 3. 4. 5. Likely Unlikely 18. You write your name on your hair YES NO 1 . 2 . 3. 4. 5. Likely Unlikely 19. They raised pigs on their door. YES NO 1 . 2 . 3. 4. 5. Likely Unlikely 20. I can't remember his rust. YES NO 1 .__ 2. 3. 4. 5.___ Likely Unlikely 197 Sentences ID Set B Subject # 1. Sunday morning people pray in their sugar. YES NO 1 . 2 . 3. 4. 5.___ Likely Unlikely 2. He spread the warm bread with socks. YES NO 1 . 2 . 3. 4. 5. Likely Unlikely 3. He swept the floor with a broom. YES NO 1.___ 2.____ 3.__ 4. 5. Likely Unlikely 4. The dough was put in the hot scissors. YES NO 1. 2 . 3. 4. 5. Likely Unlikely 5. Yesterday they canoed down the salt. YES NO 1. 2 . 3. 4. 5. Likely Unlikely 6. The boy fell down and skinned his knee. YES NO 1. 2 . 3. 4. 5. Likely Unlikely 7. She punched him in the aquarium. YES NO 1. 2 . 3. 4. 5. Likely Unlikely 8. The hot sun made Judy's popcycle melt, YES NO 1. 2 . 3. Likely Unlikely 9. She awoke after a bad lemon. YES NO 1 . 2 . 3. 4. 5.___ Likely Unlikely 10. The parents asked their daughter to come home. YES NO 1 .__ 2. 3. 4. 5.___ Likely Unlikely 198 Sentences ID Set B Subject # 11. January is the first month of the size. YES NO 1.___ 2.___ 3.___ 4.. Likely Unlikely 12. He threw a rock and broke the window. YES NO 1 . 2 . 3. 4. 5. Likely Unlikely 13. They washed the dishes after dinner. YES NO 1. 2 . 3. 4. 5. Likely Unlikely 14. Don't believe everything you chew. YES NO 1. 2 . 3. 4. 5. Likely Unlikely 15. The students thought the test was easy. YES NO 1 . 2 . 3. 4. 5. Likely Unlikely 16. He did not want to work at night. YES NO 1 . 2 . 3. 4. 5. Likely Unlikely 17. The argument was settled by the tooth. YES NO 2 . 3. 4. 5. Likely Unlikely 18. He added his name to the list. YES NO 1. 2 . 3. 4. 5. Likely Unlikely 19. The mother bear protected her cub. YES NO 1. 2 . 3. 5. Likely Unlikely 20. They raised pigs on their door. YES NO 1 .__ 2. 3. 4. 5.___ Likely Unlikely 199 Sentences 2E Set A Subject #_ 1. The gambler had a streak of bad coat. YES_ NO______1._ 2.__ 3.______4.. 5.___ Likely Unlikely 2. Potatoes growunder the ground. YES_ NO 1 1.. 2.2 .._ 3.______4. 5.___ Likely Unlikely 3. She boiled the eggs in water. YES NO 1. 2 . 3. 4. 5.___ Likely Unlikely 4. She called her dad at his pencil. YES NO 1. 2 . 3. 4. 5.___ Likely Unlikely 5. The old milk tasted very sour. YES NO 1. 2 . 3. 4. 5.___ Likely Unlikely 6. John tried to fix the chain on his bike. YES NO 1.___ 2.___ 3.____ 4.. 5. Likely Unlikely 7. Shark attacks occur close to size. YES NO 1. 2 . 5.___ Likely Unlikely 8. We borrowed books from our school library. YES NO 1 . 2 . 3. Likely Unlikely 9. Chicago is a very busy city. YES NO 4. 5.___ Likely Unlikely 10. Father carved the turkey with a cap. YES NO 1 .__ 2. 3. 4. Likely Unlikely 200 Sentences 2E Set A Subject H 11. My father goes jogging every stream. YES. NO 1.1 .___ 2.2 .._____ 3. 5.___ Likely Unlikely 12. He yelled at the top of his dinner YES NO 1.1 .___ 2.2 . 3. 5. Likely Unlikely 13. Fred put the worm on a hook. YES NO 1.____ 2._____ 3.___ 4 . _ Likely Unlikely 14. The captain stayed with his sinking tone. YES NO 1. 2 . 3. 5.___ Likely Unlikely 15. She laid down and took a nap. YES NO 1 . 2 . 3. 5. Likely Unlikely 16. She dried the dishes with the floor. YES NO 1 . 2 . 3. 5. Likely Unlikely 17. At night the woman locked the leaf. YES NO 2 . 3. 4. 5. Likely Unlikely 18. Nancy lit the candles with a match. YES NO 1 . 2 . 3. 5. Likely Unlikely 19. A candy bar is sweet to giggle, YES NO 1 . 2 . 3. 5. Likely Unlikely 20. We can see Mars through a telescope. YES NO 1.1 . 2.2 .. 3. 5. Likely Unlikely 201 Sentences 2E Set B Subject # 1. Judy shoved her way through the crowd. YES NO 1 . 2 . 3. 4. 5.___ Likely Unlikely 2. Fire burned the house to the ground. YES NO 1 . 2 . 3. 4. 5. Likely Unlikely 3. He liked cream and sugar in his letter. YES NO 1 . 2 . 3. 4. 5.___ Likely Unlikely 4. He kept his horse on a tomato. YES NO 1. 2 . 3. 4. 5. Likely Unlikely 5. Summer is the hottest season o£ the puddle. YES NO 1 . 2 . 3. 4. 5. Likely Unlikely 6. Scary movies give me bad dreams. YES NO 1. 2 . 4. 5. Likely Unlikely 7. Julie is a new student in our bush. YES NO 1 . 2 . 4. 5. Likely Unlikely 8 . David ate eggs and toast for breakfast. YES NO 1 . 2 . 3. 4. 5. Likely Unlikely 9. Sally grows flowers in her garden. YES NO 1. 2 . 3. 4. 5. Likely Unlikely 10. A rose is a kind of doorway. YES NO 1 .__ 2. 3. 5.___ Likely Unlikely 202 Sentences 2E Set B Subject #_ 11. I put my pictures in a photo album. YES NO 1.1 . 2. 2.. 3. 4. 5.___ Likely Unlikely 12. The door won't open with the wrong key. YES NO 1.___ 2.___ 3.___ 4.. 5. Likely Unlikely 13. Practice the piano every bicycle. YES NO 2 . 3. 4. 5. Likely Unlikely 14. The horse galloped to the barn. YES NO 1 . 2 . 3. 4. 5. Likely Unlikely 15. The mouse ate some cheese. YES NO 1 . 2 .. 3. 4. 5. Likely Unlikely 16. Please put some milk in the miracle. YES NO 1. . __ 2.2 .. 3. 4. 5. Likely Unlikely 17. John's mom refused to give him a cloud. YES NO 1.___ 2._____ 3.__ 4.. 5. Likely Unlikely 18. Water and sunshine help plants fly. YES NO 1 . 2 . 4. 5. Likely Unlikely 19. She called her dad at his pencil. YES NO 1.___ 2.___ 3.. 4. 5. Likely Unlikely 20. Fred put the worm on a hook. YES NO 2. 3. 4. Likely Unlikely 203 Sentences 3F Set A Subject # ______ 1. Cathy is liked by all her friends. YES NO 1.___ 2._____ 3.__ 4_.__ 5.___ Likely Unlikely 2. The Pilgrim's ship landed at Plymouth Rock. YES NO 1.___ 2._____ 3. 4 .____5.___ Likely Unlikely 3. None o£ his books made tape. YES NO 1.___ 2._____ 3.___ 4._ 5.___ Likely Unlikely 4. Motorcycles can be very noisy. YES NO 1.___ 2._____ 3. 4 .____5.___ Likely Unlikely 5. George must keep his dog on a finger. YES NO 1.___ 2._____ 3.___ 4._ 5.___ Likely Unlikely 6 . He did not believe her story was noisy. YES NO 1.___ 2._____ 3.___ 4._ 5.___ Likely Unlikely 7. It is hard to admit a bathtub. YES NO 1.___ 2._____ 3.___ 4._ 5.___ Likely Unlikely 8. The dog chased the cat up the tree. YES NO 1.___ 2._____ 3.___ 4._ 5.___ Likely Unlikely 9. He put some drops in his eyes. YES NO 1.___ 2._____ 3.___ 4._ 5.___ Likely Unlikely 10. All the guests had a good time. YES NO 1.___ 2._____ 3.___ 4._ 5.___ Likely Unlikely 204 Sentences 3F set A Subject #______ 11. The girl was smart for her foot. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 12. They sat together without saying a wheel. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 13. The pizza was too hot to eat. YES NO 1.__ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 14. The pigs wallowed in the mop. YES NO. 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 15. My dog catches a ball in her mouth. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 16. The children held hands and formed a minute. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 17. Lemons are very sour. YES NO 1.___ 2.___ 3.___ 4.____ 5.___ Likely Unlikely 18. A thief once robbed that inch. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 19. Tall is the opposite of short. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 20. The rude waiter was not given a sky. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 205 Sentences 3F Set B Subject #______ 1. Beth likes to read her favorite nursery rhyme. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 2. He mailed the letter without a drill. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 3. She loosened the lace3 in her rain. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 4. Cheetahs can run very fast. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 5. She weighed the bananas on a scale. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 6. The barber is cutting my brother's hair. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 7. Clowns and trapeze artists perform at the flower. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 8 . The child fed the ducks some stale chair. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 9. The piano was out of tune. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 10. While skiing Randy broke his eye. YES NO 1.___ 2.___ 3.___ 4.___ 5.___ Likely Unlikely 206 Sentences 3F Set B Subject #. 11. Santa lives at the North Pole. YES NO 1.___ 2.___ 3.____ 4. 5.___ Likely Unlikely 12. The raft floated down the dryer. YES NO___ 1.1 .___ 2.2 ..______3. 4. 5.___ Likely Unlikely 13. A dog has a good sense of smell. YES NO 1.___ 2.____ 3 ._ 4. 5.___ Likely Unlikely 14. Most cats see very well at court. YES NO 1 . 2 . 3. 4. 5.___ Likely Unlikely 15. He hung her coat in the closet. YES NO 1 . 2 . 3. 4. 5.___ Likely Unlikely 16. Goldilocks fell asleep in the baby bear's bed YES NO 1.___ 2._____ 3._ 4.___ Likely Unlikely 17. He scraped the cold food from his chain. YES NO 1.___ 2._____ 3._ 4.___ 5.___ Likely Unlikely 18. The wealthy child attended a private frog. YES NO 1 . 2 . 3. 4. 5.___ Likely Unlikely 19. It Is hard to admit a bathtub. YES NO 1 . 2 . 4. 5.___ Likely Unlikely 20. The pizza was too hot to eat. YES NO_ 1. 2.__ 3. 4. 5. Likely Unlikely APPENDIX K T- Maps 207 208 e N—400 CHILD STUDV 136T -4 6 T -1 3 7 T -2 2 8 T -3 1 9 T 410T -5 0 0 T u A \>y /V -1 0 0 0 52 £ 0 4 : 356 506 6 60 612 Figure 23. Event-related potentials by recording site for anomalous sentence endings (----) and congruent sentence endings (- - -). The topographic map shows the t distribution (in t values x 100) for the comparison of mean averaged amplitudes within the 250-500 ms range between the two sentence ending conditions. 209 N — 4-00 CHILD STUDV FP1 FP2 5013 T F7 409T F3 3 1 8 T FZ / 2S7T CZ f 136T PZ \ T3 |illl T 4 137T C3 V C4- -3 1 9 T T5 4-10T T6 -5 0 0 T 01 02 EVE Figure 24. Event-related potentials by recording site for congruent sentence endings (---- ) and categorization of words (- - -). The topographic map shows the t distribution (in t values x 100) for the comparison of negative peak amplitudes in the 250-500 ms range between congruent endings and categorizing words. 210 e N-400 CHILD STUDV 500T 4 0 3 T ^ 7 “ -1 3 7 T V 410T 500T A ... V -1000 52 £04 : 356 5 0 3 6 6 0 81£ Figure 25. Event-related potentials by recording site for congruent sentence endings (---- ) and categorization of words (- - -). The topographic map shows the t distribution (in t values x 100) for the comparison of positive peak amplitudes in the 250-500 ms range between congruent endings and categorizing words. 211 N-400 CHILD STUDV FP1 FP2 F 7 F9 31ST FZ CZ 136T PZ 45T T3 7 > r y l- T 4 -1 3 7 T C3 -2 2 8 T C4- T5 -4-10T TS -5 0 0 T __/v 01 02 EVE ■ 1 M 0 52 204- : 356 508 660 812 Figure 26. Event-related potentials by recording site for congruent sentence endings (---- ) and categorization of words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of mean averaged amplitudes within the 250-500 ms range between congruent endings and categorizing words. 212 N - 4 0 0 CHILD STUDV E00T 4459T a J18T £27T 136T -1 3 7 T -4-llBT -S 00 T ■‘»0 52 Figure 27. Event-related potentials by recording site for congruent sentence endings (---- ) and reading unrelated words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of negative peak amplitudes in the 250-500 ms range between congruent endings and reading words. 213 N-4-00 CHILD STUDV FP1 FF'£ 5 0 0 T F7 -409T FS 3 1 S T FZ £ £ ? T CZ 1 3 6 T PZ 4 5 T T3 - 4 6 T T4 - 1 3 ? T C3 - £ 2 8 T CA - 3 1 9 T TS - 4 1 0 T T6 - 5 0 0 T 01 02 EVE -iB00 se £ 0 4 : 3 5 6 5 0 6 6 6 0 81 £ Figure 28. Event-related potentials by recording site for congruent sentence endings (---- ) and reading unrelated words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of positive peak amplitudes in the 250-500 ms range between congruent endings and reading words. 214 N-4-00 CHILD 5TUDV 5I3UT -M39T 318T ££?T 'S -£ £ 8 T 3 I'D I -4-lloT -5 0 0 T Figure 29. Event-related potentials by recording site for congruent sentence endings (---- ) and reading unrelated words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of mean averaged amplitude within the 250-500 ms range between congruent endings and reading words. 215 N-4-00 CHILD STUDS E0IST W3T 1 36T -13? T -4-10T -5 0 0 T Figure 30. Event-related potentials by recording site for anomalous sentence endings (----) and categorization of words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of the largest positive peak in the 500-924 ms range between anomalous endings and categorizing words. 216 e N - 4 0 0 CHILD STUDV 5 0 0 T £2? T 13ST -1 3 7 T -2 2 8 T -3 1 9 T -4 1 0 T -5 0 0 T 0 S£ 2 0 4 356 506 6 60 ! 61 Figure 31. Event-related potentials by recording site for anomalous sentence endings (----) and categorization of words (- - -). The topographic map shows the distribution (in t. values x 100) for the comparison of the mean averaged amplitude within the 500-800 ms range between anomalous endings and categorizing words. 217 N - 4 0 0 CHILD STUDV 500T 403T 318T vmmv 1 36T - 1 3?T i£ 8 T -•410T -5 0 0 T Figure 32. Event-related potentials by recording site for anomalous sentence endings (---- ) and reading unrelated words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of the largest negative peak within the 500-924 ms range between anomalous endings and categorizing words. 218 N-4-00 CHILD STUDV SfflJT 443-3 T 411ST Figure 33. Event-related potentials by recording site for anomalous sentence endings (---- ) and reading unrelated words (- - -). The topographic map shows the distribution (in t. values x 100) for the comparison of the largest positive peak within the 500-924 ms range between anomalous endings and categorizing words. 219 N-400 CHILD STUDV **59T Figure 34. Event-related potentials by recording site for anomalous sentence endings (----) and reading unrelated words (- - -). The topographic map shows the distribution (in t values x 100) for the comparison of the mean averaged amplitude within the 500-800 ms range between anomalous endings and categorizing words.