UNIVERSITY OF CINCINNATI

Date: 1-Feb-2010

I, Lisa D. Cahill , hereby submit this original work as part of the requirements for the degree of: Doctor of Philosophy in Communication Sciences and Disorders It is entitled: Cortical responses to speech stimuli in hearing impaired infants measured by

fMRI and auditory evoked potentials

Student Signature: Lisa D. Cahill

This work and its defense approved by: Committee Chair: Robert Keith, PhD Robert Keith, PhD

David Brown, PhD David Brown, PhD

Scott Holland, PhD Scott Holland, PhD

Peter Scheifele, PhD Peter Scheifele, PhD

5/6/2010 369

Cortical responses to speech stimuli in hearing impaired infants measured by fMRI and auditory evoked potentials

A dissertation submitted to the Division of Research and Advanced Studies of the University of Cincinnati in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY Ph.D.

in the Department of Communication Sciences and Disorders of the College of Allied Health Sciences

2010

Lisa D. Cahill, M.A., CCC-A

B.A. Indiana University – Bloomington, 1996 M.A. University of Cincinnati – Cincinnati, 1998

Committee Chair: Robert W. Keith, Ph.D.

Committee Members: Scott K. Holland, Ph.D. Peter Schiefele, Ph.D. David Brown, Ph.D.

ABSTRACT

Many brain regions respond and adapt to early exposure to sensory experience. Long periods of auditory deprivation, particularly during critical or sensitive periods of neurodevelopment, are known to produce cortical reorganization including functional and/or structural deficits at all levels of the human auditory system. Auditory evoked potentials have been used as an index of maturation of both normal-hearing and hearing impaired auditory cortical networks, as well as neuronal recovery time upon initiation of auditory stimulation (Sharma, Dorman, & Spahr,

2002a). However, the relationship between neuronal and vascular cortical activity in the developing impaired auditory nervous system has not been fully characterized.

The overall aim of the present research was to perform an exploratory analysis of the relationship between the P1 auditory evoked potential response and residual auditory cortical function as shown by fMRI activation maps in moderate or severe to profoundly hearing impaired subjects.

Electrophysiologic and functional neuroimaging evaluations using speech stimuli were conducted on fourteen subjects ages 9-24 months with residual hearing ranging from 85 dBHL to

100 dBHL pure tone average (PTA), in the .5 to 2 KHz range. Subjects who met the study’s eligibility requirements were made available through the Cincinnati Children’s Hospital Medical

Center Departments of Otolaryngology and Radiology.

Electrophysiological testing included evaluation of P1 cortical auditory evoked response with a hearing aid on using a Klatt generated /ba/ stimulus in the soundfield at 75 dBSPL. Subjects unable to wear an amplification device during the testing were stimulated using an Eartone 3A insert earphone at a minimum of 10 dB sensation level based on aided audiometric results. An

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fMRI paradigm consisting of Narrow Band Noise (NBN) and stories was administered under sedation at the end of a clinical scan in a 3 Tesla system using sound presentation levels of 10 dB sensation level based on audiometric results. Stimuli were interleaved with silence in a block- periodic counterbalanced fMRI design with 30-second on-off intervals. Results were subjected to a correlation analysis to search for a relationship between P1 characteristics and the number of activated fMRI pixels detected within specified regions of interest in the auditory cortex. In addition, a multiple regression analysis was conducted to assess the prediction of the P1 latency in our sample based on duration of hearing aid use and age at the time of the fitting.

The importance of early intervention for congenital hearing loss has been well established using a variety of measures, including speech and language outcome, cognitive and educational assessment techniques, and electrophysiologic measures. The P1 auditory evoked potential has been acknowledged and characterized as a biological indicator of auditory neurodevelopment in normal hearing children and in children with cochlear implants. (Sharma, et al., 2005). In this sample of infants with hearing aids, multiple regression analysis results suggest that the age of hearing aid fitting and duration of hearing aid use are significant predictors of shifts in P1 latency even during very early stages of development (F (2,8) = 10.266, p= .006). Combining both predictors in the model explained 72% of the overall variance (R2 = .720). These findings provide additional support for the essential influence of early sensory exposure on auditory neuromaturation during the first year of life using a non-invasive physiological measure.

Activity related cortical signals reflecting higher auditory cortical function could be more clearly understood by interrelating electrophysiologic findings with non-invasive mapping techniques.

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fMRI evaluation of the central auditory system prior to cochlear implantation may offer a possible means of objective assessment of auditory nervous system pathways. Auditory cortex activation observed in this sample of hearing impaired toddlers was highly variable between subjects. Group and individual maps of BOLD activation were also markedly dissimilar from what has been observed in normal hearing subjects within the same age range (Smith, et al.,

2008). In all subjects, common areas of BOLD activity outside of auditory regions included positive BOLD within the medial frontal gyrus and anterior cingulate cortex, and negative

BOLD responses in the inferior frontal gyrus. Areas that were shown to possess a positive correlation with shifts in P1 latency included the left middle frontal gyrus and inferior frontal gyrus, the anterior cingulate, and bilaterally in insular and occipital areas.

Results indicated that although fMRI activation patterns do not exhibit a predictive relationship with P1 latency (r(10) = .038, p = .456), the strength of the auditory BOLD response was inversely correlated with P1 amplitude (rS = -.85, p = .001), suggesting more localized regions of cortical responsivity in subjects with robust P1 waveforms. This finding was difficult to interpret in light of fMRI sedation effects, and may be a reflection of normal cortical maturational processes that are known to influence the anatomical generators of the P1 response.

In order to verify and further characterize a possible inverse connection between neural and vascular activity in thalamocortical and primary auditory cortical regions, more information is needed regarding developmental effects auditory deprivation on P1 amplitude.

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Lisa Dawn Cahill, 2010 All rights reserved

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ACKNOWLEDGEMENTS

I gratefully acknowledge my family as the most important contributors to the completion of this dissertation. The emotional and moral support of my husband, and the patience and endurance of my children have helped make this research possible. I’ve been amazed by their ability to adapt and understand the time I have spent pursuing this goal. Many thanks to my in-law family who has consistently offered assistance and support, and to my parents for motivating me and instilling in me a strong work ethic and concern for what is right and good. Thanks to my sister for being my best friend, and to my aunts, uncles, and cousins for their constant encouragement and interest in my work.

I would also like to thank the entire faculty of the department of Communication Sciences and

Disorders at the University of Cincinnati. I have received invaluable support in at least one instance from nearly every member of the department. My dissertation committee specifically,

Dr. Robert Keith, Dr. Scott Holland, Dr. David Brown, and Dr. Pete Scheifele all provided immeasurable expertise and motivational support throughout my research and educational endeavors. I owe enormous gratitude to Dr. Scott Holland, who accepted me into this research project and invited me to share in his immense knowledge, and the opportunity of a lifetime for a doctoral student. Dr. Keith also served on my academic committee with Dr. Laura Kretschmer, both of whom have been instrumental in the development of my career and providing much needed words of encouragement since I was a Master’s student. Dr. Susan Stanton was the chair of my academic committee as well as an admired role model and mentor. Dr. Nancy Creaghead has made it possible for me to stay in this program over the years by providing me with assistance and opportunities, not only to remain financially stable throughout the program but

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also to develop my skills as an educator. Dr. Ernest Weiler, may he rest in peace, supervised my

Master’s thesis in my introductory research effort, and was a most wonderful educator and a motivational person for me.

I acknowledge the Cincinnati Children’s Hospital Medical Center departments of

Otolaryngology, Audiology, Radiology, and the Pediatric Neuroimaging Research Consortium for their participation and efforts toward my project. Additionally, I wish to thank all of my personal friends, my colleagues in the Audiology community, and my fellow doctoral students in

Communication Sciences and Disorders who reminded me why I chose this path and encouraged me to keep going, even in the face of adversity and personal challenges. Also deserving of an acknowledgement are those who gave me flexible employment throughout my studies, affording me a reasonable balance between work, school and family. Finally, I would like to thank the families of the parents who volunteered their time for their children to contribute to this very important scientific topic.

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TABLE OF CONTENTS Title Page i Abstract ii Acknowledgements vi Chapter One: Introduction 1 Purpose of the study 7 Specific Aims and Hypotheses 9 Chapter Two: Review of the Literature 11 Cochlear Physiology 11 Cochlear Pathology: Spiral ganglion degeneration 13 Central Auditory Nervous System: Development and deprivation effects 15 Animal models of electrical stimulation demonstrating age related plasticity 21 Effects of acoustical and electrical stimulation on the developing auditory system 24 Evoked potential studies of developmental plasticity in animals and humans 25 Auditory nerve, brainstem, and midbrain plasticity 30 Cortical plasticity 32 Acoustical stimulation in the hearing impaired auditory cortex 39 Speech and language measures of human auditory developmental plasticity 41 Neuroimaging studies of human auditory developmental plasticity 42 Magnetoencephalography 42 Positron Emission Tomography 44 Functional Magnetic Resonance Imaging 45 Sedation 47 Acoustic scanner noise 49 fMRI of the Auditory Cortex: Current findings 51 Cross-Modal Plasticity 56 Combination of fMRI with evoked potential measures 58 Conclusions 60 Chapter Three: Methods 62 Subjects 62 Inclusion criteria 62

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Exclusion criteria 63 Participant Characteristics 63 Subject Descriptions 65 Functional imaging protocol 65 Sedation 66 Instrumentation 67 Stimuli 67 Procedures 68 Data analysis 69 Auditory evoked potential recording protocol 71 Instrumentation 71 Stimuli 71 Procedures 72 Data analysis 73 Statistical analysis of evoked potential and fMRI data 74 Chapter Four: Results 77 Introduction 77 Auditory Evoked Potentials Results 77 Multiple Regression Analysis 81 fMRI Results 86 Comparison of fMRI and AEP Results 89 Chapter Five: Discussion 94 BOLD activation in the hearing-impaired toddler 95 Auditory pathways: brainstem to cortex interactions 97 Cross-modal interactions and plasticity 101 Limitations 103 Implications for future research 106 Conclusions 108 References 100 Appendices 141

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LIST OF FIGURES

Figure 1: Cerebral cortex showing auditory and language areas 16 Figure 2: Auditory pathways from Promenade around the Cochlea 27 Figure 3: Auditory Evoked Potential from Promenade around the Cochlea 28 Figure 4: P1 Latencies as a function of age in normal hearing children 32 Figure 5: P1 Latencies in 245 normal hearing children 33 Figure 6: Normal hearing, early and late implanted waveforms 35 Figure 7: Examples of P1 waveforms in normal and disordered 36 Figure 8: Coronal and Axial views of infant primary auditory cortex 48 Figure 9: Group maps of normal-hearing HUSH-fMRI data 52 Figure 10: Group maps of NH HUSH fMRI under sedation 52 Figure 11: Activation in hearing impaired infants 53 Figure 12: ROI defined for study 70 Figure 13a: Averaged waveforms for individual subjects 79 Figure 13b: Averaged waveforms for individual subjects 80 Figure 14: Correlation scatterplot for P1 Latency and duration HA use 82 Figure 15: Correlation scatterplot for P1 Latency and age at fitting 83 Figure 16: Group HUSH-fMRI activation for positive contrasts 87 Figure 17: Group HUSH-fMRI activation for negative contrasts 89 Figure 18: Correlation scatterplot for P1 latency and fMRI activation 90 Figure 19: Correlation scatterplot for P1 amplitude and fMRI activaton 91 Figure 20: Correlation maps between fMRI Activation and P1 latency 92 Figure 21: Correlation scatterplot for occipital activation and P1 latency 93

LIST OF TABLES

Table 1: Sample Characteristics 64 Table 2: Individual participant characteristics 65 Table 3: HUSH fMRI Paradigm 68 Table 4: Regression ANOVA table 84 Table 5: Pearson Correlations 86

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Chapter One: INTRODUCTION It has been estimated that approximately 60 newborns a day (1 to 6 infants per 1,000) are born in the United States with significant hearing loss (Bachmann & Arvedson, 1998; Cunningham &

Cox, 2003; Kemper & Downs, 2000; Northern, 1994). The effects of early hearing loss on communication development, as well as social and educational development are well documented (Davis, Elfenbein, Schum, & Bentler, 1986; Erenberg, Lemons, Sia, Trunkel, &

Ziring, 1999; JCIH, 2000; Moeller, Osberger, & Eccarius, 1986). A considerable body of evidence and literature now supports the benefit of early detection of congenital hearing loss and the concomitant implementation of early intervention strategies (Kileny, Zwolan, & Ashbaugh,

2001; Knott, 2001; MMWR, 2003; White, 2003; Yoshinaga-Itano, Sedey, Coulter, & Mehl,

1998).

Current research using behavioral techniques demonstrates that the development of language skills are significantly altered in hearing impaired children as compared with normal hearing children, documented using expressive and comprehension language samples, parent questionnaires and vocabulary checklists, and teacher rating scales (Hammes, et al., 2002;

Nicholas & Geers, 2006; Yoshinaga-Itano et al., 1998). Studies utilizing behavioral techniques such as an early head-turn response in normal-hearing infants have shown that sensitivity and preference to the characteristic sounds, stress patterns, and sequencing features of the native language appears as early as 6-9 months of age (Jusczyk, 2002). Substantial evidence indicates that exposure to auditory stimulation prior to 18 months or even 12 months of age is essential to normal central auditory maturation and language skill development (Colletti, et al., 2005;

McConkey Robbins, Koch, Osberger, Zimmerman-Phillips, & Kishon-Rabin, 2004; Sharma,

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Dorman et al., 2002a; Sharma, Dorman, & Spahr, 2002b; Sharma, et al., 2004; Waltzman &

Roland, 2005; Yoshinaga-Itano & Apuzzo, 1998).

Enrollment in early language and hearing services prior to three months of age has substantiated beneficial effects on the communication development of children with all degrees congenital hearing loss (Vohr, et al., 2008). With the advent of universal newborn hearing screenings in nearly all areas of the United States, the average age of diagnosis of congenital hearing impairment has now decreased to 3-6 months of age, thereby increasing the likelihood for appropriate and successful early intervention in these infants (Nelson, Bougatsos, & Nygren,

2008). The Year 2007 Position Statement of the Joint Committee on Infant Hearing is involved with improving the follow up and intervention standard of care in the United States (JCIH,

2007). Currently, efforts are underway for establishing uniform international standards for identifying congenital sensorineural hearing loss on a worldwide level (Olusanya, Somefun, &

Swanepoel de, 2008).

As with other neurocognitive systems, early auditory experience and biological circuitry interact to stimulate and support mutual development of structure and function (Kishon-Rabin, et al.,

2002; Moore, 2002). Animal studies using evoked excitatory synaptic potentials in single neurons and local field potentials support the idea that early auditory experience is necessary for normal maturation of synaptic plasticity mechanisms (Kotak, Breithaupt, & Sanes, 2007; Kral,

Tillein, Heid, Hartmann, & Klinke, 2005). Evidence of the concept of abnormal or delayed neuronal processes in input-deprived human auditory systems has also been observed using a variety of electrophysiology techniques, such as auditory brainstem response (Ray, Gibson, &

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Sanli, 2004), middle latency responses (Gordon, Papsin, & Harrison, 2005), and cortical potentials (Ponton, et al., 1996; Sharma, Martin et al., 2005); also with neuroimaging techniques such as positron emissions tomography (Naito, Okazawa, Honjo, Takahashi, et al., 1995), magnetoencephalography (Godey, et al., 2000), and functional MRI (Amaro, et al., 2002; Patel, et al., 2007b; Wilke, Holland, Myseros, Schmithorst, & Ball, 2003)

Cochlear implantation is an effective use of electrical stimulation to restore hearing in children with severe to profound sensorineural hearing loss (Geers, Nicholas, & Sedey, 2003; McConkey

Robbins et al., 2004; Sharma et al., 2004; Svirsky, Teoh, & Neuburger, 2004; Waltzman &

Cohen, 1998). As reported by the Food and Drug administration in 2005, nearly 150,000 individuals worldwide are users of cochlear implants, and many infants are now being implanted earlier than 12 months of age for exposure to auditory stimulation that is critical to development of spoken language (Colletti et al., 2005; House, 1976; Miyamoto, Houston, & Bergeson, 2005;

Sininger, Doyle, & Moore, 1999; Waltzman & Roland, 2005). Infants prior to the minimum surgical age required for implantation may be fitted with hearing aid amplification in order to stimulate the auditory system acoustically, as early as two or three months of age in many circumstances. The last few decades have advanced the development of microelectronics and auditory prostheses that acoustically or electrically stimulate the auditory nerve and brainstem are now considered safe, efficient, and effective for widespread use.

Outcome studies and comparisons with hearing aid users have established that electrical stimulation via cochlear implantation can produce successful communication benefit, particularly improved speech understanding, even in children with significant residual hearing (Cullen, et al.,

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2004; Dettman, et al., 2004; House, Berliner, Eisenberg, Edgerton, & Thielemeir, 1981). The application of cochlear implants has been extended to include children with poor open-set sentence recognition and/or pure tone averages (PTA) ranging from 70-100 dBHL (House et al.,

1981; Winton, Hollow, & Dettmen, 2002). An impetus for consideration of children with significant residual hearing for implantation arose from the sizable proportion of such children not progressing with their hearing aids at the same rate as those with implants (Dettman et al.,

2004; Skinner, Holden, & Binzer, 1994).

Although many of the initial problems of electric hearing have been resolved, in order to continue its perfection, several anatomical and functional concerns relevant to the design of cochlear implants must be understood and addressed. A major clinical dilemma lies in predicting the likelihood of substantial communication benefit from cochlear implantation in infants and children with residual hearing. Rehabilitation and candidacy issues arise due to large individual variability and poor performance outcome in some users. Current challenges include electrode insertion depth, the response of the central auditory system to chronic electrical stimulation, the restoration of normal frequency resolution and pitch sensation, establishment of the optimum number of functional channels, and development of advanced objective diagnostic tools for assessment of auditory cortical function and prognostic cochlear implant outcome prediction.

Auditory evoked potentials have provided substantial insight about the deleterious effects of age related plasticity and sensory deprivation on the developing auditory system. Due to the likelihood that these degenerative effects would interfere with the effectiveness of the implant, it

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is important to determine the extent of the alterations to the development and plasticity of the central auditory system when considering the decision of when to implant. The P1 component of the auditory evoked potential response is a reflection of neuronal activity from thalamic and cortical sources representing the sum of synaptic transmission from peripheral to central auditory pathways (Kraus, et al., 1993), and exhibits predictable changes in latency and morphological patterns with increasing durations of hearing loss and subsequent implant use (Singh, Liasis,

Rajput, Towell, & Luxon, 2004).

In several prior studies, the latency of the P1 auditory evoked potential has been described as a biological marker for auditory system maturation, since it reliably varies as a function of chronological age, auditory system status, duration of deafness, and duration of stimulation

(Ceponiene, Cheour, & Naatanen, 1998; Ponton, Don, Eggermont, Waring, & Masuda, 1996;

Sharma, Martin et al., 2005). In this sense, the P1 latency can be used to infer the maturational status of hearing impaired or implanted children. In addition, several morphological classifications have been noted which appear suggestive of various stages of auditory system development. Poor waveform morphology or a polyphonic, double-peaked waveform shape has been shown in cases where initial responses are developing in an auditory system in which stimulation has been delayed for a longer duration (Sharma & Dorman, 2006).

In spite of the advancement of cochlear implantation and techniques for outcome assessment, the exact nature of higher auditory cortical processing and perception in the congenitally deaf auditory nervous system is not well characterized by the battery of instrumentation traditionally utilized. An objective and minimally invasive tool that assists in describing central auditory

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system function and ultimately in determining potential speech perception benefit from cochlear implantation is highly desirable. Functional neuroimaging techniques may be useful in evaluation of central auditory function in children that are cochlear implant candidates.

Specifically, fMRI may permit differentiation of brain responses corresponding to auditory detection, speech perception and language processing in normal and hearing-impaired infants.

The ability of fMRI to demonstrate cortical representation of auditory perception may provide important information regarding various aspects of auditory and language processing in both normal-hearing and hearing impaired infants and toddlers (Wilke et al., 2003).

Significant changes in the organization of auditory cortical response patterns have been observed using fMRI in deaf adults after long-term use of hearing aid amplification (Hwang, Wu, Chen, &

Liu, 2006). Non-invasive assessment of the cortical response to sound input in an infant who is unable to respond reliably to behavioral auditory system assessment is important for accurate decision making in the cochlear implant staging process. fMRI has the potential to provide an advanced objective diagnostic tool to clinicians with capabilities to be used in conjunction with auditory evoked potential assessment (Scarff, et al., 2004), as this would combine spatial and temporal information to provide further evidence that a stimulus is reaching the auditory cortex via the cochlear nerve pathways (Schmidt, et al., 2003).

fMRI evaluation offers a possible means of objective assessment of auditory processing as well as the general state of the central auditory nervous system pathways for both normal hearing and hearing impaired populations. This tool could prove to be especially useful in advancing our understanding of the degenerative effects of sensory deprivation on central auditory maturation.

Due to the relationship between neuronal and hemodynamic events, use of cortical auditory

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evoked potentials may be of assistance in identifying functional brain imaging patterns observed in hearing impaired toddlers, specifically the P1 evoked potential response latency, amplitude, and waveform morphology. Further development of fMRI as a means of clinical evaluation may ultimately aid in the development of early intervention and management strategies for hearing impairment.

Purpose of the Study

The purpose of this study is to examine and compare cortical responses to speech stimuli in hearing impaired toddlers using fMRI and the P1 auditory evoked potential. Auditory BOLD activation is identified and described in relationship to the P1 latency and amplitude as well as patient characteristics such as subject age. Furthermore, issues pertaining to use of amplification, functional aided hearing, and auditory skills development as well as language abilities are illustrated in order to more fully characterize the auditory experience of the subjects in our sample.

The following research questions were developed to assess a possible relationship between neuronal firing and BOLD activity at the primary auditory cortical level. Additional relationships between these measures and hearing aid use and outcomes are also considered. This exploratory study may identify predictive patterns of neuronal to vascular activity within the hearing-impaired central auditory nervous system prior to cochlear implantation.

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Research Question 1

Is P1 latency in severe to profoundly hearing impaired toddlers influenced by the age at which they were fitted with hearing instruments?

Research Question 2

Is P1 latency in severe to profoundly hearing impaired toddlers influenced by the duration of hearing instrument use?

Research Question 3

Is there a relationship between characteristics of the P1 auditory evoked potential response and residual auditory cortical function as shown by fMRI activation maps in severe to profoundly hearing impaired subjects?

Research Question 4

Is there evidence of cross-modal plasticity in children with enlarged or robust P1 positivity?

Specific aims and hypotheses

General Aim

The goal of the present research is to describe auditory BOLD activation in relationship to the P1 auditory evoked potential response and hearing aid use and outcomes in severe to profoundly hearing impaired subjects.

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Specific Aims

1. Investigate the relationship between P1 auditory evoked potentials and auditory

sensory experience with hearing aid amplification in infants and toddlers with severe

to profound sensorineural hearing loss.

2. Evaluate residual auditory cortical function in this population as shown by fMRI

activation maps using speech stimuli.

3. Describe relationships observed between fMRI activity and P1 response

characteristics.

Hypotheses

Hypothesis 1: There will be a significant relationship between P1 latency and duration of

auditory experience or hearing aid use in infants with severe to profound sensorineural

hearing loss.

Hypothesis 2: There will be a significant relationship between P1 latency and the age of hearing

aid fitting in infants with severe to profound sensorineural hearing loss.

Hypothesis 3: Hearing-impaired toddlers with absent or significantly delayed P1 latencies will

exhibit auditory fMRI BOLD activation patterns that deviate significantly from those

with normal or expected P1 latency values.

Hypothesis 4: A significant relationship will be observed between characteristics of the P1

response and the number of activated pixels in A1 auditory cortex, as well as activated

pixels outside of auditory regions.

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In order to test these research hypotheses we will collect data and perform statistical tests aimed at validating the null hypotheses as stated below. If these hypotheses cannot be validated then we can infer that our research hypotheses are true.

Null Hypothesis 1: There will be no significant relationship between P1 latency and duration of

auditory experience or hearing aid use in infants with severe to profound sensorineural

hearing loss.

Null Hypothesis 2: There will be no significant relationship between P1 latency and the age of

hearing aid fitting in infants with severe to profound sensorineural hearing loss.

Null Hypothesis 3: Hearing-impaired toddlers with absent or significantly delayed P1 latencies

will exhibit auditory fMRI BOLD activation patterns that do not deviate significantly

from those with normal or expected P1 latency values.

Null Hypothesis 4: No significant relationship will be observed between characteristics of the P1

response and the number of activated pixels in A1 auditory cortex, or activated pixels

outside of auditory regions.

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Chapter Two: REVIEW OF THE LITERATURE

In order to fully understand the relationships involved in central auditory system function, it is also necessary to understand the peripheral sensory processing and functional networks involved in transducing and transmitting acoustic sounds in the external environment into a meaningful message that can be interpreted and understood by the brain. In cases of auditory sensory deprivation such as sensorineural hearing loss, the encoding of sensory input is dramatically different in the periphery, resulting in disordered input to the central auditory system that is not

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only reduced, but also distorted with poor frequency resolution. Our brains adapt to sensory experience both structurally and functionally, therefore it is important to understand the implications of such deprivation globally throughout the entire auditory system, from cochlea to cortex.

Cochlear physiology

A network of nerves forming the peripheral nervous system accomplishes communication between the sensory organs of hearing and the central nervous system. The inner ear is innervated by the cochlear component of the VIIIth cranial nerve, which travels from the cochleovestibular mechanism to the cochlear nucleus in the midbrain. This pathway contains both ascending (afferent) and descending (efferent) tracts to transmit messages to and from the higher auditory centers of the brain. In humans, approximately 3500 cochlear inner hair cells, or

25% of the total hair cell population, are innervated by 90-95% of the total afferent neuron population of about 30,000 (Jahn & Santos-Sacchi, 2001; Roeser, Valente, & Hosford-Dunn,

2000).

The individual nerve fibers that make up the auditory nerve have bodies that are contained as a group within the modiolus, innervating the organ of Corti via small openings called the habenulae perforata. In the peripheral nervous system, a collection of cell bodies is called a ganglion. The spiral ganglion is contained within Rosenthal’s canal, a spiral channel within the bone of the modiolus. Rosenthal’s canal travels parallel to the line of inner hair cells, each one innervated by its own sector of tonotopically organized bipolar spiral ganglion neurons (Jahn &

Santos-Sacchi, 2001; Roeser et al., 2000).

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In the normal auditory system, the inner hair cell transmits information about incoming acoustic signals by releasing the excitatory neurotransmitter glutamate. As part of the receptor organ, hair cells rest on a basilar membrane and connect to one another by tight junctions. Because they are epithelial cells, they do not have axons or dendrites. Instead, hair cells make synapses onto afferent nerve fibers of the eighth cranial nerve and also receive efferent synaptic contacts from axons originating in the brainstem. Receptor potential changes within the inner hair cell adjust glutamate release, generating action potentials within the nerve fiber. Thus, the inner hair cell is a specialized epithelial cell that excites the sensory neurons of the spiral ganglion by synaptic transmission (Jahn & Santos-Sacchi, 2001).

The membrane potential changes associated with movement of the hair cell stereocilia results in alteration of the discharges of eighth nerve afferent innervation connected at the hair cell base.

In order for synaptic transmission from the hair cells to the neurons to be possible, afferent axons must have contact via peripheral processes, or dendrites, of bipolar neurons in the spiral ganglion

(McFadden, Ding, Jiang, & Salvi, 2004). From this location, the central processes of the 30,000 spiral ganglion neurons form the acoustic branch of cranial nerve VIII and project to synapse on cells within the cochlear nucleus in the brainstem.

Cochlear pathology: Spiral ganglion degeneration

A significant decline in hearing acuity is likely to occur when hair cells are lost to ototoxicity, noise, or other cochlear insult. Interruption of the incoming auditory signal pathway at the cochlear level typically results in significant loss of hair cell function and eventual degeneration

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of spiral ganglion neurons (McFadden et al., 2004; Snyder, Sinex, McGee, & Walsh, 2000;

Staecker, Gabaizadeh, Federoff, & Van De Water, 1998; Stankovic, et al., 2004; Suzuka &

Schuknecht, 1988). Histological evidence has long established that the survival of spiral ganglion neurons is reliant on the integrity of the hair cells with which they make synaptic contact(Suzuka & Schuknecht, 1988). In fact, synaptic contact between both peripheral (hair cell) and central (cochlear nucleus) targets is necessary for spiral ganglion neurons to survive

(Hartmann, Topp, & Klinke, 1984; Shepherd & Javel, 1997; Tan & Shepherd, 2006). As many as four types of neurotrophins possess some survival action on the nervous tissue, carrying dozens of different essential amino acids to spiral ganglion cell bodies (Ernfors, Duan, ElShamy,

& Canlon, 1996; Fritzsch, Tessarollo, Coppola, & Reichardt, 2004). The severance of contact with hair cells and supporting cells induces a deprivation of neurotrophins, which are vital proteins involved in neuronal nourishment and growth (Tan & Shepherd, 2006).

Contingent upon timing and site of expression, the interaction between neurotrophins and their receptors either protect neurons from apoptosis or conversely, promote this naturally occurring programmed death cycle (Duan, Agerman, Ernfors, & Canlon, 2000; Staecker et al., 1998;

Stankovic et al., 2004) In the presence of cochlear insult resulting in complete destruction of all hair cells, a number of spiral ganglion neurons may subsist while awaiting signals from neurotrophin receptors (Duan et al., 2000; McFadden et al., 2004). The activities of neurotrophins and their receptor pathways, which are dependent on signals from effective hair cell function, are instrumental in propagation of the life cycle of a spiral ganglion cell body(Ernfors et al., 1996; Fritzsch, Pirvola, & Ylikoski, 1999).

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Examples of pathological insult that may result in the anatomic disruption of the inner hair cell base from the dendrites of the afferent spiral ganglion neuron include drug exposure, hypoxia, metabolic abnormalities, noise trauma, and various types of mass lesions or tumors involving the brainstem. The consequence of these insults is likely to indicate significant sensorineural hearing impairment and communication difficulties that require intervention strategies dependent upon spiral ganglion cell survival. Spiral ganglion cell counts are particularly low in cases of congenital sensorineural hearing loss (Nadol, 1997). SGN degeneration has additionally been implicated in changes in the frequency tuning of the inferior colliculus in the brainstem (Sumner,

Scholes, & Snyder, 2008).

The relationships between these pathologies and the fate of spiral ganglion neurons are dependent upon interactions of neurotrophins with their receptors (Fritzsch et al., 2004;

Stankovic et al., 2004). Evidence exists that infusion of neurotrophins and antioxidants into the scala tympani of the cochlea contributed to preservation of surviving SGN bodies in deafened guinea pigs (Maruyama, Miller, & Ulfendahl, 2008; Richardson, O'Leary, Wise, Hardman, &

Clark, 2005). Additionally, evidence in animals has suggested that following administration of neurotrophic therapy, SGN survival can be further enhanced by electrical stimulation to the scala tympani (Shepherd, Coco, & Epp, 2008). Spiral ganglion neurons are the target location for cochlear implants, therefore prevention of the degenerative process associated with cochlear malfunction is likely to enhance intervention outcome (Gallo & Letourneau, 2000; Li, Parkins, &

Webster, 1999; Nadol, Young, & Glynn, 1989; Zheng, Stewart, & Gao, 1995). Consideration of this process of neural degeneration is an important element of understanding sensorineural hearing loss and devising intervention strategies.

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Central auditory nervous system: Development and deprivation effects

The central auditory nervous system is comprised of neural circuits responsible for representing sounds with sufficient detail to support behavioral detection and discrimination. Spiral ganglion neurons connect to pathways of independently functioning and narrowly tunes cochlear nerve fibers that are tonotopically tuned to the characteristic frequency of the hair cell to which it is connected (Snyder & Leake, 1997). Frequency representation is maintained throughout several redundant processing and relay stages as the axon of each cochlear nerve cell bifurcates and penetrates anterior, posteroventral, and dorsal cochlear nucleus areas in an orderly fashion

(Webster, 1999). Cochlear axonal outflow disseminated through this region is then routed into a pathway of several bilateral brainstem nuclei, including the medial and lateral superior olivary nuclei, the dorsal nuclei of the lateral lemniscus, the inferior colliculus, and medial geniculate body (Jahn & Santos-Sacchi, 2001; Katz, Burkard, & Medwetsky, 2002).

The medial geniculate body is the auditory portion of the diencephalon of the forebrain and projects through the sublenticular internal capsule onto primary auditory cortical and thalamic areas, which contain strips or layers of tonotopically tuned regions. The areas of the temporal lobe involved in processing of auditory signals are called the transverse gyri of Heschyl

(Brodmann’s ares 41 and 42) and include middle, ventral and posterior Ectosylvian areas, the

Sylvian fringe area, the anterior auditory field, and the insular area, also extending partially onto the planum temporale (Webster, 1999). Areas 41 and 42 are both considered primary auditory cortex, although the neuronal structure of area 42 more closely resembles that of an association cortex, with several layers of highly developed neuron types. The tonotopic maps expressed here represent system preservation of the “place” code developed in peripheral locations. Responses

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to temporal and spatial cues such as interaural time and level differences are initiated in brainstem nuclei and preserved throughout cortical areas in an interdependent manner (See

Gelfand, 2004 for review).

Specific auditory information necessary for interpretation and discrimination of various types of sounds, including speech, is processed by areas 41 and 42, or the primary auditory cortex, and subsequently passed on to Brodmann’s area 22 (Wernicke’s area), or the association auditory cortex, the area responsible for normal speech perception. This area occupies the posterior two- thirds of the superior temporal gyrus and the planum temporale. The arcuate fasciculus then connects area 22 with areas 44 and 45, the area triangularis (Broca’s area), and the prefrontal cortex, which work together to process motor speech signals for expressive speech function

(Bhatnagar, 2002).

FIGURE 1: Cerebral cortex showing auditory and language areas Aqua: Broca’s Area (BA44), Magenta: Primary Auditory (BA41) Orange: Wernicke’s Area (BA22), Chartreuse: Primary Visual (BA17)

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Embryological brain development produces about twice the number of neurons that are actually needed to generate a physiologically relevant network. In conjunction with the naturally programmed cell death or apoptosis that must occur to remove excess neurons beyond the formative stages, stimulation is vital to proper formation of neural structures (Kral, Hartmann,

Tillein, Heid, & Klinke, 2002; Leake, Hradek, Chair, & Snyder, 2006; Moore, Palmer, Hall, &

Sumner, 2007; Ponton, Moore, & Eggermont, 1999; Russell & Moore, 1995). In this sense, adequate stimulation is necessary for normal cortical growth, adaptation, and development, as the nervous system continues to remodel and change throughout all developmental stages in response to environmental influences and genetically preprogrammed events.

In the human brain and nervous system, neuron migration, cell proliferation, and synapse formation are all very active from birth through three years of age, with myelinization and development of cellular insulation around nerve fibers continuing in a layer-specific pattern for at least 10 years and possibly into adulthood (Eggermont & Ponton, 2003; Moore, Ponton,

Eggermont, Wu, & Huang, 1996; Ponton, Eggermont, Khosla, Kwong, & Don, 2002; Ponton,

Don, Eggermont, Waring, & Masuda, 1996; Ponton, Eggermont, Kwong, & Don, 2000). Based on this information regarding the time course of structural auditory system growth, it is useful to have some idea of the stage of cortical maturation of a child’s developing auditory system in selecting an appropriate time for intervention.

When auditory deprivation at the cochlear level occurs during critical stages of neurological development, the central auditory system is not receiving adequate stimulation, which in turn arrests the normal developmental course and reduces synaptic activity within auditory-specific

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areas (Forster & Illing, 2000; Illing, Forster, & Horvath, 1997; Kral, Hartmann, Tillein, Heid, &

Klinke, 2000). The implications of this effect are more severe than what is expected with the initial stages of simple auditory deprivation that is exclusively conductive, such as plugged ears, which depending on extent and severity of the loss my not always lead to degeneration of the cochlear nerve in spite of slight reorganization of brainstem and cortical connectivity (Moore,

Hutchings, King, & Kowalchuk, 1989). Sensory deprivation related to hair cell death that eventually leads to neural atrophy initiates permanent degenerative changes in neuronal structure, function, and organization at all levels of the auditory system pathway (Nadol et al.,

1989; Russell & Moore, 1995; White, Burgess, Hall, & Nadol, 2000; Zimmermann, Burgess, &

Nadol, 1995).

A variety of information regarding the effects of sensory deprivation on peripheral and central nervous system maturation for auditory, visual, and somatosensory modalities has also been supported in animal models. Anatomical studies of the cochlea and auditory nerve have used techniques including cytocochleograms, neuronal counts, and volume and density estimations using light microscopy and scanning electron microscopy. Anatomical and functional changes within the cochlea as a result of loss of neurotrophins support include progressive demyelinization of spiral ganglion neurons, loss of peripheral processes, and deterioration of their somata (Ryugo, Rosenbaum, Kim, Niparko, & Saada, 1998; White et al., 2000;

Zimmermann et al., 1995). In turn, the central auditory nervous system response to these changes includes a reduction in the volume of the cochlear nuclei, shrinkage or loss of auditory brainstem neurons, reduction in synaptic density within the inferior colliculus, and degradation in

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temporal resolution and spatial selectivity (Saada, Niparko, & Ryugo, 1996; Shepherd & Hardie,

2001; Snyder, Sinex et al., 2000).

Spiral ganglion degeneration has been shown in neonatally deafened cats, as SGN cell densities were shown to be significantly greater when studied at earlier stages of development as compared to those studied at greater than 2.5 years (Hultcrantz, Snyder, Rebscher, & Leake,

1991; Rebscher, Snyder, & Leake, 2001). Furthermore, longer periods of deafness are known to significantly impact the efficacy of signal propagation and neural conduction times along the auditory nervous system pathways, as measured by various evoked potential latencies in both animals and humans (Bauer, Sharma, Martin, & Dorman, 2006; Dorman, Sharma, Gilley,

Martin, & Roland, 2007; Eggermont & Ponton, 2003; Ponton, Don, Eggermont, Waring, Kwong et al., 1996; Ponton & Eggermont, 2001; Ponton, et al., 2000; Ponton et al., 1999; Ponton, et al.,

2001; Sharma, Dorman, Spahr, & Todd, 2002).

Depending on extent and severity, cochlear hair cell loss is known to create a more broadly tuned tonotopic neural response pattern within the auditory cortical centers. Demonstrated in neonatally deafened cats and chinchilla, auditory deprivation typically results in a significant reduction of the size of the cochlear nucleus(Saada et al., 1996), with a spatial distribution of hair cell loss which corresponds with spiral ganglion loss and structural abnormalities of endbulbs and synapses within the cochlear nucleus (Ryugo et al., 1998). In addition, a limited topographic specificity is displayed across the entire auditory system, as the afferent SGN to CN projections and inferior colliculus are degraded in frequency resolution, particularly in neonatally deafened animals as compared to adults (Harrison, Ibrahim, & Mount, 1998; Harrison, Stanton, Nagasawa,

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Ibrahim, & Mount, 1993; Leake et al., 2006; Stanton & Harrison, 2000). Even in cases of frequency limited cochlear loss, a significant reorganization of tonotopic map representation is observed in the form of expanded cortical representation of functional cochlear regions (Rajan,

Irvine, Wise, & Heil, 1993; Robertson & Irvine, 1989).

The cause and duration of hearing loss have been shown to have the single greatest influence in spiral ganglion survival based on cell count, with congenital and genetic causes producing the greatest loss of SGN function, as compared to acquired or ototoxic causes (Nadol et al., 1989).

Several experiments demonstrate that following cochlear hair cell loss, a critical survival period exists, during which function of spiral ganglion neurons may be salvaged by controlling the behavior of neurotrophins and their receptors (Gallo & Letourneau, 2000; Zheng et al., 1995).

Additionally, chronic electrical stimulation of the auditory nerve is an important consideration in spiral ganglion survival with implications relevant to cochlear implantation (Leake, Snyder,

Hradek, & Rebscher, 1995). Possibilities have been investigated for treatments using nerve growth factor therapy in combination with electrical stimulation to aid in survival of spiral ganglion neurons(Gillespie & Shepherd, 2005; Shepherd et al., 2008; Shepherd, Coco, Epp, &

Crook, 2005).

Animal models of auditory system stimulation demonstrating age related plasticity

Animal studies of the effects of chronic electrical stimulation of the auditory system may promote the survival of SGNs, or possibly prevent or delay their degeneration that occurs with loss of neurotrophic support from hair cells (Hartshorn, Miller, & Altschuler, 1991; Lousteau,

1987; Miller, 2001). Atrophy or shrinkage of SGN cell density typically seen with auditory

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deprivation is either stopped or reversed with the application of stimulating electrodes over large regions of the cochlea, although conflicting results and differing methodologies among experiments have made findings difficult to interpret, with many questions about whether or not cochlear implants promote actual trophic support or simply morphological anatomical cellular changes (Araki, et al., 1998; Li et al., 1999). Methodological questions that have been raised involve duration of stimulation and electrode configuration.

Findings from many studies indicate that in animals deafened early in life, electrical stimulation can induce significant functional plasticity and reorganization within all levels of the auditory nervous system. Decreased SGN cell density has been associated with cochlear nucleus size reduction (Leake et al., 2006), as well as altered temporal resolution and longer evoked potential response latencies in the central nucleus of the inferior colliculus (Vollmer, Leake, Beitel,

Rebscher, & Snyder, 2005). Chronic electrical stimulation in neonatally deafened cats has been shown to reverse the degradation of temporal resolution typically seen in the midbrain resulting from long term deafness (Lustig, Leake, Snyder, & Rebscher, 1994; Snyder, et al., 2000).

Accurate reproduction of the temporal and frequency coding of sound using electrical stimulation has been the key consideration in the development of cochlear implant speech processing strategies for cochlear implants. According to frequency tuning curve studies of auditory nerve fibers at various stages of the developing cat auditory system, frequency selectivity appears to be established neonatally in spite of deafness but does not maintain tonotopicity in long-term deprivation (Raggio & Schreiner, 2003). The presence of sensitive periods in the brainstem is not supported, as electrical stimulation is known to facilitate the same

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expansions of frequency responsivity and increased metabolic activity in the inferior colliculus in adult cats as in kittens (Moore, Vollmer, Leake, Snyder, & Rebscher, 2002; Seldon, Kawano, &

Clark, 1996; Snyder, Rebscher, Cao, Leake, & Kelly, 1990). However, in neonatally deafened animals that receive electrical inputs, significant changes are seen in spatial representations and frequency organization maps, including an expansion of cortical areas activated by the implant

(Klinke, Kral, Heid, Tillein, & Hartmann, 1999; Leake, Snyder, Rebscher, Moore, & Vollmer,

2000), although this effect is reduced with the use of an adjacent multiple bipolar electrode configuration.

Animal models investigating the effects of electrical stimulation on functional and damaged cochleae show that electrophysiologic responses to any electrical stimulus differed considerably in amplitude and latency in both deaf and hearing cats as compared to each other and to responses from the corresponding acoustic stimuli in hearing cats (Popelar, Hartmann, Syka, &

Klinke, 1995; Shepherd & Javel, 1997). Auditory deprivation is known to decrease the middle latency response (MLR) input/output function in guinea pigs (Jyung, Miller, & Cannon, 1989).

In the deafened guinea pig auditory system, electrical stimulation was correlated with metabolically induced SGN survival as well as an input/output relationship between MLR amplitude and electrical current levels (Hartshorn et al., 1991). Similar results were seen in cats implanted with different configurations of a multiple channel cochlear implant which yielded input-dependent variations in amplitude, latency, and slope of the electrically evoked MLR when recorded from well-defined tonotopically specific areas (Popelar et al., 1995). Normal hearing cats exhibited similar latency, amplitude and slope responses to both electrically and acoustically

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evoked middle latency responses for high frequency inputs and low intensity electrical stimulation.

In support of an age-related plasticity of the developing auditory system, congenitally deaf white cats were shown to have a developmental plasticity of cortical areas as a result of cochlear implantation only if installed prior to 6 months of age (Kral, Hartmann, Tillein, Heid, & Klinke,

2001). This study suggested that electrical stimulation of the cat cochlea, if performed during sensitive periods of development, leads to synaptic activation of cortical layers that becomes similar to that of normal hearing cats, expressed as higher amplitude middle latency responses and the emergence of long latency responses (Klinke et al., 1999). In addition, long latency responses were developed in the primary auditory cortex of auditory-deprived normal hearing cats in response to both acoustic and electric stimuli (Kral et al., 2001). Maturation of cortical auditory evoked potential responses reflects development of higher order auditory areas and is crucially important for development of wider auditory cognitive function.

Effects of acoustical and electrical stimulation on the developing auditory system

Stimulation of the auditory system has been used to augment or restore human sensorineural hearing function in the form of cochlear implants for more than 30 years (Ballantyne, Evans, &

Morrison, 1978; House, 1976; House et al., 1981; Ponton, Don, Eggermont, Waring, Kwong et al., 1996). The advent of the multiple channel devices in the 1980’s made useful hearing possible in cases of severe to profound deafness due to cochlear dysfunction or malformation. A cochlear implant effectively stimulates the auditory pathways with electrical pulses, which promote unique developmental changes in auditory neurons throughout the central nervous system due to both normal and abnormal processes. The stimulation provided by a hearing aid

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or cochlear implant during critical periods of neural development may facilitate SGN survival and a more functional maturation of the central auditory system pathways (Eggermont, Ponton,

Don, Waring, & Kwong, 1997; Sharma, Dorman, Spahr et al., 2002)

Spiral ganglion neuron survival is dependent upon neurotrophic signals and support from hair cells and supporting cells of the organ of Corti (Shepherd et al., 2005; Stankovic et al., 2004).

Several studies, however, have suggested that electrical stimulation does not necessarily promote

SGN cell growth or rejuvenation the way a neurotrophin would, but rather prevents the reduction in SGN cell size, packing density and diameter that typically results from hair cell loss and spiral ganglion degeneration originating from prolonged auditory deprivation (Araki et al., 1998; Li et al., 1999; Shepherd, Matsushima, Martin, & Clark, 1994). Direct chronic electrical stimulation of hair cells can assist with sustaining surviving SGNs within the deafened cochlea (Hartshorn et al., 1991; Leake, Hradek, & Snyder, 1999; Lousteau, 1987; Mitchell, et al., 1997). Electrical stimulation also helps to preserve or restore a more normal morphology in SGNs by preventing demyelinization (Leake et al., 1995).

It is commonly accepted that at least a minimal number of surviving SGNs are required for successful speech understanding with a cochlear implant. Better acoustic thresholds have been significantly correlated with higher SGN counts, suggesting that patients with better residual hearing may have a larger number of accessible functioning SGNs (Incesulu & Nadol, 1998). In turn, a higher maximum potential benefit for speech understanding may be possible than for patients with higher thresholds or no residual hearing. Despite loss of residual hearing upon implantation resulting from mechanical insertion trauma, only a slight decrease in SGN counts is

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observed in implanted ears versus non-implanted ears (Khan, Handzel, Damian, Eddington, &

Nadol, 2005). Furthermore, the SGN loss noted in implanted ears is predominantly within the unstimulated apical segment to which the implant electrode does not typically extend. This may be an implication that many SGNs in the basal half of the cochlea, the site of implant array insertion, are sustained by electrical stimulation from the implant.

Although much emphasis is placed on surgical and programming aspects, it is becoming evident that success with a cochlear implant entails considerations that extend well beyond the device itself. In order to restore speech comprehension by prosthetically stimulating the auditory periphery, all patient-specific anatomical and functional features must be considered (Parkins,

1985). Producing an accurate representation of the place and temporal coding of the frequency of sound with electrical stimulation is of fundamental importance in developing speech processing strategies for cochlear implants.

An important aspect of spiral ganglion loss and neuron shrinkage is the corresponding reduction of both neuronal (Javel & Shepherd, 2000; Parkins & Colombo, 1987) and psychophysical

(Zeng, Popper, & Fay, 2004) dynamic ranges, which require compression to be introduced into the processing scheme for normal loudness perception. Pitch perception issues are influenced by depth of insertion greater than 20 mm, since stimulation of the apical segment of the cochlea and closer to the medial wall is theorized to provide greater frequency selectivity and less crosstalk between electrodes. Models of electrical stimulation of auditory nerve fibers are important in determining ways in which to improve the signal processing technology in cochlear implants for the maximum potential sound quality and speech recognition for the patient.

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In spite of apparent advantages to electrical stimulation of the hearing impaired auditory system, it is imperative to know how constant stimulation will affect the nerve function and transmission of information to the cochlear implant patient. Within the cochlea, excess bone growth within the scala tympani and a decrease in the volume of Rosenthal’s canal has been observed (Li et al.,

1999; Nadol & Eddington, 2006) In the central nervous system, functional consequences of electrical stimulation have been theorized to include alterations in tonotopic organization of the midbrain and temporal response properties of the inferior colliculus (Lustig et al., 1994). Great variability exists in the available data regarding the effects of prolonged electrical auditory nerve stimulation. Future research is needed to determine the appropriate mode, type, and duration of stimuli and the specific electrical parameters required to balance the protective outcome and negative effects.

Evoked Potential Studies of developmental plasticity in animals and humans

Auditory evoked potentials (AEP) are a subclass of event-related potentials (ERP), which are neuronal responses time-locked to some "event". The event is typically a sensory stimulus such as a visual flash, an auditory sound, a mental event such as target recognition, or the omission of a stimulus such as an increased time gap between stimuli. Auditory evoked potentials are very small electrical voltage potentials originating from the bursting activity of large populations of neurons along the nervous system pathway from the cochlea to the cortex, and are recorded from the scalp in response to an auditory stimulus, such as clicks, pure tone pips or bursts, or speech sounds.

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The P1 auditory evoked potential, which is the measure of interest in this study, is generated within thalamocortical projections and primary auditory cortex(Sharma, Kraus, McGee, & Nicol, 1997) .

FIGURE 2: drawing by P. Minary, S. Blatrix, from "Promenade around the cochlea" http://www.cochlea.org, EDU website by R Pujol et al INSERM and University Montpellier. http://www.neuroreille.com/promenade/english/audiometry/ex_ptw/explo_ptw.htm

Several components of the auditory evoked potential response can be recorded from the top of the head, originating from structures within the brain, such as the auditory cortex, the auditory brainstem structures, the auditory VIIIth cranial nerve. These responses carry a low electrical voltage ranging from 2-10 microvolts for cortical responses to less than 1 microvolt from the deeper brainstem structures. Highly sensitive amplifiers and computer averaging equipment coupled with a set of specifically tuned filters helps to compensate for the low voltage and relatively high background electrical noise generated when recording these responses. A computer generated signal averaged waveform is then evaluated based on several parameters, such as response latency or time-course, amplitude or magnitude of the response, and waveform morphology.

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FIGURE 3: drawing by P. Minary, S. Blatrix, from "Promenade around the cochlea" http://www.cochlea.org, EDU website by R Pujol et al INSERM and University Montpellier. http://www.neuroreille.com/promenade/english/audiometry/ex_ptw/explo_ptw.htm

Longitudinal studies of auditory evoked potentials (AEP) have demonstrated predictable shifts in response latency and morphology with chronological age, and indicate that the time course for the most sensitive maturational periods of human auditory brain development continues until around the age of 12 years (Ponton, Eggermont, Kwong et al., 2000; Ponton et al., 1999).

Auditory development and central auditory activity in severe to profound sensorineural hearing loss after cochlear implantation has been investigated using a variety of techniques. Studies using both near and far-field auditory evoked potentials have provided a description of multiple level auditory system responses to electrical stimulation.

The focus of AEP testing in cochlear implant users has been to identify changes in the developmental plasticity of the system in response to long and short term deafness, duration and age of onset, and reaction to stimulation using evoked potential techniques such as Auditory

Brainstem Response (ABR), Middle Latency Response (MLR), Mismatch Negativity (MMN), and P1 latencies (Eggermont & Ponton, 2003; Gordon, Papsin, & Harrison, 2006; Harrison, et al., 1993; Ponton, Don, Eggermont, Waring, Kwong et al., 1996; Ponton, Eggermont, Don et al.,

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2000; Sharma, Martin et al., 2005). Speech perception in hearing aid and cochlear implant users is highly variable between users and appears to be dependent on auditory pathway encoding and neuron survival and synchronous function (Hall, 1990). Evoked potentials provide possibilities for evaluating critical components of synchronous neural encoding, auditory pathway responses at various stages of development and relationships with variability in speech perception in cochlear implant users.

The overwhelming majority of data involving human subjects has corroborated with parallel animal models regarding age related plasticity of the auditory system. One common finding is that stimulation must be delivered to a developing sensory system within a narrow window of time, or a sensitive period, in order for normal development to occur (Kral et al., 2002; Kral et al., 2005). Auditory input delivered by a cochlear implant activates a normalization of responses from the auditory cortex in humans (Ponton & Eggermont, 2001; Sharma, Dorman, Spahr et al.,

2002). Subjects who are congenitally deaf and have been provided with hearing aids or cochlear implants at various ages offer an ideal opportunity to study age related plasticity and critical periods during human auditory development.

Auditory nerve, brainstem, and midbrain plasticity in humans

Electrically evoked ABR (Auditory Brainstem Response) studies in humans with hearing- impairment and/or cochlear implants have demonstrated that responses from near-field regions may be visualized immediately upon initial activation of electrical stimulation (Gordon et al.,

2006). Although the latencies are typically delayed at the outset, the plasticity of brainstem responses does not appear to be affected by age or duration of deafness. In most cases, delayed

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brainstem responses are visualized immediately upon initial implant activation, and neural conduction time within the brainstem continues to decrease throughout the first year of cochlear implant stimulation (Gordon, Papsin, & Harrison, 2002).

In human subjects the wave I component of the ABR, arising from the distal portion of the cochlear nerve, reflects response latencies comparable to normal hearing individuals after 1-2 months of cochlear implant use; while waves III-V, arising from rostral brainstem areas, exhibited normal response latencies within 6-12 months of initial stimulation (Gordon et al.,

2002, 2006). This corresponds with studies in guinea pigs which revealed increased amplitudes and decreased latencies 3 hours following a 2 hour period of high-rate electrical stimulation of

2000 pulses per second (Liu, Wang, Cui, Zhou, & Chi, 2005). These findings provide support for the notion that these areas are experiencing increased myelinization and improved synaptic efficacy as a result of auditory exposure (Gorga, Kaminski, Beauchaine, Jesteadt, & Neely, 1989;

Moore et al., 1996).

Neurophysiologic responses from thalamic areas occurring between 10-50 millisecond post- stimulus using the middle latency response (MLR) have been recorded in conjunction with cochlear implant use in both adults (Firszt, Chambers, Kraus And, & Reeder, 2002; Shallop,

Beiter, Goin, & Mischke, 1990) and children (Gordon et al., 2005). Deprivation effects and sensitive periods within the thalamus have not been well characterized because of a lack of MLR detectability in sleeping or sedated subjects (Kraus, McGee, & Comperatore, 1989). However, aside from slight differences in response amplitude, dipole source analysis in normal hearing

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older subjects did not suggest age related changes in neural conduction time for the Pa and Pb components of the middle latency response (Ponton et al., 2002).

eMLR waveform morphology and visibility improve and become readily detectable with ongoing cochlear implant use (Gordon et al., 2006). They have been used in human subjects to select an ear for implantation and to evaluate differences in subject performance (Firszt,

Chambers et al., 2002; Shallop et al., 1990). eMLR response amplitudes and latencies correspond well with acoustically evoked MLR and behavioral electrical promontory responses

(Kileny & Kemink, 1987), and normalization of the eMLR latency response has been shown to be a distinguishing feature of good speech perception in cochlear implant users (Firszt,

Chambers And, & Kraus, 2002), suggesting that middle latencies may provide a reflection of neural encoding with electrical stimulation.

Cortical plasticity: P1 auditory evoked potential

Cortical auditory evoked potentials occur in adults at post-stimulus onset latencies of 100-300 milliseconds and reflect functioning of auditory thalamocortical pathways and the auditory cortex (Erwin & Buchwald, 1987). Changes in the P1 latency occur during development and throughout life, with normal neonatal latencies around 300 ms and a 2-3 year trajectory to 125 ms, extending into the second decade of life with an adult mean latency of 60 ms (Cunningham,

Nicol, Zecker, & Kraus, 2000; Gilley, Sharma, Dorman, & Martin, 2005; Sharma, Dorman et al.,

2002a; Sharma et al., 1997) Since the P1 response latencies reliably shift as a function of age and/or auditory stimulation (Ponton, Don, Eggermont, Waring, & Masuda, 1996; Ponton &

Eggermont, 2001), it is possible to utilize this evoked potential as an index of auditory system

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maturation. Longitudinal development of this response has been examined in groups of early and later implanted children (Sharma, Martin et al., 2005).

FIGURE 4: P1 latencies as a function of age for 190 normal-hearing children. The line of best fit and the 95% confidence intervals are super-imposed on the raw data. The inset is a CAEP from a 3-year-old normal-hearing child. Reprinted with permission from (Dorman et al., 2007)

It is established that P1 latencies are delayed in hearing impaired toddlers as compared to normal hearing toddlers (Ponton et al., 1999; Ponton et al., 2001). Investigations of children with long periods of auditory deprivation (4.5 years) found that while P1 latencies decreased over time after introduction of auditory stimulation through cochlear implants, the maturational time course was significantly extended to a course of up to 20 years, and in many cases, never reached a latency that was within normal limits (Ponton, Don, Eggermont, Waring, & Masuda, 1996).

However, in another series of experiments (Sharma, Dorman, Spahr et al., 2002; Sharma,

Dorman et al., 2002a, 2002b), it was determined that in severe to profound hearing impaired

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infants under 3.5 years of age, a rapid and systematic decrease following introduction of electrical auditory stimulation was evident, with the response immediately visible upon activation of the implant and the latencies are delayed to approximately 400 ms or more. P1 latency resembled that of a newborn infant within one week of use, and within 8 months of implantation and successful auditory stimulation, most subjects exhibited a decrease in P1 latency to an average of 125 ms, a value that is considered to be well within normal limits for normal-hearing individuals (Sharma, Dorman, Spahr et al., 2002).

FIGURE 5: P1 latencies as a function of chronological age for 245 children with cochlear implants. Diamonds indicate latencies for children implanted at age 7 years or greater. Triangles indicate latencies for children implanted between ages 3.5 and 6.5 years. Circles indicate latencies for children implanted at less than 3.5 years. Reprinted with permission from (Dorman et al., 2007)

Later implanted children exhibit a different pattern of P1 emergence and adaptation following implantation as compared to early implanted children, suggesting that developmental plasticity may limit the potential influence of electrical stimulation on auditory system pathway structure

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and function with longer periods of deprivation (Sharma, Martin et al., 2005). An age cutoff has been estimated for humans at around seven years which is attributable to cortical reorganization rather than changes in the sensory mechanism itself, after which less potential for expression of neural plasticity is evident, presumably due to longer periods of deprivation during critical periods of brain development (Sharma, Dorman et al., 2002a). These results have been corroborated in other experiments and using other components of the auditory evoked potential response as well (Eggermont & Ponton, 2003; Gordon et al., 2005). In later implanted children,

P1 latencies may decrease but do not reach normal latencies, and may exhibit abnormal waveform morphology until at least 12 to 18 months post-implant (Sharma, Martin et al., 2005).

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FIGURE 6: Grand average waveforms for normal-hearing, early and late-implanted children, reprinted with permission from (Sharma, Dorman, & Kral, 2005)

The cortical auditory evoked potential can also be evaluated based on waveform morphology, which refers to the shape, form and structure of the waveform represented. Changes in waveform morphology occur differently in normally developing children as compared to hearing

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impaired children with stimulated versus unstimulated auditory systems (Gordon et al., 2005,

2006; Sharma & Dorman, 2006).

FIGURE 7: Examples of P1 waveforms for a normally developing central auditory pathway (top), an unstimulated central auditory system (second from top), a partially stimulated central auditory system loss (third from top), and a reorganized auditory system (bottom). Reprinted with permission from (Sharma & Dorman, 2006).

In general, poor or distorted waveform morphology in an auditory evoked potential recording is considered to be a sign of dysfunctional synaptic transmission and signal conduction, and is typically attributed to problems with axonal demyelization, degeneration, and/or neuronal death within the nervous system pathways being evaluated (Burkard, Eggermont, & Don, 2007; Katz et al., 2002). For example, the cortical AEP waveform from a normally developing child typically exhibits a large initial positivity (P1), while a hearing-impaired child receiving stimulation via a

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hearing aid or cochlear implant reveals a large negative peak. After a period of auditory exposure, a less severe hearing loss will exhibit a large P1 positivity with a delayed latency as compared to the normally developing child, while in older children with profound hearing loss, an abnormal polyphasic or bifid waveform is observed (Sharma & Dorman, 2006). In this sense, the morphology of the cortical AEP can be used to assess the maturational and functional status of the central auditory nervous system pathways prior to and following intervention.

Scalp-recorded cortical auditory evoked potentials in cochlear implant users are highly susceptible to artifact introduced by the cochlear implant, lasting at least the duration of the stimulus. The P1 response in particular is obscured by a large magnitude pedestal beginning slightly after stimulus onset, followed by overshoot and the ringing of the amplifier filters. The type of implant device and its mode of stimulation, as well as the placement of the remote return electrode affect the distribution of this artifact on the scalp. Bipolar electrodes tend to produce smaller artifact than monopolar coupled electrodes in the cochlea. Several techniques have been successfully developed for removal of cochlear implant artifact from CAEP recordings, including Principal Components Analysis , Independent Components Analysis and an optimized differential reference (ODR) electrode placement strategy (Gilley, et al., 2006).

Diminished plasticity of the central auditory pathways in congenitally deaf children after the age of 7 years is correlated with deficits in speech perception and spoken language development

(Geers, 2006) and agrees with animal models suggesting restricted development of cortical connections outside of sensitive periods (Kral, Tillein, Heid, Klinke, & Hartmann, 2006).

Intervention strategies for congenital hearing loss that involve electrical stimulation of the

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auditory nervous system have greater potential benefit when administered prior to 3.5 years of age, lending a time-sensitive aspect to clinical decision making regarding cochlear implantation.

The P1 response latency has been described as a biomarker for central auditory system development that may be useful in conjunction with standard clinical assessment batteries to monitor the effectiveness of intervention strategies that utilize electrical stimulation of the auditory pathways.

Acoustical stimulation in the maturing hearing impaired auditory cortex

Many infants with congenital sensorineural hearing loss are now fitted with hearing aid amplification as early as 2 months of age (JCIH, 2007). Due to the age requirements for surgical installation of a cochlear implant, it is common practice to begin stimulation with an acoustic device as early as possible to assist the developing auditory system. This approach has produced beneficial effects on the early language outcomes in infants identified prior to 3 months of age with the help of UNHS programs (Sininger et al., 1999; Vohr et al., 2008). Children who are enrolled in very early intervention programs have a significantly greater receptive and expressive vocabulary and appropriate use of gestures by 12 to 16 months of age (Vohr et al., 2008;

Yoshinaga-Itano, 2003), and the vast majority of cases have been shown to reach mainstream education by six years of age (Verhaert, Willems, Van Kerschaver, & Desloovere, 2008). These findings indicate the crucial need to implement an intervention strategy for introduction of auditory stimulations as early as possible when a newborn is identified with hearing loss.

Speech evoked auditory evoked potentials may be used to further study the effects of deprivation and stimulation on the developing auditory system (Eggermont & Ponton, 2003; Martin,

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Tremblay, & Korczak, 2008; Sharma, Martin et al., 2005). The effects of amplification, digital signal processing and various electroacoustic features available with current hearing aid technology on cortical auditory maturation has not been well characterized, as the number of studies in this area is scarce. It has been established the importance of verifying hearing aid functionality using electroacoustic and real-ear measurements prior to CAEP testing in order to evaluate the effects of hearing loss and hearing aid amplification in a methodical fashion.

Conflicting findings in the literature have raised questions about the precise influence of factors such as hearing aid compression characteristics or physiologic saturation on CAEP latencies and amplitudes. Research has shown enhanced obligatory responses of cortical ERP’s in hearing- impaired adults under aided conditions (Korczak, Kurtzberg, & Stapells, 2005), while others have demonstrated no effect of amplification on ERP’s under aided vs. unaided conditions

(Billings, Tremblay, Souza, & Binns, 2007; Tremblay, Billings, Friesen, & Souza, 2006). These discrepancies have raised concerns about interpretation of CAEP latencies and amplitudes under aided conditions.

Although it is essential to establish a greater understanding of auditory cortical processing of acoustically altered signals, these studies did not investigate the pediatric population or long- term effects of amplification on ERP characteristics, which has primarily been investigated in cochlear implant users, and in older children (Eggermont et al., 1997; Ponton, Don, Eggermont,

Waring, & Masuda, 1996; Sharma, Martin et al., 2005). This body of research supports the idea of a critical period of auditory neurodevelopment that is highly susceptible to changes in the plasticity of the auditory cortex, and that intervention during this period is imperative to reaching the maximum potential communication benefit for the developing hearing-impaired child. In

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order to fully understand the relationships between auditory cortical development, deprivation and subsequent intervention in the congenitally deaf infant, the influence of early amplification prior to cochlear implantation must be examined under carefully controlled conditions.

Speech and language measures supporting human auditory developmental plasticity

Results with evoked potential studies of plasticity in electrical stimulation and early sensitive periods are supported by behavioral measures of speech and language outcome (Hammes et al.,

2002). Evidence of influence of cochlear implant use has been identified by improvements in speech perception skills in children (Tyler, et al., 2002; Waltzman, Cohen, Green, & Roland,

2002). Children that undergo implantation prior to the age of three years achieve speech and language development skills comparable to those of their normal hearing peers (Kishon-Rabin et al., 2002; McConkey Robbins et al., 2004). However, congenitally deaf children who are later identified or implanted do not reach the same level of speech perception ability at a similar duration of implant use as their younger implanted peers (Nikolopoulos, O'Donoghue, &

Archbold, 1999; Osberger, et al., 1991; Tyler, et al., 1997).

Evidence of differences in speech perception abilities between age groups has been observed using open and closed set recognition tests, and measures that test recognition of stress pattern, consonants, vowels, words, and sentences (Firszt, Chambers And et al., 2002; Nikolopoulos,

Archbold, & O'Donoghue, 1999). Audiovisual perception and speech intelligibility measures have also shown differences (Tyler et al., 1997). Prelingually deaf children have shown significant improvements in speech perception ability; when implanted prior to the age of 8

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years, 82% of subjects exhibit fluent conversational ability without visual cues (Nikolopoulos,

Archbold et al., 1999).

Neuroimaging studies of human auditory developmental plasticity

Brain imaging techniques have significantly advanced current knowledge in the area of auditory neuroscience, both in normal hearing and hearing-impaired populations. Several methods have made contributions to the study of auditory cortical organization, including magnetoencephalography, positron emissions tomography, and functional magnetic resonance imaging. In the current study, functional MRI is used to investigate auditory cortical status of hearing-impaired toddlers. However, critical findings regarding central auditory system evaluation using other techniques are also discussed.

Magnetoencephalography

Magnetoencephalography (MEG) is a non-invasive technology for functional brain mapping which localizes and characterizes electrical activity of the central nervous system by measuring associated magnetic fields emanating from the brain (Hari, 1990). With fairly sensitive spatial discrimination and excellent temporal resolution, these magnetic fields provide a macroscopic view of brain function that is not obscured or distorted by tissue, fluid or bone. Magnetic signals are most readily measured using induction coils composed of loops of wire which in turn produce a magnetic field within a low noise, high gain current-to-voltage converter called a superconducting quantum interference device (SQUID)(Sams & Hari, 1991).

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The neural basis of sound discrimination has been investigated using MEG in preschool children

(Pihko, et al., 2005), infants (Cheour, et al., 2004), and even fetuses (Lowery, Eswaran, Murphy,

& Preissl, 2006; Schleussner & Schneider, 2004). MEG has been used in conjunction with various components of the auditory evoked potential response for purposes of comparison and dipole source localization (Gage, Roberts, & Hickok, 2006; May & Tiitinen, 2004; Yoshiura,

Ueno, Iramina, & Masuda, 1995). Magnetic field studies have supported prior evidence of tonotopicity and frequency specificity of the central auditory system, and that different response patterns are reflected for human voice stimuli as compared to other types of stimuli (Cansino,

Ducorps, & Ragot, 2003; Gunji, et al., 2003). Evidence of cortical reorganization has been demonstrated in subjects with cochlear hearing loss (Dietrich, Nieschalk, Stoll, Rajan, & Pantev,

2001), as well as evidence of auditory neuroplasticity, by gradual increases in evoked brain activity following the initiation of stimulation by cochlear implantation (Pantev, Dinnesen, Ross,

Wollbrink, & Knief, 2006)

The information provided by MEG consists of functional mapping of neurological activity in real time rather than structural or anatomical information. MEG can be combined with other imaging modalities for a composite representation of function and anatomy. Although MEG offers superior temporal resolution than other neuroimaging techniques, the magnetic fields are perpendicular to the electrical voltage and decrease at a high rate as a function of distance, which renders MEG incapable of detecting deep brain fields (Ponton, Don, Eggermont, Waring, &

Masuda, 1996; Williamson, Lu, Karron, & Kaufman, 1991).

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Positron Emission Tomography

Positron Emission Tomography (PET) is a nuclear medical imaging technique that produces a three-dimensional image or map of functional processes in the body. PET techniques utilize a short lived radioactive tracer isotope injection which emits a positron that decays into metabolically active molecules concentrated within tissues of interest (Villringer & Dirnagl,

1995). This allows for imaging of changes in regional blood flow and glucose metabolism as a reflection of neural activity (van den Hoff, 2005). PET offers somewhat detailed spatial resolution and equal sensitivity for deep and superficial layers (Kandel & Squire, 2000), however, as a technique for scientific investigation in humans, PET is limited by the need to inject radioactive material into participants and the high cost of cyclotrons needed to produce the appropriately formulated radiopharmaceuticals (Budinger, 1998).

Cortical activations in response to electrical auditory nerve stimulation has been observed using

Positron Emission Tomography (PET) (Naito, Okazawa, Honjo, Hirano, et al., 1995). Primary auditory cortex activation appeared to exhibit similar patterns and extent of activation for both pre- and post-lingually deaf subjects as well as hearing subjects. However, higher-order association cortical areas showed significantly smaller regions of activation for pre-lingually deaf subjects as compared to post-lingually deaf or hearing subjects (Naito, et al., 1997). These findings are consistent with animal studies investigating auditory cortical activation patterns

(Hartmann, Shepherd, Heid, & Klinke, 1997; Raggio & Schreiner, 2003; Shepherd & Javel,

1997), as well as observations using functional magnetic resonance imaging (fMRI) with

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auditory stimuli in deaf and hearing toddlers (Cahill, et al., 2007; Patel, et al., 2007a; Wilke et al., 2003).

Cortical blood flow patterns differed between hearing and post-lingually deaf cochlear implant users not for noise stimuli but for speech stimuli, CI users showed greater areas of activation

(Naito, et al., 2000). When listening to speech stimuli, experienced CI users exhibited significantly larger activation than hearing subjects in the temporal cortices as well as Broca’s area and several supplementary areas. Thus far, theories regarding the nature of this phenomenon include issues surrounding the influence of electrical stimulation on spatial tuning and frequency representation in the hearing impaired auditory system, as well as possibilities regarding higher-order cross modal reorganization (Nishimura, et al., 2000) and glucose metabolism (Lee, et al., 2001). It is of interest to explore these questions and look for relationships using fMRI techniques to assess the effects of differing electrically evoked cochlear implant stimulus parameters on cortical blood flow in various populations.

Functional Magnetic Resonance Imaging

Functional Magnetic Resonance Imaging (fMRI) is rapidly developing as a non-invasive diagnostic technique of human brain function which allows neuronal activity to be visualized in vivo by identifying differences in localized regional blood flow and increased oxygenation levels in response to a stimulus or test parameter. fMRI relies on the assumption that neuronal activity stimulates increased glucose metabolism, which is subsequently followed by an increase in demand for cerebral blood flow to the active region (Forster, et al., 1998). The blood oxygen level dependent (BOLD) response was first described in animal studies (Ogawa, Lee, Kay, &

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Tank, 1990) and quickly translated into human studies of the brain (Kwong, et al., 1992), becoming more widely used than PET for experimental purposes due to its availability, excellent spatial resolution and the fact that it does not require exposure to radiopharmaceuticals. Since hemodynamic effects can be somewhat displaced compared to neural activity, fMRI is considered an indirect measure of brain activity with poor temporal resolution. However, improvements in knowledge about cortical organization could be attained through a combination of electrophysiologic, behavioral and neuroimaging techniques.

MRI is beneficial in assessment of temporal bone anatomy as compared to CT due to its enhanced soft tissue contrast, adding greater sensitivity to the internal auditory canal and other cranial structures, and for highlighting cochlear and auditory nerve status (Greess, Baum, Romer,

Tomandl, & Bautz, 2002). Due to susceptibility changes in the magnetic field differences of gray matter induced by the BOLD effect, functional MRI sequences are best visualized using T2 weighted contrasts and fast imaging techniques such as echo-planar imaging (EPI) which has image acquisition capability as rapid as 100 milliseconds (Kwong, 1995; Kwong et al., 1992;

Wilke et al., 2003). Anatomical images can be easily acquired and combined with motion- corrected functional images to localize maximally active regions and determine interactions between anatomy and function. In addition, use of auditory fMRI paradigms may help confirm that nerve conduction and signal propagation from the cochlea to the higher auditory cortical centers is occurring (Patel et al., 2007a). fMRI with auditory stimulation in patients with temporal bone pathology may provide an effective method for assessment of auditory brain activity patterns, particularly in cases of questionable auditory nerve integrity (Cahill et al.,

2007).

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Several current cochlear implant designs are now magnet-compatible (Wackym, et al., 2004), making it possible to evaluate auditory cortical response patterns following implantation.

However, tonotopic organization has not been clearly identified in deaf implant users to date

(Lazeyras, et al., 2002; Seghier, Boex, Lazeyras, Sigrist, & Pelizzone, 2005), and image masking due to implant artifact continues to be a concern for the higher field strengths necessary to illuminate the auditory system response (Teissl, Kremser, Hochmair, & Hochmair-Desoyer,

1999). Several concerns and limitations exist even in non-implanted and normal-hearing subjects for fMRI of the auditory system, including sedation effects and acoustic scanner noise, which must be addressed in order to accurately detect and reflect BOLD activity in specific brain regions. Appropriate methods that have been developed to ameliorate negative effects from nuisance factors are discussed in the following sections.

Sedation

Functional MRI has been used to examine neural auditory and language activity in children

(Holland, et al., 2001) and infants (Altman & Bernal, 2001; Anderson, et al., 2001). Although sedation is typically required in pediatric populations in order to obtain a complete evaluation, several investigations have shown that subjects given passive auditory stimulation under various types of sedation have exhibited a positive BOLD signal response (Born, et al., 2000; Born, et al., 1998; Martin, et al., 1999a). Propofol sedation in particular has been shown to decrease the magnitude of the auditory system response by 40-50% with a reduction in word and voice specific activations (Plourde, et al., 2006), however this effect has been shown to be dependent on the level of propofol plasma target concentrations (Dueck, et al., 2005). Similar dose-

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dependent suppression of auditory BOLD signals has been observed using a sevoflurane agent which limits the ability of higher level word processing during anesthesia but does not completely obliterate the auditory response (Kerssens, et al., 2005; Peltier, et al., 2005).

Therefore, it is possible to obtain valid neuroimaging data from responsive primary and association auditory cortices in sedated infants and toddlers using the appropriate dosage levels

(Veselis, Feshchenko, Reinsel, Beattie, & Akhurst, 2005).

Assessment of Pediatric Brain Data

Spatial normalization of brain imaging data is typically referenced to frameworks based on adult sized brains (Talairach & Tournoux, 1988). Cortical size and shape continually changes and develops throughout childhood, and the morphological structure can be significantly different at various ages and stage of development. In order to minimize error during spatial normalization of functional imaging data, a newly developed pediatric brain template is being used when assessing subjects in developmental studies (Wilke, Schmithorst, & Holland, 2002). Use of infant brain templates allows for normalization of individual images, leading to consistent definition of primary auditory cortex (Altaye, Holland, Wilke, & Gaser, 2008). See Figure B for an example of a manually defined ROI in Heschl’s gyrus using an image normalized to the infant brain template with both coronal and axial views.

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FIGURE 8: Coronal and Axial views of primary auditory cortex defined in an anatomical image using an infant template (Altaye et al., 2008).

Acoustic Scanner Noise

In the past, the high intensity acoustic noise generated by the pulsing of gradient coils during fMRI acquisition has been a major limitation of BOLD studies of the auditory system (Cho, et al., 1997; Hedeen & Edelstein, 1997). Several investigations have shown that large areas of the auditory and association cortices can, in fact, be activated bilaterally by the complex noise of the echo-planar pulse sequence itself, contaminating or masking responses to the actual stimuli administered (Bandettini, Jesmanowicz, Van Kylen, Birn, & Hyde, 1998; Elliott, Bowtell, &

Morris, 1999; Ulmer, et al., 1998). This negative effect is more pronounced for higher magnetic field strengths needed to enhance fMRI (Hattori, Fukatsu, & Ishigaki, 2007; Moelker &

Pattynama, 2003), and increased scanner noise also increases the BOLD response in associated brain regions including the cerebellum and fusiform gyri, possibly due to the compensation for

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noise interference requiring greater recruitment of attentional resources from these related brain areas (Tomasi, Caparelli, Chang, & Ernst, 2005). In addition, the masking effect is more pronounced when the spectral content of the stimulus is similar to that of the scanner noise

(Langers, Van Dijk, & Backes, 2005; Scarff, Dort, Eggermont, & Goodyear, 2004).

Several techniques have been described and investigated to counteract the impact of acoustic scanner noise on fMRI BOLD activation response patterns, including “sparse” temporal sampling (Hall, et al., 1999), clustered volume acquisition (Edmister, Talavage, Ledden, &

Weisskoff, 1999; Talavage, Edmister, Ledden, & Weisskoff, 1999), and behavior interleaved acquisition (Eden, Joseph, Brown, Brown, & Zeffiro, 1999). Combinations of sparse temporal sampling and clustered designs have proved to be promising (Zaehle, et al., 2007). Although it is feasible to diminish some of the effects of acoustic noise generated by the gradient system using these techniques, a number of issues and concerns persist regarding flexibility of the scanning sequence due to constraints related to stimulus duration and repetition time requirements using event-related designs(Gaab, Gabrieli, & Glover, 2007). Therefore, a flexible technique is needed when using auditory stimuli in which scanner noise does not obstruct the brain activation response to the stimulus in any way.

Results have indicated that presentation of an auditory stimulus during periods free from scanner noise lead to a more distinct BOLD response (Schmitter, et al., 2008; Shah, Jancke, Grosse-

Ruyken, & Muller-Gartner, 1999). Auditory cortical function may be investigated in hearing impaired subjects by presenting the stimuli exclusively during completely silent gradient intervals (Schmithorst & Holland, 2004). Using an event related acquisition approach; this

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design offers greater flexibility than other methods, allowing for a number of various durations of auditory stimulation during periods of complete silence in the scanner. The data is then collected during the time period from the peak of the hemodynamic response until it again reaches the baseline. This method provides improved signal to noise ratio and contrast and has robust BOLD activity detection ability in spite of various stimulus durations. Statistical analysis used with this method is the general linear model for image post-processing (Schmithorst &

Holland, 2004).

fMRI of the Auditory Cortex: Current Findings

The mid-1990’s initiated investigations of the functional organization and integrity of the human cerebrum using fMRI of the somatosensory system (Hammeke, et al., 1994). Shortly thereafter, consistent BOLD responses from the left temporal lobe were observed in normal adult listeners using both pure tone and speech stimuli (Millen, Haughton, & Yetkin, 1995), and that word presentation rate significantly influences total activated volume and signal response from both primary and secondary auditory cortices (Dhankhar, et al., 1997). In addition, stimulus intensity induces signal intensity increases within the superior temporal gyrus with a spread of spatial extent for higher intensity levels (Bilecen, Seifritz, Scheffler, Henning, & Schulte, 2002; Jancke,

Shah, Posse, Grosse-Ryuken, & Muller-Gartner, 1998; Mohr, King, Freeman, Briggs, &

Leonard, 1999). Other findings have indicated that stimulus duration (Jancke, et al., 1999), complexity, and frequency content play a role in BOLD activation patterns as well (Hall, et al.,

2002; Strainer, et al., 1997). Tonotopicity of the auditory cortex can be assessed based on the location of the focal brain activity, typically more medial and posterior within the STG for higher frequency stimuli (Seghier et al., 2005; Yetkin, Roland, Christensen, & Purdy, 2004). It was initially believed that fMRI was unreliable for assessment of auditory brainstem activity,

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however, it has now been shown that not only can reliable BOLD responses be recorded from brainstem areas, but it also is subject to spectral sound features such as sound bandwidth

(Hawley, Melcher, & Fullerton, 2005; Sigalovsky & Melcher, 2006). It was recently shown that injury to the inferior colliculus produces reorganized cortical processing in the auditory regions

(Paiement, et al., 2009)

Acoustic stimulation of the auditory system has produced observable patterns of BOLD activation in infants (Anderson et al., 2001), adults (Seifritz, Di Salle, Bilecen, Radu, &

Scheffler, 2001), and even live fetuses at 33 weeks gestation (Jardri, et al., 2008), as well as pediatric subjects with severe to profound congenital sensorineural hearing loss (Wilke et al.,

2003). Furthermore, fMRI has detected BOLD activity in response to direct electrical cochlear stimulation in profoundly deaf patients (Berthezene, et al., 1997; Neumann, et al., 2008; Schmidt et al., 2003). Functional brain activation has been suggested as a possible tool to investigate auditory function in cochlear implant candidates and estimate potential rehabilitative outcomes

(Cahill et al., 2007; Patel et al., 2007b; Schmidt, Weber, & Becker, 2001). An extensive body of work describing auditory cortical function in both normal hearing and hearing impaired infants and toddlers is being developed in the Pediatric Neuroimaging Research Consortium at

Cincinnati Children’s Hospital Medical Center in Cincinnati, OH. See Figures C-E for examples of BOLD activation patterns that have been observed in normal hearing and hearing impaired listeners.

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FIGURE 9: Group maps of HUSH-fMRI data for 19 normal hearing awake children ages 11-18 years using female speech contrasted with silence for both negative and positive contrasts in a pediatric reference frame. Color overlay represents significant activation with spatial filtering above a threshold of z = 1.5, p<0.002, cluster size = 30. . Voxels are only highlighted in color if they adjoin at least 2 other voxels that exceed this activation threshold. Activation is overlaid on a gray-scale, T1-weighted image. (Holland, Karunanayaka, Rajagopal, Smith, & Choo, 2008; Smith et al., 2008).

Negative Positive

FIGURE 10: Group activation maps of HUSH-fMRI data for 22 normal hearing infants with sedation, ages 9-24 months, using female speech contrasted with silence for both negative and positive contrasts in a pediatric reference frame. Color overlay represents significant activation with spatial filtering above a threshold of z = 1.5, p<0.002, cluster size =50. Voxels are only highlighted in color if they adjoin at least 2 other voxels that exceed this activation threshold.

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Activation is overlaid on a gray-scale, T1-weighted image displaying significant BOLD activation in posterior cingulated, A1, Wernicke’s area, thalamus, insula, and primary visual cortex (Holland, et al., 2008; Smith et al., 2008).

Negative Positive

FIGURE 11: Activation in HI infants Group activation maps of HUSH-fMRI data for 16 hearing impaired infants with sedation, ages 9-24 months, using female speech contrasted with silence for both negative and positive contrasts in a pediatric reference frame. Color overlay represents significant activation with spatial filtering above a threshold of z = 1.5, p<0.002, cluster size = 50. Voxels are only highlighted in color if they adjoin at least 2 other voxels that exceed this activation threshold. Activation is overlaid on a gray-scale, T1-weighted image displaying significant A1 activation as well as widespread activation in many non-auditory areas (Holland, Smith et al., 2008).

Due to dramatic differences in BOLD activation patterns between normal hearing and hearing- impaired subjects, the effects of auditory deprivation on cortical hemodynamics have not been well characterized. Extreme variability among individual subjects is problematic for construction and assessment of group maps and individual data. In order for group maps of

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BOLD activation to be representative of overall function in a sample, the activation patterns among subjects must be fairly similar, which is not the case in our hearing impaired population.

A more thorough understanding of the intricate connectivity patterns in the hearing impaired cortical system may be gleaned by investigating larger samples of subjects with various degrees and duration of hearing loss as well as the effects of auditory stimulation, both acoustic and electrical.

Current knowledge in fMRI activation and electrophysiological responses in cochlear implant patients is growing rapidly Most cochlear implant candidates who report hearing sensation upon electrical promontory stimulation also exhibit contralateral hemisphere activation, while those who did not show activation also did not report hearing sensation (Schmidt et al., 2003). Deaf cochlear implant users have exhibited a functional subdivision of the primary auditory cortex into multiple cortical regions in fMRI experiments, and tonotopic maps have been difficult to identify (Seghier et al., 2005). However, stimulation of individual intracochlear implant electrodes has produced fMRI activation maps consistent with the established auditory cortical tonotopic organization (Lazeyras et al., 2002).

Unilaterally deaf subjects have shown patterns of focal brain activity in response to auditory stimulation to the hearing ear, although issues concerning sound transmission to the better ear via bone conduction have caused difficulty with assessment of responses from the deaf ear

(Tschopp, et al., 2000). Findings have indicated that compensatory cortical reorganization takes place in an auditory system which has only been monaurally stimulated (Bilecen, et al., 2000), and that patients with right unilateral hearing loss show the greatest deficits in speech and

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language development as compared to those with left unilateral hearing loss (Schmithorst, et al.,

2005). Hearing impaired subjects that have been acoustically stimulated monaurally with a hearing aid show initial decreases in speech-elicited BOLD activation, but exhibit contralateral hemisphere recovery after 9 months of acoustic stimulation (Hwang et al., 2006).

The auditory nervous system pathway encompasses both functional and morphological components. fMRI offers high spatial resolution which may prove to be useful in assessment of anatomical and structural landmarks of neuronal activity in addition to interpreting connectivity patterns and communication between various cortical regions in both normally developing and hearing impaired auditory systems. Increasing knowledge of the auditory system along with growing popularity and widespread use of fMRI as a research tool may lead to greater advancement of its reliability and consistency for diagnostic assessment and treatment planning.

Cross-Modal Plasticity

Until recent years, it was commonly believed that sensory function was unimodal and that the primary sensory cortices could be reduced to discrete and separate systems operating in complete isolation, independently from the rest of the brain. However, these traditional views have been challenged in favor of a cross-modal system in which early interactions occur even at subcortical levels for purposes of integration of multi-sensory information (Kayser & Logothetis, 2007).

Multi-modal integration at early stages of the sensory processing pathway has important implications for understanding the mechanisms of cortical plasticity involved in the auditory deprivation and acclimatization of congenital deafness.

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Various sensory streams may be modulated by the thalamus, and several studies have suggested the possibility of overlapping or merging of sensory interactions among thalamic nuclei sending and receiving inputs to link different sensory modalities (Crabtree & Isaac, 2002). A study of electrical stimulation in the auditory cortex of guinea pigs was consistent with the theory that neurons within the medial geniculate body of the thalamus are involved in highly specific gating of auditory information across sensory modalities (Yu, Xiong, Chan, & He, 2004). The thalamus is a collection of mixed-circuit nuclei comprised of many separate channels through which sensory and motor information is received and transmitted. A possible functional role of intrathalamic pathways is simultaneous modulation of transmission of signals in multiple regions, engaging a separate or overlapping population of cells in one or more nuclei (Crabtree &

Isaac, 2002). This relationship could have implications for development of thalamocortical connections and the routing and transmission of sensory inputs in cases of auditory deprivation.

On a cortical level, functional pathways between auditory and visual primary cortices have been identified using fMRI in the macaque monkey (Kayser, Petkov, Augath, & Logothetis, 2007), as well as in humans (Meyer, Baumann, Marchina, & Jancke, 2007), exhibiting modulated auditory cortex responses using only visual stimuli, particularly when the stimuli is language related, as in speech reading tasks (Calvert, et al., 1997). Conversely, direct projections from auditory cortex to primary and secondary visual areas have been detected in macaque monkeys (Falchier,

Clavagnier, Barone, & Kennedy, 2002), suggesting that the primary visual cortex (area 17) is anatomically and functionally capable of receiving input from auditory areas. Retinotopically organized visual motion processing areas in cats have been shown to exhibit activation in response to complex auditory information and that, in fact, visually evoked activity is

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significantly enhanced by concurrent auditory stimulation (Clemo, Sharma, Allman, & Meredith,

2008). Numerous animal studies have shown responsivity of visual occipital areas to auditory inputs such as speech and pure tones in cats (Fishman & Michael, 1973; Morrell, 1972), as well as mole rats (Bronchti, et al., 2002). It has been theorized that the main purpose of this relationship is connected to sound source localization (Andersen, Snyder, Bradley, & Xing,

1997) and spatial functions such as attention and navigation (Kolb, Buhrmann, McDonald, &

Sutherland, 1994), however, this evidence is also suggestive of possible multimodal plasticity functions leading to maturational cortical reorganization in the hearing impaired central auditory system.

Combination of fMRI with Evoked Potential Measures

The use of combined fMRI and evoked potential recordings is a growing area of expertise with great promise to expand our knowledge of auditory cortical function. The two techniques in conjunction with each other offer the advantage of both spatial and temporal resolution of neuronal processing. Auditory evoked potentials can be used to identify areas in which the blood oxygenation level signal varies with changes in the EEG waveform such as latency, amplitude, and morphology. Studies using simultaneous EEG and fMRI measures have supported the idea of reduced scanner noise and increased signal intensity for shorter evoked potential latencies and improved waveform morphology; and also stronger BOLD activation with a greater number of activated voxels (Novitski, et al., 2001; Thaerig, et al., 2007). Due to issues regarding signal-to- noise ratio, it is suggested that a 64 electrode montage is most suitable for recording evoked potentials within the magnetic field (Scarff, Reynolds et al., 2004). Data between fMRI and

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simultaneously recorded evoked potentials has agreed on the anatomical AEP equivalent dipole locations and center of gravity of the fMRI activity (Scarff, Reynolds et al., 2004).

The relationship between neuronal and hemodynamic activity has been illuminated using fMRI in conjunction with various components of the AEP response, by identifying task-relevant sources of activity and separating regions with different response properties. For example, the fMRI regions observed as most correlated with P300 amplitude include the supramarginal gyri, thalamus, insula, and the right medial frontal gyrus (Horovitz, Skudlarski, & Gore, 2002). A recent study utilizing a combination approach with fMRI and cortical auditory evoked potentials was able to determine that the N1 and P1 response amplitudes represent specific indices of exogenous attentional processes generated in frontal parietal cortical regions (N1) and visual occipital areas (P1) (Natale, Marzi, Girelli, Pavone, & Pollmann, 2006). Auditory cortical activity has been investigated using fMRI in conjunction with the Mismatch negativity (MMN), revealing that the magnetic field has little to no influence of the characteristics of the MMN response waveform, but localizing the BOLD signal foci related to the MMN stimulus to generators in the right superior temporal gyrus and the right superior temporal plane (Liebenthal, et al., 2003). MMN has also been shown to have plasticity and sensitivity to auditory memory and training, however, no hemodynamic changes have been observed in individual subjects following auditory training (Jancke, Gaab, Wustenberg, Scheich, & Heinze, 2001).

It has been suggested that fMRI methods should accurately reflect the oscillatory activity of electrophysiological population responses for frequency tuning (Kayser, Petkov, & Logothetis,

2007), intensity changes (Thaerig et al., 2007), temporal sequencing of cortical activity (Rowan,

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et al., 2004), and localization cues (Fujiki, Riederer, Jousmaki, Makela, & Hari, 2002).

Significant efforts has been successfully invested in reducing MR induced cardiac artifact in order to retrieve the small voltage auditory component from the EEG when simultaneously recorded during fMRI (Ellingson, et al., 2004; Mantini, et al., 2007; Nakamura, et al., 2006;

Wan, et al., 2006), however, in the current study, the evoked potential measurements were obtained outside the MR scanner during a separate session. The precise relationship between the morphology of P1 auditory evoked response with its associated BOLD activity has not been well characterized in cases of auditory development and deprivation. The unique exploratory possibilities offered by combining the abilities of fMRI with auditory evoked potentials could expand our knowledge of auditory cortical neuronal development and dysfunction, leading to important developments in functional diagnostics for patients with hearing loss and auditory pathology.

Conclusions

As a result of innovative and pioneering work in electric stimulation of hearing, the cochlear implant has proven to be a safe and effective device and perhaps the most successful neural prosthesis that uses electrical stimulation to restore sensory function. Numerous possibilities for utilizing fMRI and auditory evoked potentials as diagnostic techniques are evident in the current efforts to improve the design and performance of electrical stimulation with cochlear implants.

The development of new prognostic tools for objective outcome predictors and assessment may contribute to advancement of current topics of interest, including design of the electrode array and insertion depth, the use of bilateral implants to enhance speech perception and localization ability, bimodal stimulation, and approaches to rehabilitation and auditory learning.

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Electrical stimulation of the auditory system via cochlear implantation has revolutionized the management of patients with permanent congenital sensorineural hearing impairment. Rapid change is occurring in the design of cochlear implants, with new developments in electrode arrays, mode of stimulation, and processing strategies. Technology for stimulation has evolved from single-electrode devices used mainly for sound awareness to multiple electrode devices that provide users with near normal speech perception ability even with no visual cues.

An established body of evidence indicates that performing cochlear implantation as early as possible in congenitally deaf infants and toddlers facilitates more effective utilization of prosthetic auditory stimulation, resulting in greater advancement of language skills compared to children implanted later in development. However, auditory perception and language skills are difficult to assess accurately in infants. Despite concerted efforts, confidence and accuracy in pre-surgical outcome prediction and post-surgical outcome verification continues to present challenges. While technological advances are likely to result in continued improvements in patient performance, it will be important to resolve engineering problems and narrow down possible causes of the large individual variability in outcome among today’s cochlear implant users.

Pre-implant acoustic stimulation is important to overall outcome in speech perception and language development in the hearing impaired infant. Hearing aid amplification may be fit to a newborn infant as early as 2 months of age in order to provide acoustic input prior to cochlear implantation (Bubbico, Di Castelbianco, Tangucci, & Salvinelli, 2007; JCIH, 2007). All

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evidence indicates that appropriate auditory exposure during the first year of life is highly beneficial in facilitating neural development and maximum communication ability (Sininger et al., 1999). Introducing early intervention through amplification may alter functional and morphological changes in the physiological and anatomical properties of the central auditory system that are induced by deprivation effects (Sharma, Dorman, Spahr et al., 2002; Willott,

1996).

An extensive body of research has developed to describe the effects of both electrical and acoustic stimulation at various levels of the auditory system. Developmental and morphological patterns of changes that occur as a result of chronic stimulation provided by long-term use of an implant can be measured objectively using a variety of non-invasive techniques. Cortical neuronal dysfunction may contribute significantly to the variability in individual outcomes of cochlear implantation. Functional magnetic resonance imaging techniques offer a reflection of the spatial relationships and magnitude of neural activity, while AEP responses are the only methods with a sufficiently high temporal resolution to analyze these dynamic patterns of activity. A growing interest in central physiologic studies of auditory development and deprivation, and cochlear implant electrical stimulation will hopefully provide a means of evaluating the engineering and patient challenges with the goal of enhancing and maximizing our capabilities in the restoration of human hearing.

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Chapter Three: METHODS

Subjects

Fourteen hearing impaired (HI) children ages 9-24 months with residual hearing ranging from 85 dBHL to 100 dBHL pure tone average (PTA) were recruited for this study through the

Departments of Otolaryngology, Audiology, and Radiology respectively, according to an

Institutional Review Board (IRB) approved protocol and informed consent obtained from the parents or guardian. Three subjects were excluded from the study due to grossly abnormal brain anatomy. All subjects had minimal residual hearing levels (HL) with pure tone audiometry ranging from 70 dB to 110dB, placing them in the classification of severe to profound hearing loss.

In order to fully describe the auditory function of individual subjects and rule out exclusion criteria, audiological test results were retrieved from medical records, which including aided and unaided pure tone air conduction, bone conduction and speech audiometry, tympanometry, the

Ling 6-Sound test, Infant and Toddler Meaningful Auditory Integration Skills (IT-MAIS) assessment, and the Auditory Skills Checklist (ASC).

Inclusion Criteria

-Age 9-24 months.

-Weight and height between the 5th to the 95th percentile for age.

-Referred to CCHMC Radiology for MRI of brain by Otolaryngology for

evaluation of internal auditory canal (IAC) and suspected sensorineural hearing

loss.

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-Audiologic evaluations retrieved from medical records reflecting Narrow-Band

Noise (NBN) or pure tone threshold average within the conventional test range of

speech frequencies (500, 1000, and 2000 Hz) between 70 and 110 dBHL

bilaterally, identified by auditory brainstem response, otoacoustic emissions,

and/or behavioral techniques such as visual reinforcement audiometry using

sound field or insert earphones if possible.

-Informed consent of parent or guardian for the subject’s fMRI study participation

and additional audiologic testing at follow up appointments.

Exclusion Criteria

-Standard MRI exclusion criteria as set forth by the CCHMC Dept. of Radiology.

(See Appendix A).

-Orthodontic appliance or other metallic implants that contraindicate MRI.

-Gestational age <36 weeks and/or birth weight less than the 25th percentile.

-Head circumference <5th or >95th percentile.

-Conductive or unilateral hearing loss.

-Congenital brain malformations as identified in anatomical images by a licensed

radiologist during clinical MRI.

-Stigmata known to be associated with auditory system dysfunction (See

Appendix B).

Participant Characteristics

A total of fourteen subjects ages 9-24 months were initially enrolled in this study. All subjects had congenital bilateral severe to profound sensorineural hearing loss and had been fitted with

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appropriate binaural hearing aid amplification. Three subjects were excluded from the study due to abnormal brain anatomy, based on neuroradiology reports. Table 1 defines the sample characteristics. Sixty percent of the sample was female; the mean age was 15 months (range 9-

24 months), and comorbidities were present in 3 children in the sample. Comorbidities included history of cytomegalovirus, fetal alcohol syndrome, severe combined immunodeficiency, and otitis media/pressure equalization tubes.

Table 1: Sample Characteristics (n = 11)

Characteristic: Mean SD Range Age at time of study 15 months 5.2 months 9-24 months Age at HA fitting 7.7 months 5.8 months 3-21 months Duration of HA use 6.5 months 3.4 months 1-12 months Aided SRT 52 dBHL 5.4 dBHL 45-60 dBHL P1 Latency 215 ms 67.7 ms 116-318 ms P1 Amplitude 4.5 V 1.4 V 3.02-7.38 V Total fMRI Activation 194 pixels 204 pixels 13-603 pixels Gender Number in Sample Male 4 Female 7 Race Caucasian 8 African American 2 Hispanic 1 Native American 0 Asian 0 Sedation Propofol 7 Sevofluorane 2 Nembutal 2 HA Experience Users 6 months or less 5 Users 7-12 months 6

Fitted prior to age 7 months 4 Fitted 7 mos of age or later 7 Key: SD= Standard Deviation; dBHL= Decibels Hearing Level; HA= Hearing Aid

TABLE 1: Sample characteristics

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Subject descriptions

A participant description of hearing and history of auditory development was generated for all eleven subjects, obtained from medical records, chart notes, and interviews with the participants and their attending physicians or audiologists. Language ability estimations are based on the

SKI HI Language Development Scale for receptive language ability. Auditory abilities were assessed using the Infant and Toddler Meaningful Auditory Integration Scale (IT-MAIS) and the

Auditory Skills Checklist (ASC). A summary of these findings is found in Table 2.

Subject Age Race Duration Age at Aided Threshold at Language IT- ASC Number and HA use fitting SRT/PTA 500 Hz ability MAIS Gender (mos) Aided/Unaided (age range in mos) 1 16 WF 10 6 55/60 55/110 8 to 10 8/40 9/70

2 12 BM 8 4 55/50 35/75 2 to 4 7/40 11/70

3 10 WF 7 3 50/70 60/90 6 to 8 0/40 1/70

4 22 WF 7 15 45/60 55/85 14 to 16 13/40 33/70

5 16 WM 12 4 60/50 55/115 16 to 18 0/40 1/70

6 9 WM 6 3 50/70 70/110 6 to 8 1/40 13/70

7 15 HF 9 6 50/55 55/95 18 to 20 15/40 31/70

8 11 WF 1 10 60/65 55/110 4 to 6 10/40 18/70

9 24 BF 3 21 45/60 45/100 10 to 12 0/10 1/70

10 12 WM 2 10 50/55 50/95 4 to 6 1/40 6/70

11 10 WF 7 3 70/60 35/80 4 to 6 0/40 7/70

TABLE 2: Individual participant characteristics (additional information on individual subjects available in Appendix C). Functional Imaging Protocol

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Sedation

All subjects included in this protocol were sedated for a clinical MRI procedure. Sedation was performed according to the clinical procedures outlined in the Sedation Program for the

Department of Radiology. The procedure used for sedation in these subjects followed the clinical standard of care prescribed by the CCHMC Division of Pediatric Anesthesiology for sedation of infants for clinical MRI. It is important to note that sedation was not performed solely for the purposes of this research protocol. Rather, patients requiring sedation for a clinically indicated MRI scan were approached to enroll in this study.

The method used for sedation during MRI varied depending on judgment of the anesthesiologists, radiologists and others involved with the clinical scan of the patient. At the time of this study, the protocol for sedation used by Pediatric Anesthesiology appeared to best preserve the BOLD signal needed for fMRI and was considered optimal for the purposes of this fMRI study. Every effort was made for this study to capture fMRI data under sedation with

Propofol. However, the Radiology Department also uses oral Nembutal, oral Chloral Hydrate, intravenous Nembutal and other forms of sedation for MRI, based on the clinical needs of the individual patients.

In seven subjects, a protocol was followed for intravenous Propofol drip 200 g per Kg per minute with an 8% Sevoflurane induction. One subject in the study received orally administered

Nembutal sedation at a dosage of 5 mg per Kg based on the weight of the patient, and one subject received intravenous Nembutal sedation at a dosage of 3 mg per Kg. One subject was initially sedated using the Propofol protocol, but awakened during the MRI procedure, therefore

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was continued with an 8% Sevoflurane in oxygen combined with 1 liter per minute of nitrous oxide. Finally, one subject received Sevoflurane in oxygen, induced at a gradually increasing level of 2% to 8% and then continued at 2.2% throughout the remainder of the procedure.

Instrumentation

Functional MRI scans were performed using the Siemens Medical Solutions (Erlangen,

Germany) Trio 3T MRI system. The auditory input to the subjects was delivered at ear level through a calibrated Avotec, Inc. SS3100 MR compatible audio system (Stuart, Florida) with levels set to exceed audiometric hearing thresholds of each patient by approximately 10 dBSL.

Silicone ear inserts were coupled to the headset for direct placement in the ear canal to accommodate for infant head size and to prevent collapsing ear canals. This was to ensure that sound stimulation is presented directly toward the tympanic membrane through a patent external ear canal. Following audiologist-supervised headset placement the head was restrained within a padded head holder with additional foam pads to minimize head motion.

Stimuli

The first stimulus is a series of Narrow Band Noise (NBN) that range from 0.5 to 2 seconds duration, with center frequencies of 250, 500, 1000, 2000, and 4000 Hz, alternating with silence.

Each NBN sequence was played through the earphones for 5 seconds during the silent interval of the scanner. The second stimulus consisted of the pre-recorded female voice reading several short stories previously used in fMRI studies of language development (Holland, et al., 2007;

Plante, Schmithorst, Holland, & Byars, 2006). The stories are broken into speech segments of 5- second duration. Speech segments were alternated with silent intervals for maximal contrast

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between conditions in auditory and speech recognition regions (Table 3). Sound levels for auditory stimulation were set to approximately 10 dB above the hearing threshold for the infant as measured during audiologic evaluation and in no case did the stimulus level exceed 120 dB.

TABLE 3: HUSH fMRI Paradigm (Story-Silence-NBN) 15 blocks of 36 seconds each = 9 minutes (plus 4 seconds initial scan period) (Schmithorst & Holland, 2004).

Procedures

Subjects were placed in the scanner following sedation with MR compatible headphones/inserts and padded head holder to minimize motion. The clinical scans prescribed by the neuroradiologist in the referral protocol were performed first following the sedation procedures.

A licensed neuroradiologist immediately reviewed all clinical brain scans to ascertain whether pathology is present that would be likely to impact hearing. If such pathology was suspected, the child was excluded from the study, and the fMRI procedure was not performed. Abnormalities

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were reported to the patient’s referring physician or family as dictated by standard clinical protocol in Radiology.

Infants with normal appearing brain MR images underwent fMRI at the end of the clinically prescribed MRI series. During the above described speech stories and NBN stimuli presentation, a time series of 110 echo planar imaging gradient-echo images was acquired. Twenty-four axial sections 5 mm thick were obtained ranging from inferior aspect of temporal lobes to superior apex of cerebrum. These scans added 10 minutes to the time required for the clinical exam. The total MR imaging examination, including the fMRI scan, was typically completed in one hour or less.

Data Analysis

Three dimensional anatomical and functional image data sets were reconstructed and processed on a computer workstation using Cincinnati Children’s Hospital Image Processing Software

(CCHIPS). This Interactive Data Language (IDL) based program (ITT Corp., Boulder,

Colorado) for statistical parameter mapping of activation was used to compute the 2D activation maps and to overlay them on anatomical MR images of the same plane. A pediatric template referenced from infant brains was used to reconstruct the anatomical scans (Altaye et al., 2008).

Anatomical scans acquired as part of the clinical sequence were used as reference and overlay of the fMRI activation maps. CCHIPS uses statistical algorithms to estimate the areas of activation and confidence levels from acquired images. Following calculation of cortical activation maps on a pixel-by-pixel basis, artifact, noise reduction and motion correction were performed and images post-processed using the general linear model. Individual activation maps were created

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using a fixed effects analysis to find significant regions of activation (ROI), identified in each subject’s anatomical images and defined functionally by two neuroimaging experts, based on group averages of activation observed in normal hearing subjects. These ROI’s include the full extent of the primary auditory cortex (A1) located within the transverse temporal gyrus, including Heschl’s gyrus and Brodman’s area 41 and 42, and encompassing language processing regions of Brodmann’s areas 21 and 22. See Figure 12 for an anatomical image representing the

ROI defined for this study.

FIGURE 12: White-lined sectioned areas represent ROI defined for this study

Due to the limited size and area contained within primary auditory cortex, surrounding language regions were included to increase the likelihood of identifying BOLD activation occurring in response to auditory stimuli. Within this ROI, the total number of pixels exceeding a P < .05 threshold were tallied and subjected to statistical analysis as a dependent variable for correlation with auditory evoked potential findings. Similarly, a voxel-by-voxel correlation for activated

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regions outside the ROI was conducted to identify other areas of cortex involved in metabolic activity during the story tasks.

Auditory Evoked Potential Recording Protocol

Instrumentation

Electrophysiologic responses were collected in a sound treated booth using the Intelligent

Hearing System Smart-EP two-channel evoked potential recording system, and the stimulus was delivered via Behringer MS16 Monitor Speakers with presentation levels calibrated for

75dBSPL at ear level, or exceeding aided hearing thresholds by a minimum of 10 dBSL.

Speakers were situated 1.5 meters and at 45 degree angles from the center of the patient chair, on each side, and with the center of the speaker positioned at a height of 3 feet. Gold EEG cup electrodes of 10 mm diameter and 1.5 M in length were used for the recordings, with the active electrode placed at Cz and references on the mastoids. The second channel montage was placed at the lateral canthus of the eye (referenced to supra-orbital) to monitor and remove eye-blink artifact. Age appropriate books and toys were used to maintain the subject’s attention throughout the task.

Stimuli

Cortical auditory evoked responses were recorded by a licensed audiologist using the synthesized speech CV syllable /ba/, identical to the one used in Sharma, et.al. (1997, 2002). This stimulus was generated by the Klatt (1980) speech synthesizer, was 90 ms in duration and contained five formants. The starting frequencies of F1 and F2 are 234 Hz and 616 Hz, while the center frequencies for the vowel sound are 769 Hz, 1232 Hz, 2862 Hz, 3600 Hz, and 4500 Hz. The upper three formants are steady-state; the amplitude is constant for 80 ms and falls linearly to 0

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during the last 10 ms of the stimuli. The stimulus was presented binaurally at 1.1 per second with 910 ms offset-to-onset interstimulus intervals for a minimum total of at least two runs of

300 sweeps each.

Procedures

Within one month of each subject’s fMRI scans and prior to cochlear implantation, an additional audiology clinic visit to Cincinnati Children’s Hospital Medical Center was scheduled. During this visit a licensed audiologist obtained aided cortical auditory evoked potential measurements using standard clinical procedures. Participants sat in a chair on the caregiver’s lap and watched a silent video movie, played with hospital-approved toys, or looked at a picture book of their choice. Tympanometry evaluations were conducted to ensure normal middle ear system status.

After the skin was cleansed with a mild abrasive, five electrodes were applied by washing the scalp with alcohol and using a water-based paste to hold them in place. Behringer MS16

Monitor Speakers were used to administer the stimulus in the aided sound field at a minimum of

10dBSL (over the aided SRT), with binaural hearing aid amplification devices adjusted to appropriate output and gain by a licensed audiologist (LC). Hearing aid functionality was verified via listening check on the day of testing. Four subjects had to be evaluated using EAR

3A insert earphones due to hearing aid problems such as being out for repair, unsuccessful fit or non-compliance during the testing. These subjects were tested at 10dBSL (over their unaided

SRT). All subjects received the stimulus or wore a hearing aid in the better or best functionally hearing ear, while the reference electrode was placed on the contralateral mastoid, to avoid electromagnetic interference from the hearing aid or insert earphone.

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Evoked potentials were measured from the Cz location with a mastoid reference and forehead ground, and eye blinks were monitored in a second channel using a bipolar electrode montage

(lateral outer canthus-superior outer canthus). Averaging was automatically suspended when eye blinks are detected. The recording window included a 10 ms pre-stimulus and 500 ms post- stimulus time frame, with a .1-100 Hz analog filter of incoming evoked responses. A minimum two runs of 300 sweeps each was collected, and in circumstances when the run had to be terminated early due to child test fatigue, extra runs were acquired in order to complete at least a grand total of 600 sweeps. No individual run contained fewer than 150 sweeps. In some cases, extra runs were also acquired up to 1200 sweeps total if waveform morphology or repeatability was questionable. In all subjects, an additional test run with no amplification and no stimulus was collected to ensure that the repeatable response observed was not due to extraneous factors.

The entire test session lasted approximately 25-30 minutes.

Data Analysis

P1 auditory evoked potential data were accumulated in at least two separate runs of 300 sweeps each and stored in the Smart-EP database and as a separate PDF file. During the recording, sweeps greater than 100 microvolts were rejected offline to eliminate artifact, and remaining sweeps computed into an averaged waveform. Replicable individual waveforms were averaged into a grand average waveform for individual subjects; latency peaks selected, amplitude measured and morphology classification were judged and agreed upon by two licensed audiologists (LC, AS), based on the following criteria. P1 was defined as the first robust positivity in the waveform falling within the range of 125 to 450 ms latency, and with minimum amplitude of 1 microvolt measured from the initial downward slope of the peak of the P1

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component to the preceding negative trough. If an initial negativity of greater than 1 microvolt was visible within the first 250 ms of the waveform, the P1 peak was selected on the first positive peak within criteria following this negativity, and bifid peaks were marked on the first peak. These determinations were made without regard to the subject’s chronological age.

Statistical analysis of evoked potential and fMRI data

Descriptive statistics are presented, including means; standard deviations and the range of scores for both fMRI activated pixel count and evoked potential latency and amplitude. Demographic characteristics of the sample are included in a table format. In order to describe the P1 response characteristics of our sample in relationship to auditory sensory experience, a multiple regression analysis was performed to assess hypotheses 1 and 2. Correlation coefficients will be reported and a representative scatterplot will be constructed with one variable on each axis and the scores of all subjects plotted as variables, as well as a regression line to identify central tendency and a prediction of standard error of estimate. The purpose of this analysis was to determine the impact of chronological age/duration of the hearing loss and auditory sensory experience or duration of hearing aid use (in months) on the latency of the P1 auditory evoked potential response waveform. Using the PASW Statistics 18 (SPSS, Inc., Chicago, IL) software program, this regression analysis was tested at a .05 level of significance and with an appropriate measure of effect size, descriptive statistics and demographic information.

In order to test exploratory hypotheses 3 and 4, statistical analysis searched for significant relationships between BOLD-activated pixel count on fMRI for P1 characteristics of latency and amplitude. In this sense, the independent variable is considered to be P1 latency, while the

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dependent variable was the activated pixel count in specified regions of interest. For the group analysis, P1 peak latencies and the number of activated fMRI pixels from the auditory tasks presented were subjected to a one-tailed Pearson product-moment correlation coefficient to define and describe the strength, direction, and form of the relationship between these two variables. The P1 amplitude/fMRI activation correlation was performed using a Spearman’s

Rho correlation due to non-linearity. Using the CCHIPS software program, this correlation analysis was tested at a .05 level of significance and with an appropriate measure of effect size, descriptive statistics and demographic information. A correlation map was constructed using z statistic images of suprathreshold voxels within a specified sensory ROI to identify a group activation pattern associated with P1 latency. These images were thresholded at z > 1.96 and significant clusters defined according to extent (at p < .002). This model answered the research question by identifying corresponding changes between fMRI and evoked potential data that may reveal a systematic relationship between the two variables.

Critical assumptions underlying this statistical model included a normal distribution of interval- level data exhibiting a linear relationship, homoscedacity and an absence of outliers, as well as minimal measurement error and unrestricted variance. Due to the presence of non-linear relationships between several of our measurement variables, it was determined that a non- parametric Spearman correlation should be used for a portion of the analysis, as described in the comparison of fMRI and AEP results below. This will allow for the use of each of these variables to make accurate predictions about the other, demonstrate the validity and reliability of fMRI as a comparison measure to the P1 auditory evoked potential latency, and verify our theory

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that patterns of fMRI activation in the auditory cortex are a precise reflection of central auditory nervous system maturation.

According to findings in neuroimaging literature, approximately 12 subjects are required to achieve 80% power at the single voxel level for typical activations (Desmond & Glover, 2002), which is reasonably consistent with the estimated number of subjects available to recruit for this exploratory study. For further confirmation of appropriate sample size, an a priori estimation was conducted to help estimate the number of subjects needed to achieve adequate power (>.80) for this study using G*Power, a statistical software package designed to perform high-precision power analyses for the most common statistical tests in behavioral research (Faul, Erdfelder,

Lang, & Buchner, 2007). At a significance level of .05, we expect that the number of activated pixels on fMRI will explain approximately 50% of the variance in the data for P1 latency, and based on that assumption an estimated large effect size of 1 at 80% power was calculated according to the criteria set forth by Cohen’s d. Based on the results of this power analysis we expect to find a statistically significant effect for approximately eleven subjects if the effect size reaches 1.

Issues of internal validity have been addressed in the subject selection inclusion and exclusion criteria in a finely tuned attempt to avoid threats related to subject characteristics. The conditions under which the study will occur for each individual subject were standardized to control for location, instrumentation, and implementer threats to internal validity. External validity was established through a purposive sampling method in order to create results that are generalizable to the accessible population of interest. This nonrandom sampling procedure

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builds a sample that was selected because the individuals exhibit special characteristics representative of the target population, which are toddlers with congenital moderate to severe sensorineural hearing loss. It was determined prior to the study that extreme outliers that individually shift the degree of the correlation by more than r = .3 would be eliminated from the analysis, however, no extreme outliers were evident in this subject sample. Inter-rater reliability was established by evaluation of the individual subject data by three different experts, as well as test-retest reliability by evaluation of individual responses several times using separate samples of data from the same subject.

Chapter Four: RESULTS

Introduction

The results of this study are presented in three sections. The first section contains results pertaining to the auditory evoked potentials data, specifically the P1 amplitude and latency values, and waveform morphology in relationship to auditory sensory experience. Functional

MRI information is presented in the second section, including group maps of auditory cortex activation. The final section of these results discuss the comprehensive analysis of the final sample of data, including the statistical comparisons between fMRI activation and auditory evoked potentials data, as well as additional significant results observed.

Auditory Evoked Potentials Results

This section presents results of the analyses responding to the first two research questions presented in Chapter One. Additionally, the interaction between these two research questions is

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explored. A probability level of .05 was considered statistically significant on all measures. The research questions are specified below.

Research Question 1

Is P1 latency in HI toddlers influenced by the age at which they were fitted with hearing instruments?

Research Question 2

Is P1 latency in HI toddlers influenced by the duration of hearing instrument use?

All subjects in the study exhibited an observable and measurable P1 response with good repeatability, and meeting all of the criteria predetermined at the outset of the study. Waveform morphology was compromised in some instances due to the condition of the child, and may also have been influenced by age or auditory exposure. Since the child is required to be awake and alert during P1 measurements, test fatigue was problematic during some test sessions, and therefore, some of the recordings were noisy. In spite of this challenge, it was still possible to visualize a repeatable P1 waveform in every subject. Representative waveform complexes are displayed in Figure 13a-b, presenting in the 13a the P1 waveforms that interpreted as outside of normal limits, or delayed, for age range of the subject, and presenting in 13b the waveforms that are considered to be within normal limits for age range of the subject. Waveforms shown are averages for individual subjects containing at least two trials runs with a minimum of 600 sweeps total contained in the average. Two individual runs and grand averages are shown on each subject in Appendix C, along with a description of each subject’s hearing history.

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FIGURE 13a: Averaged waveforms for individual subjects 4, 7, 8, 9, and 10 are displayed with P1 peaks marked and labeled with latency in ms followed by amplitude in V. Subjects with latencies that are delayed in comparison to age norms are displayed in this graph; subjects with latencies that are considered to be within normal limits for age norms are displayed in the graph below (Figure 13b). Waveform displays represent at least two runs of 300 sweeps each on a 12 V, 500 ms scale. Stimulus amplitude is labeled on the left. Subjects 4 and 7 (top two waveforms) were stimulated via insert earphone. Other subjects were stimulated in the sound field with a hearing aid on. See Appendix C for additional information.

FIGURE 13b: Averaged waveforms for individual subjects 3, 2, 11, 5, 6, and 1(in this order) are displayed with P1 peaks marked and labeled with latency in ms followed by amplitude in V. Subjects with latencies that are delayed in comparison to age norms are displayed in the above graph (Figure 13a); subjects with latencies that are considered to be within normal limits for age norms are displayed in this graph. Waveform displays represent at least two runs of 300 sweeps each on a 12 V, 500 ms scale. Stimulus amplitude is labeled on the left. Subjects 6 and 1 (bottom two waveforms) were stimulated via insert earphone. Other subjects were stimulated in the sound field with a hearing aid on. See Appendix C for additional information.

80 Multiple Regression Analysis

A standard multiple regression was performed between P1 latency as the dependent variable and duration of hearing aid use (in months) and age (in months) at hearing aid fitting as independent variables. Analysis was performed using PASW Statistics 18 REGRESSION and PASW

Statistics 18 FREQUENCIES (SPSS, Inc., Chicago, IL) for evaluation of assumptions. Results of this evaluation revealed that normality, linearity, and homoscedacity of residuals for the variables involved were within acceptable limits, therefore no transformations were performed on the data. With the use of a p < .001 criterion for the Mehalanobis distance one outlier among the cases was found, however, deletion of this case did not dramatically affect the overall result, therefore it was included in the dataset. No case had missing data and no suppressor variables were found, N = 11.

P1 latency is regarded as having a developmental effect in relationship to auditory sensory experience, and although typical age-related changes in the P1 response are only present in the normal-hearing population (Dorman et al., 2007; Ponton & Eggermont, 2001), a corrected latency value based on a comparison with age-norms was evaluated for use in this statistical analysis. In order to verify that an effect of absolute chronological age as a confounding factor does not exist within this sample of severe to profoundly hearing impaired children, a correlation analysis was conducted between P1 Latency and absolute age, and was not found to be significant for an effect, r (10) = .33, p = .318. For further confirmation, a Student’s t-test (for small sample sizes) was performed to determine if a statistically significant difference in P1 latency is evident in this sample between subjects 0-12 months and subjects over 12 months of age. This analysis also did not reveal a significant effect, t(9) = .268, p = .795, and no

chronological age-related changes were detectable. Therefore, it was determined that factoring absolute age as a covariate would not be necessary, and absolute latencies were used in the regression and correlation analyses. Figures 14 and 15 display the individual correlation scatterplots for actual P1 latency with duration of hearing aid use and age at fitting.

Relationship between P1 Latency and duration of HA use 350

300

250

200

150 P1 Latency (ms) Latency P1

100

50

0 02468101214

Duration of HA use (mos)

FIGURE 14: Correlation scatterplot illustrating relationship between P1 Latency (ms) and duration of consistent hearing aid use in months for individual subjects. Results suggest that in this age population, P1 latency can be predicted to decrease by 10.6 ms for every month of consistent hearing aid use. Squares: fMRI scans and P1 measurements were performed on separate days.

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Relationship between P1 Latency and age at HA fitting

350

300

250

200

150 P1 Latency (ms) P1 Latency

100

50

0 0 5 10 15 20 25

Age at HA fitting (mos)

FIGURE 15: Correlation scatterplot illustrating relationship between P1 Latency (ms) and age in months at the time of hearing aid fitting for individual subjects. Results suggest that in this age population, P1 latency can be predicted to appear earlier (by 5.2 ms per month) in children experiencing shorter periods of full time auditory deprivation. Squares: fMRI scans and P1 measurements were performed on separate days.

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REGRESSION TABLE

Model R R Square St. Error Change Statistics of the R Square F Change Df1 Df2 Sig. F Estimate Change Change .848 .720 40.052 .720 10.266 2 8 .006

Model Sum of Squares df Mean Square F Sig. Regression 32936.624 2 16468.312 10.266 .006 Residual 12833.376 8 1604.172 Total 45770.000 10

Model Unstandardized Coefficients t Sig. B Std. Error (Constant) 242.921 44.376 Age at fit 5.203 2.558 2.034 .076 Dur of use --10.408 4.404 -2.363 .046

TABLE 4: Regression ANOVA for P1 Latency (ms) with predictors Age at HA fitting (mos.) and Duration of HA use (mos)., significance of overall model is p = .006, two tailed

Table 4 presents the multiple linear regression analysis results for the prediction of P1 latency from the duration of consistent hearing aid use (in months) and the age in months at the time of the hearing aid fitting. Consistent hearing aid use was considered as wearing the instruments at appropriate gain settings for a minimum of 3 hours each day. Both of these variables were determined to be significant predictors of P1 latency. Shown in Table 5, significant individual correlations with P1 latency were evident for both duration of HA use (r(10) = -.758, p = .003) and the age at HA fitting (r(10) = .724, p = .006). Unstandardized regression coefficients (B), standard error, significance levels of the F statistic of the overall model as well as the t statistics and p values of the individual predictors; and R and R2 are also displayed. R reflects the magnitude of the correlation in the model and R2 is the coefficient of determination, which gives an estimate of the proportion of variance explained by the model, or the relative predictive power of the model. Sum of Squares and Mean Square are a reflection of the variability in the P1

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latency values. The constant is the Y intercept, or the point at which the regression line crosses the y-axis, while the B values for the predictor variables are the slope, used with the y intercept to calculate the regression prediction. This model produced the following regression prediction equation:

Predicted P1 Latency = 243 ms + 5.2 ms (X1) – 10.4 ms (X2)

X1 = multiply 5.2 ms by age at fit in months

X2 = multiply 10.4 ms by duration of HA use in months

Thus, as indicated by the regression coefficient results, if infants are using hearing aid amplification consistently from a younger age, as duration of consistent use increases, based on this model the P1 latency systematically decreases by 10.4 milliseconds for each additional month of HA use until it reaches an age-appropriate latency. Note that the main predictor of P1 latency in this model is the duration of hearing aid use, explaining 58% of the variance in this sample, while combining both predictors in the model explained 72% of the overall variance (R2

= .720). R for regression was significantly different from zero, F (2,8) = 10.266, p= .006. Post hoc evaluation of the predictive power of age at HA fitting for P1 latency revealed that it was approaching significance, t (10) = 2.034, p = .07. Duration of hearing aid use revealed significant predictive capability for P1 latency, t (10) = -2.363, p = .04.

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CORRELATIONS

P1 Latency (ms) Duration of use Pearson r -.758 Sig. (1-tailed) .003 N 11 Age at HA Fitting Pearson r .724 Sig. (1-tailed) .006 N 11

TABLE 5: Pearson’s r correlation coefficients for Duration of HA use and Age at HA Fitting with P1 latency (ms).

fMRI Results

The fMRI result section consists of representative group maps, a discussion of measurements and outcomes, and special decisions that were made regarding the post-processing. Possible explanations for the variance in the sample will be presented as well as the relationship of this data to prior studies using similar techniques. Figures 16 and 17 show group maps from our sample of HI toddlers. Due to activation in multiple cortical areas, negative and positive BOLD contrasts were mapped separately for greater ease in visualization of anatomical regions.

Positive activation was prominent in frontal regions while negative activation was evident in occipital cortex. The nature of negative BOLD activation has not been fully investigated and is not well understood at the time of this study, and therefore must be interpreted with caution. A study by Martin et al. (Martin, et al., 1999b) concluded that immature vascular system in neonates is the leading factor in determining the polarity of the BOLD signal, and that local cerebral blood flow (CBF) may be the dominant factor in determining the strength of the bold signal. Thus, it is generally believed that significant negative BOLD activation indicates some level or type of hemodynamic action in that region and this is the rationale for including the absolute value or strength of activation in the analysis regardless of negative or positive.

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Auditory cortex activation revealed high variability among hearing impaired subjects. Group maps show only areas that are active in every subject included in the analysis, and group maps generally produce more representative images of the sample responses when all subjects show highly similar activation patterns. Individual subjects in this sample exhibited various pixel counts of auditory activation and in different anatomical regions of auditory cortex. Due to cancellation of non-overlapping areas of BOLD activity within Heschl’s gyrus between subjects, our group maps revealed small but strong areas of visible auditory cortex activation, in spite of the fact that fMRI BOLD maps of individual subject data did, in fact, reveal varied patterns of activation within those auditory regions. Positive BOLD activation was highly consistent among hearing-impaired subjects in a clear pattern within frontal regions, such as medial frontal gyrus and possibly anterior cingulated cortex (Figure 16), which is not typically observed in normal-hearing groups.

Less Activation More Activation

FIGURE 16: Group activation maps of HUSH-fMRI data for 11 hearing impaired infants with sedation, ages 9-24 months, using female speech contrasted with silence for POSITIVE contrasts only. Color overlay represents significant activation with spatial filtering above a threshold of z

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= 1.96, p<0.002, cluster size = 50. Voxels are only highlighted in color if they adjoin at least 2 other voxels that exceed this activation threshold. Activation is overlaid on a gray-scale, T1- weighted image in a pediatric reference frame.

Group maps illustrating negative BOLD activation to speech stimuli in the HI group revealed a pattern primarily consistent with what is generally considered to be the “default mode network”

(Figure 17). The default mode network has been described as a reliable pattern of spontaneous

BOLD fluctuations reflecting activity that occurs during a resting state even in the absence of an extraneous stimulus (Greicius, Krasnow, Reiss, & Menon, 2003; Meindl, et al., 2009), under the influence of sleep, sedation and other altered states of consciousness (Boly, et al., 2008).

Anatomical regions typically identified within the default network include the posterior cingulate cortex, ventral anterior cingluate cortex, hippocampus, and the white matter infrastructure connecting these areas with temporal lobes and precuneus (Teipel, et al., 2009). The “default network” pattern in these group maps is unexpected in light of the presence of significant negative BOLD contrasts within the specified ROI in 8 out of 11 individual subject maps, therefore it may be concluded that the variability of negative BOLD activation patterns in the auditory cortex among subjects was exceedingly high and could not be detected in a group map containing data from all 11 subjects. However, it is noted that significant BOLD activation appears in these group maps within the left inferior frontal gyrus, a region which is known to be associated with deficient phonological processing of speech in deaf listeners (MacSweeney,

Brammer, Waters, & Goswami, 2009).

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Less Activation More Activation

FIGURE 17: Group activation maps of HUSH-fMRI data for 11 hearing impaired infants with sedation, ages 9-24 months, using female speech contrasted with silence for NEGATIVE contrasts only. Color overlay represents significant activation with spatial filtering above a threshold of z = 1.96, p<0.002, cluster size = 50. Voxels are only highlighted in color if they adjoin at least 2 other voxels that exceed this activation threshold. Activation is overlaid on a gray-scale, T1-weighted image in a pediatric reference frame.

Comparison of fMRI and AEP Results

Responses to the following research questions will be presented in this section:

Research Question 3

Is there a relationship between the latency of the P1 auditory evoked potential response and residual auditory cortical function as shown by fMRI activation maps in moderate or severe to profoundly hearing impaired subjects?

Research Question 4

Is there evidence of cross-modal plasticity in children with enlarged or robust P1 positivity?

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Several components of the auditory evoked potential response were analyzed in relationship to fMRI BOLD activated pixel counts. The initial hypothesis in this study theorized that P1 latency would demonstrate a correlation with BOLD activation pixel counts within auditory cortex. It was surprising that fMRI pixel count did not exhibit a significant relationship with P1 latency

(r(10) = .038, p = .456), and that no observable pattern was observed in the data (Figure 18).

Relationship between P1 Latency and fMRI Activation in Auditory and Language Areas 700

600

500

400

300 Activated Pixels 200

100

0 0 50 100 150 200 250 300 350

P1 Latency (ms)

FIGURE 18: Scatterplot representing the relationship between P1 Latency (ms) and fMRI activation in activated pixels, demonstrating no significant correlation at r(10) = -.038, p = .456.

It was noteworthy that fMRI pixel count held an inverse relationship with the amplitude of the

P1 response (rS = -.85, p = .001). However, a borderline significant age effect appeared

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alongside this conclusion which was evident with both fMRI pixel count (r(10) = -.498, p = .059), as well as a significant relationship of chronological age with P1 amplitude (r(10) = .723, p =

.006). This age effect could explain the relationship observed between fMRI pixel count and P1 amplitude. Due to the non-linear nature of the amplitude/activation relationship, that correlation analysis was converted to a Spearman’s r tested at the p = .05 level of significance. See Figure

19 for a scatterplot display with a trendline.

Relationship between P1 Amplitude and fMRI Activation in Auditory and Language Areas 700

600

500

400

300

Activated Pixels 200

100

0 012345678

P1 Amplitude (mV)

FIGURE 19: Scatterplot representing the relationship between P1 Amplitude ( V) and P1 Latency (ms) demonstrating a negative correlation of rS = -.85, p = .001. Smaller areas of fMRI BOLD were consistent with larger P1 amplitudes. KEY: Diamonds: Propofol sedation for fMRI; Squares: Nembutal sedation for fMRI scan; Circles: Sevoflourane sedation for fMRI scan.

Correlation maps were constructed which illustrate within-subjects hemodynamic group activation most corresponding with P1 latency. First, a Z statistic image of P1 latency-related

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differences was calculated and normalized across the group by subtracting the group mean and dividing by the group standard deviation. The resulting images were then summed and divided by the square root of the number of subjects. This analysis effectively performs a correlation of between-subjects activation differences and P1 latency at each voxel. This gave a “P1 latency- weighted” Z-score image for the group with a threshold of z > 1.96 and significant clusters defined according to extent (p < .002). The areas showing significant positive correlation with

P1 latency were overlaid onto individual high-resolution T1-weighted scans in a pediatric reference frame.

Negative Positive

FIGURE 20: Correlation maps between HUSH- fMRI Activation and P1 Latency (ms) for 11 hearing impaired infants with sedation, ages 9-24 months, using female speech contrasted with silence. Color overlay represents significant activation with spatial filtering above a threshold of z = 1.96, p<0.002, cluster size = 50. Voxels are only highlighted in color if they adjoin at least 2 other voxels that exceed this activation threshold. Activation is overlaid on a gray-scale, T1- weighted image in a pediatric reference frame.

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Figure 20 identifies clusters of brain activation in which a positive correlation or change with P1 latency was observed. Several frontal areas appeared in these images, including the left middle frontal gyrus and the inferior frontal gyrus, which includes Brodmann’s area 44 and 45 or

Broca’s area. This is a site that is known to be involved in speech perception and semantic tasks such as syntactic and phonological processing, and word retrieval. In addition, regions encompassing the insula and once again, the anterior cingulate cortex appeared in these maps as correlates of P1 latency, as well as the majority of occipital cortex bilaterally.

P1 Latency in milliseconds

FIGURE 21: Correlation scatterplot illustrating increased occipital cortex activation intensity (z-score) with delayed P1 latencies (milliseconds).

An area of strong correlation between positive BOLD activation and P1 latency in ms is detected in the visual cortex, represented by a region of interest selected within the occipital cortex. As

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further support for this relationship, the correlation scatterplot seen in Figure 21 illustrates a strong positive correlation between P1 latency measured in auditory cortex and visual cortex activation intensity as represented by voxel-wise z-scores (r(10) = .72, p = .01). This relationship suggests that longer or more delayed P1 latencies may correspond with increased occipital or visual cortex activation intensity.

Chapter Five: DISCUSSION

The vasculature of the cerebral cortex is intricately involved in a synergistic relationship with cortical neuronal networks, which facilitates nerve signal transduction and sensory information processing. Human functional brain imaging detects metabolic local and regional changes in blood flow and oxygen consumption and replenishment that appears to indirectly reflect the activity of nearby neuronal populations involved in relevant sensory and motor functions. The interaction between vascular and neural networks in cortical and subcortical areas involved in sensory processing has been described in animal studies as a matching of local neural activity and blood flow and regulation of neural firing thresholds through coordinated signaling of the glial cells providing support, insulation, and nutrition to the neurons (Nedergaard, Ransom, &

Goldman, 2003). The principal goal of functional neuroimaging is to generate a graphic representation of hemodynamic events that are believed to be associated with neuronal activity within a functional cortical network. The primary purpose of this research was to investigate the relationship between P1 auditory evoked potential response and fMRI BOLD activation in the auditory cortical regions. A number of conclusions and theories drawn from this study may be discussed as a result of the cortical activity observed in hearing impaired toddlers.

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BOLD Activation patterns in the hearing impaired toddler

It is well established that severe/profound hearing-impaired children process sound stimulation differently compared to normal hearing children. Patterns of cortical responses to sensory stimuli have been shown to be significantly different in the human infant brain than in adults or older children (Anderson et al., 2001). It may be possible to understand the nature of auditory cortex activity by investigating literature that describes brain responses to visual sensory input.

In particular, it has been noted that negative BOLD activation is a frequently observed response to sensory input in the infant cortex (Born et al., 2000; Born et al., 1998). Recent findings indicate that negative BOLD signals may actually result from increased neuronal activity and the interaction between hemodynamics and metabolism, particularly in cases of pathological sensory or cortical function (Schridde, et al., 2008). This is consistent with prior work suggesting that the negative signal change may arise from an imbalance between oxygen demands and an inability of the infant cerebral vasculature to meet the immediate need for increased blood flow, leading to temporary deoxygenation of the area (Meek, et al., 1998). This may explain the phenomenon seen in the present study, in which only a few infants express positive auditory

BOLD activation while the majority exhibit negative signal changes (Anderson et al., 2001).

Based on this concept, this study considers the absolute magnitude of the BOLD response, whether it is positive or negative activation.

Blood oxygenation effects may vary between subjects, which is problematic because fMRI assumes that regional cerebral blood flow is normally regulated. Group data may permit stronger inferences than individual data, however, special care should be taken when auditory system function differs within a sample. Due to variability in responsive areas, group activation

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may be difficult to evaluate because the common activated areas may be small or diffuse.

Regional blood flow in the hearing impaired toddlers of this sample exemplifies this point, demonstrating large areas of scattered activation outside of auditory cortex, but little to no responsivity within auditory cortex on the group maps, in spite of significant activation within auditory regions observed on the maps of the individual subjects. This observation appears consistent with theories about cortical reorganization, neuronal recruitment, and multi-modal involvement in the processing of sensory inputs in cases of developmental auditory deprivation

(Allman, Keniston, & Meredith, 2009; Kral, 2007; Sharma, Gilley, Dorman, & Baldwin, 2007).

Several activated regions outside of auditory cortex were evident which included positive BOLD within the medial frontal gyrus and anterior cingulate cortex, and negative BOLD responses in the inferior frontal gyrus. These areas in deaf subjects appear to be involved in attentional processing of auditory stimuli (Crottaz-Herbette & Menon, 2006) and activity in these regions suggests preattentive detection of auditory target stimuli in subjects (Sevostianov, Fromm,

Nechaev, Horwitz, & Braun, 2002). In fact, PET studies have shown that activation within the anterior cingulate increases with duration of deafness in post-lingually deafened adults (Lee, et al., 2003). Anterior cingulate cortex involvement in this population of deaf infants is important to consider as a possible reflection of top-down attentional modulation and control of auditory inputs. Areas that were shown to possess a positive correlation with P1 latency included the left middle frontal gyrus and inferior frontal gyrus, the anterior cingulate, and bilaterally in insular and occipital areas. The positive correlation between P1 and these areas suggests that as P1 latency decreases with auditory system maturation, activation within these areas external to the auditory cortex also decreases. As demonstrated in prior research on fMRI activation to auditory

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stimulation in the developing brain, this network is vastly different from what is typically observed in normal-hearing infants (Anderson et al., 2001; Holland, Smith et al., 2008).

At the outset of this research, it was hypothesized that maturational changes in the development of the P1 auditory evoked potential in severe to profoundly hearing-impaired toddlers, based on auditory stimulation via hearing aid amplification would be reflected as having a positive correlation with fMRI BOLD activation within the auditory cortical and association areas.

Evaluation of this hypothesis unexpectedly revealed no systematic relationship between the two measures in this sample. This altered the direction of the study as well as the initial hypothesis regarding the relationship of the development of the P1 response with auditory BOLD activation.

The lack of an observable relationship between these two correlates could suggest wide variability in the possible patterns of responses in the developing hearing-impaired auditory system, which has not been well characterized. The key factor in this finding is that auditory evoked potentials and fMRI activation patterns could offer different and unrelated pieces of evidence regarding auditory system status that are both vital and clinically valuable in describing auditory cortical function in deaf children.

Auditory pathways: Brainstem to cortex interactions

Cortical evoked potentials have been established as a reflection of age-related postnatal developmental changes based on sensory experience. The P1 auditory evoked potential has been extensively studied as a maturational index of auditory status in normal hearing infants and toddlers as well as children with cochlear implants (Ponton, Eggermont, Kwong et al., 2000;

Sharma et al., 1997). It has generally been agreed upon that a highly susceptible period of

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auditory neurodevelopment spans early childhood up until approximately age 3.5, and that intervention with a cochlear implant prior to this time period is likely to result in significant and global changes to auditory cortical function within a 6 month time frame (Sharma, Dorman,

Spahr et al., 2002). However, very little is known about auditory cortical maturation as a result of hearing aid amplification prior to cochlear implantation, and the contribution of auditory exposure via hearing aids during the first year of life. Because of the relationships observed between the P1 latency and the age of hearing aid fitting as well as the duration of hearing aid use, findings in this study suggest that hearing aid amplification may play a significant role in priming the auditory system for input.

P1 latencies in this sample of subjects supported early intervention due to a strong relationship with the age of hearing aid fitting (r(10) = -.724, p = .006). Thus, infants that were successfully fitted with amplification at earlier stages of development showed shorter P1 latencies that were closer to being within normal range for their age-norms. However, in spite of this powerful correlation between P1 latency and age at HA fitting, the regression analysis in this sample revealed that the age at hearing aid fitting (t (10) = 2.034, p = .07) did not contribute as significantly to regression as duration of hearing aid use (t (10) = -2.363, p = .04). This could be due to a combination of factors such as the narrow age window in the sample (ages 9-24 months), or the plateau of delayed P1 latencies at around 300 ms. However, they are both strongly related and when considered together, were determined to possess powerful predictive capability of auditory maturational status in severe to profoundly hearing impaired toddlers age

9-24 months who are also hearing aid users.

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In the current study, subjects with smaller areas of auditory fMRI BOLD activation demonstrated larger amplitude P1 peaks, while subjects with larger areas of activation revealed smaller amplitude peak waveforms as shown in Figure 16 (rS = -.85, p = .001). However, the finding is difficult to interpret in light of a possible effect of chronological age on the results of this correlation analysis. P1 amplitude has been identified as having strong age-related maturational shifts in normal-hearing individuals (Ventura, Costa Filho, & Alvarenga Kde, 2009), increasing in magnitude throughout the first year of life to a peak amplitude at approximately 12 months of age, and subsequently decreasing throughout adulthood (Wunderlich, Cone-Wesson, &

Shepherd, 2006). On the other hand, these maturational shifts in P1 amplitude have not been studied in the hearing impaired population. In order to determine if an age effect of P1 amplitude exists in hearing impaired children in the same fashion as normal-hearing children, normative data must be collected and age-morns established in this population. In the current sample, it appears that an age effect does exist with p1 amplitude, as demonstrated by a significant correlation of (r(10) = .723, p = .006). It is also interesting to note a slight age effect associated with fMRI activations which did not reach significance was observed as well, (r(10) = -

.498, p = .059), which could indicate a maturational shifting of anatomical regions with growth and development.

Early childhood, particularly infancy is known to be a time of vast developmental changes in the structure and function of the brain. Increases in glucose metabolism and brain volume (Chugani,

1998; Courchesne, et al., 2000) as well as significant modulation of synaptic density

(Huttenlocher & Dabholkar, 1997) and changes in grey matter thickness (Giedd, et al., 2006) could contribute to variability in the functional and location of the neuroanatomical sites

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involved in P1 processing. Additionally, thalamocortical connections exhibit considerable developmental changes throughout childhood as projections to the auditory cortex are established and strengthened (Moore & Linthicum, 2007). In spite of the possible age or maturational influence, it is still worth mentioning that the relationship observed is a negative or inverse correlation, with robust P1 amplitudes being associated with the smallest auditory activations in the sample, and vice versa. Although this finding of an inverse correlation between P1 amplitude and fMRI activation is counterintuitive, if the analysis withstands with age or maturational status as a covariate, it may support the possibility of a modified or impaired feedforward inhibitory process that could be related to a sensory gating deficit resulting from auditory deprivation and reorganization of thalamocortical projections from the geniculate body to primary sensory areas.

Inhibitory gating, a basic central nervous system process for filtering repetitive sensory information, may have implications for understanding the regulation of brainstem and thalamic input to the auditory cortex of the hearing impaired child. Auditory information from the inferior colliculus in the brainstem is routed to the medial geniculate body in the thalamus for processing and relay to various parts of the primary auditory cortex. Additionally, afferent connections from the auditory thalamus synapse directly on inhibitory interneurons within the lateral nucleus of the amygdala, providing evidence of an auditory feedforward inhibitory process initiating in thalamo-amygdala connections (Woodson, Farb, & Ledoux, 2000). Alterations in phase locking and lowered gating ratios in subjects with decreased ERP amplitudes may be a contributing factor in observations of sensory gating deficits; however, no conclusive findings have been identified.

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Cross-Modal Interactions and Plasticity

In the past, it was commonly believed that sensory processing occurred in a unimodal fashion involving separate and discrete neural pathways with no cross-communication among sensory modalities. Many current investigations have illustrated examples of crossover among sensory inputs at multiple levels from brainstem to cortex as evidence of a multi-modal sensory system.

Little is known about multi-modal processing in the developing auditory system during infancy, particularly involving deafness.

This study observed a significant relationship between auditory maturational status and occipital cortex activations in response to auditory inputs, suggesting the possibility of a transitional period during which a partially stimulated pathway gradually becomes less reliant on visual cortex for processing of communication-related inputs. The idea of redundant connectivity between auditory and visual brain regions, particularly during developmental stages, is not a new concept and has been demonstrated using auditory event related potentials in hearing infants

(Neville & Bavelier, 2002). A number of animal studies have established transitory, developmental cross-modal projections extending from primary and secondary auditory areas to both ipsilateral and contralateral visual areas (Bronchti et al., 2002; Cappe & Barone, 2005;

Clarke & Innocenti, 1990; Falchier et al., 2002; Innocenti, Berbel, & Clarke, 1988). Studies in blind individuals have reported occipital or visual cortex activation in response to auditory stimuli using evoked potentials (Alho, Kujala, Paavilainen, Summala, & Naatanen, 1993; Kujala,

Alho, Paavilainen, Summala, & Naatanen, 1992; Kujala, et al., 1995), which was subsequently was observed in sighted subjects as well (Romei, Murray, Cappe, & Thut, 2009; Wu, Weissman,

Roberts, & Woldorff, 2007).

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Auditory occipital activations as seen in these subjects are not often reported in deaf individuals, however, activations in visual cortex in response to sound have been observed in cochlear implant patients using PET scans (Giraud & Truy, 2002), and fMRI activation is evident within occipital regions in response to pure tone stimulation in subjects with sensorineural hearing loss

(Zhang, Geng, Zhang, Li, & Zhang, 2006). In addition, similar patterns of frontal and occipital activations were detected in postlingually deafened cochlear implant users with persistent temporal discrimination difficulties (Mortensen, Madsen, & Gjedde, 2005). The mechanism by which auditory stimuli would be received by visual cortex in deaf individuals is not well understood, however, a neural system experiencing sensory deprivation appears to make advantageous use of the redundancy within these multiple pathways, as they may provide an alternate route for signal transmission and reception. Animal studies have revealed that thalamocortical projections for every thalamic nucleus, including those involved in generation of the P1 response have patterns of distribution to multiple fields in different cortical areas (Huang

& Winer, 2000). Evidence of neuronal recruitment and sensory reorganization in multi-modal regions in deaf subjects has expanded into an extensive knowledge base; for a review, see (Kral,

2007).

P1 auditory evoked potentials have been extensively investigated in pediatric populations, in normally hearing subjects, hearing-impaired subjects, and in cochlear implant users (Eggermont et al., 1997; Sharma, Dorman et al., 2002b); and the progression of its developmental trajectory with auditory experience, deprivation, and subsequent intervention with cochlear implants has been well characterized. However, the relationship between the maturation of the P1 response

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and cross-modal interactions such as occipital activity has not been investigated. Six out of eleven subjects in the study exhibited P1 latencies that were within normal limits for age norms, these six subjects all had at least 6 months of consistent hearing aid use and exhibited less occipital cortex activation in response to auditory inputs than subjects who had later P1 latencies and less hearing aid experience.

Because P1 latency offers an indication of auditory maturational status, findings in this study could imply that as hearing impaired toddlers gain experience or stimulation through the auditory modality via amplification or cochlear implants, the auditory pathways become more adept at handling inputs and routing signals appropriately for communication. It is possible that the decreases in P1 latency following the initiation of a therapeutic intervention with a hearing device also result in an altered recruitment of sensory cortices. The range of P1 outcomes evident in this study lend strength to our conclusions, as we were able to perform a direct correlation between hearing aid experience and characteristics of the P1 response, as well as fMRI activation within specific brain regions.

Limitations

Several practical concerns with the methodology of the study may restrict the generalization if its results. The primary confounding issue considered is the need for the use of sedation to obtain fMRI in this age population. Prior research has shown that it is possible to obtain some level of reduced activation of the primary and association auditory cortices under anesthesia in normal hearing subjects (Plourde et al., 2006) as well as in hearing impaired children (Patel et al.,

2007b) however, it would be difficult to identify the impact of the sedation levels on the auditory cortex activation in each individual subject. Every effort was made to use uniform procedures in

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sedating these subjects for their scans, but the findings in this study involving fMRI activation must be interpreted in light of the possible impact of sedation.

It should also be mentioned that 7 out of 11 subjects received P1 testing on the same day that they were sedated for the fMRI scan, although there was a time lapse of at least 3 hours between cessation of sedation and initiation of P1 recordings, which should have been sufficient to eliminate a possible sedation effect. According to recent anesthesiology research, the MMN and

N100 exhibit sedation related changes that are less evident during stages of recovery when the subject is awake, but the P1 response is unaffected and remains unchanged during and after propofol sedation (Heinke, et al., 2004; Ypparila, Karhu, Westeren-Punnonen, Musialowicz, &

Partanen, 2002). Nevertheless, P1 data from subjects who had been sedated earlier on the same day received careful attention to ensure that a possible effect was not observable in the data.

The severity of hearing loss in individual subjects presents an additional challenge to interpreting fMRI data. In some cases, producing a stimulus of sufficient loudness to reach the subject’s hearing thresholds and without the risk of exceeding the child’s comfort levels is complicated.

The child is under sedation and unable to respond behaviorally, therefore no indication of auditory discomfort during the test would be evident. Additionally, no behavioral indication is apparent that the child is able to perceive the stimulus. Therefore, if no visible auditory activation is present in a particular child’s imaging data, it is possible that they were unable to hear it, or that the sedation influenced the recordings. However, every infant in this study exhibited significant auditory cortex activations. Only 3 out of 11 subjects had very small regions of auditory activation but this activation was strong.

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As shown in our individual data, hearing deficits produce a wide variation of altered BOLD activation patterns between subjects. Group data allow for more powerful inferences than individual data, however, when BOLD effects are different from subject to subject, group map results are difficult to evaluate. BOLD fMRI assumes that regional cerebral blood flow is normally regulated and only the areas that are activated in every subject in the sample are visible on a group map. Therefore, the group activation would be underestimated because the common activated areas were quite small. Group data that is more homogenous, or similar among subjects, would have demonstrated greater activation, but it would be difficult to justify including only subjects with similar activation patterns in a sample for a group map representing auditory function in HI children, when this population is known to exhibit dramatically variable patterns of BOLD activation.

The need for a combination of purposive and convenience sampling should be considered as an intrinsic challenge in this study design. Since it is unethical to sedate a subject purely for purposes of research, in order to complete the study it was necessary to take only subjects who needed to be sedated for an anatomical MRI for medical reasons. The functional component would then be added during the same session as the MRI ordered by the physician. Therefore, many of our subjects were likely to have exclusion criteria or developmental/anatomical factors that would influence the study. Every effort was made to include subjects that did not exhibit grossly abnormal patterns of development. This factor also contributed to the smaller than desired sample size (n = 11).

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Implications for future research

A primary goal in validating the use of fMRI in infants and toddlers is reduction of the effects of sedation on auditory cortex responsivity. It is of great concern to determine appropriate types and dosage levels of sedation to elicit the least possible effect on auditory BOLD activity and proper methods of interpreting responses from a developing auditory cortex under sedation. A limitation of this study arises from the use of different sedation techniques for scanning procedure. These different sedation techniques might be contributing to the observed variability in activation and may impact the correlation of fMRI activation in the A1 ROI with P1 latency, which was determined to be insignificant in the results section. However, despite this variability in the study, the correlations between A1 activation with P1 amplitude (Figure 15) and occipital activation with P1 latency (Figure 17) are convincing. In fact, these correlations appear to transcend the influences of sedation, duration of deafness, and other confounds.

Due to wide variability among subjects, group data does not reflect an accurate representation of auditory cortical function in hearing impaired population. For this reason, it is necessary to develop techniques for evaluating individual data for the purposes of identifying specific patterns of cortical reorganization and longitudinal follow up of patients with short term and long term damage to auditory pathway structures. fMRI has the potential to assist in earlier diagnosis , prognosis, and characterization of recognizable patterns of auditory neuromaturation which may be invaluable to clinicians in treatment planning and patient/family counseling. Advancement of fMRI techniques will improve the reliability and sensitivity of individual data in order to position fMRI as a more useful clinical application. Future research should focus on manipulating stimulus parameters and analysis methods to enhance the quality of fMRI in individual subjects.

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Clinical applicability of fMRI as well as cortical AEP’s may eventually be determined by the challenges presented by the test procedures in a realistic clinical setting. The reality of collecting

P1 responses in this very young age population may be difficult to overcome. If it is possible for technical advances to reduce the length of time required for the testing and improve the method of delivering the stimulus and collecting responses with greater ease, it will become more feasible to train clinicians in the routine use of this valuable technique. New methods have already been developed for removing stimulus artifact due to cochlear implants, for continued monitoring of auditory neural function following the installation of a cochlear implant. (Gilley et al., 2006)

Additional studies of P1 development will be required in order to confirm the findings in the present work. A larger number of subjects with various characteristics related to duration of deafness and hearing aid use would be helpful in supporting conclusions related to predictive power and outcomes. Follow-up studies of speech and language outcomes with the present subjects are currently in progress to search for relationships between P1 development and subsequent communication outcome. It would be of interest to retrospectively investigate the pre-cochlear implant auditory experience with hearing aids in subjects whose P1 responses were measured at various post-CI stages. Intensive research is required in order to study relationships between auditory cortical activation and organization prior to cochlear implantation as well as auditory/language outcomes at various stages following cochlear implantation.

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Conclusions

Universal newborn hearing screening programs have revolutionized hearing healthcare for infants and toddlers, and have yielded a variety of new clinical issues, challenges, and concerns for pediatric audiologists. The changed circumstances surrounding routine early identification also involves new parents who are dealing with learning about deafness and hearing aid use as well. The possibility of developing useful ways to objectively identify potential sources of prognostic information regarding auditory maturation and the effects of acoustic or electrical stimulation in the developing deaf infant or toddler is very desirable. Functional MRI and auditory evoked potentials can both provide valuable information regarding auditory maturational status, and hopefully further support for the vital importance of effective delivery of auditory inputs to the developing brain of the hearing impaired child during the period prior to cochlear implantation.

These results demonstrate a significant relationship between the P1 auditory evoked potential and BOLD activation to speech stimuli in hearing impaired infants and toddlers. Furthermore, the P1 latency is significantly related to early auditory sensory experience, which suggests a possible effect of auditory stimulation on the fMRI BOLD response patterns in deafness. A noteworthy component of these findings is that despite the presence of severe to profound congenital deafness, more than half of subjects revealed P1 latencies that were within normal limits, and several with near normal peak latencies. It is striking that all of the subjects demonstrating normal or near normal peak waveforms had been consistent hearing aid users for more than 6 months. To date, this phenomenon has been demonstrated in prior research with

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older children who are cochlear implant users (Ponton, Don, Eggermont, Waring, Kwong et al.,

1996; Sharma, Dorman et al., 2005), but not in infant hearing aid users.

Tremendous interest is arising in the P1 auditory evoked potential as an objective assessment of cortical maturation and a measure of the efficacy of hearing aid use prior to cochlear implantation. Findings in the current study suggest that cortical maturation resulting from auditory experience and stimulation from hearing aid amplification occurs even during the first year of life prior to cochlear implantation, and this exposure may be vitally important to later communication development. We hope the findings in the current study may lead to improved guidance in aural rehabilitation; therapeutic approaches, outcome verification, and clinical decisions for a positive impact on parental attitudes and compliance with recommendations regarding consistent hearing aid or cochlear implant use.

Currently, the techniques of cortical auditory evoked potentials as well as fMRI of auditory activation have not yet reached the level of routine clinical use. However, swiftly expanding technical advances in available magnetic resonance systems, capabilities of imaging centers, and a widespread international interest in developing this area of research is significantly improving the precision of this technique. The opportunity provided by fMRI and evoked potentials to analyze response patterns in cortical areas prior to and following auditory stimulation could be used in conjunction established cochlear implantation assessment batteries. With further development of fMRI acquisition strategies (Schmithorst, et al, 2003), and sedation procedures, this imaging technique could potentially become a useful diagnostic tool in the evaluation of the

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effects of auditory deprivation and electrical stimulation on auditory cortical function and maturation.

In order to support service delivery to very early-identified deaf children, it will be important to emphasize the need for multi-disciplinary collaboration in pediatric cochlear implant centers. A comprehensive assessment battery for childhood deafness which would include a neuroimaging component will require the establishment of an efficient clinical relationship between the audiology and otology community with neuroradiologists that have functional imaging expertise.

Training programs within these disciplines will need to take into account the new circumstances in pediatric hearing healthcare and provide opportunities for development of an infant centered approach for both diagnostics and intervention. Clear guidelines and practice patterns in the appropriate use of evoked potential and fMRI techniques may ultimately lead to improved quality of life for pediatric hearing aid and cochlear implant users and their families.

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Appendices Appendix A

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Appendix B

Risk Factors for auditory system dysfunction

Family history of permanent congenital or childhood hearing loss Craniofacial anomalies Transient or persistent middle ear dysfunction for at least 3 months History of bacterial meningitis Trisomy 21 Pierre Robin Syndrome CHARGE Syndrome Hunter Syndrome Carcot-Marie-Tooth Syndrome Stickler Syndrome Goldenhar Syndrome Rubinstein-Taybi Syndrome Head trauma Ototoxicity Low birthweight Respiratory distress, hypoxic/anoxic/ischemic injury Bronchopulmonary dysplasia >36 days of mechanical ventilation or extracorporeal membrane oxygenation (ECMO) Hyperbilirubin at a level requiring exchange transfusion

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Appendix C Individual subject waveform displays **All audiometric measures reported were administered binaurally in the sound field.

Subject 1

Subject 1: A 16-month-old Caucasian female who was fitted with bilateral amplification at age

6 months and had 9 months of consistent hearing aid use. Her language abilities were estimated at the 8 to 10 month range of age ability. This subject received the /ba/ stimulus in the left ear via insert earphone, because she did not have her hearing aids on site and was scheduled for cochlear implantation the next morning.

Aided PTA Aided SRT Unaided SAT Threshold at 500 Hz Aided at 500 Hz 60 55 85 90 55

143

Subject 2

Subject 2: A 12-month-old African American male who was fitted with amplification at age 4 months for a total of 8 months experience with hearing aids. His language abilities were estimated at the 8 to 10 month range of age ability. This subject received the /ba/ stimulus in the right ear via insert earphone, because he was not tolerating the hearing aid during the procedure.

Aided PTA Aided SRT Unaided SAT Threshold at 500 Hz Aided at 500 Hz 50 55 80 70 35

144

Subject 3

Subject 3: A 10-month-old Caucasian female who was fitted with amplification at age 3 months for a total duration of 7 months of hearing aid use. Her language abilities were estimated at the 4 to 6 month range of age ability. This subject received the /ba/ stimulus via sound field speakers with a hearing aid on the right ear.

Aided PTA Aided SRT Unaided SAT Threshold at 500 Hz Aided at 500 Hz 70 50 75 90 60

145

Subject 4

Subject 4: A 22 month old Caucasian female who was fitted with amplification at age 15 months and had 7 months of hearing aid use. Her language abilities were estimated at the 14-16 month range of ability. This subject received the /ba/ stimulus via sound field speakers with a hearing aid on the left ear.

Aided PTA Aided SRT Unaided SAT Threshold at 500 Hz Aided at 500 Hz 60 45 75 80 55

146

Subject 5

Subject 5: A 16-month-old Caucasian male who was fitted with amplification at age 4 months and had 12 months of hearing aid experience. His language abilities were estimated at the 16 to

18 month range of ability. This subject received the /ba/ stimulus via sound field speakers with a hearing aid on the left ear.

Aided PTA Aided SRT Unaided SAT Threshold at 500 Hz Aided at 500 Hz 60 50 85 115 55

147

Subject 6

Subject 6: A 9-month-old Caucasian male who was fitted for amplification at age 3 months and had 6 months of hearing aid experience. His language abilities were estimated at the 6 to 8 month range of ability. This subject received the /ba/ stimulus via insert earphone in the left ear because he was not tolerating the hearing aid during the procedure.

Aided PTA Aided SRT Unaided SAT Threshold at 500 Hz Aided at 500 Hz 70 50 85 100 70

148

Subject 7

Subject 7: A 15 month old Hispanic female who was 6 months old when she was fitted with amplification and had 9 months of hearing aid use. Her language abilities were estimated at the

18-20 month range of ability. This subject received the /ba/ stimulus via insert earphone in the left ear because the hearing aid was non-functional during the procedure.

Aided PTA Aided SRT Unaided SAT Threshold at 500 Hz Aided at 500 Hz 55 50 75 80 55

149

Subject 8

Subject 8: An 11 month old Caucasian female who was fitted for amplification at the age of 10 months old and had less than 1 month of hearing aid use. Her language skills were estimated at the 4 to 6 month range of ability. This subject received the /ba/ stimulus via sound field speakers with a hearing aid on the right ear (the montage was reversed during the procedure due to noisy recordings).

Aided PTA Aided SRT Unaided SAT Threshold at 500 Hz Aided at 500 Hz 65 60 90 110 55

150

Subject 9

Subject 9: A 24 month old Caucasian female who was fitted for amplification at the age of 21 months old and had 3 months of hearing aid use. Her language abilities were estimated at the 10 to 12 month range of ability. This subject received the /ba/ stimulus via sound field speakers with a hearing aid on the left ear.

Aided PTA Aided SRT Unaided SAT Threshold at 500 Hz Aided at 500 Hz 60 45 85 100 45

151

Subject 10

Subject 10: A 12 month old Caucasian male who was fitted fro amplification at the age of 10 months and had 2 months of hearing aid experience. His language skills were estimated at the 4 to 6 month range of ability. This subject received the /ba/ stimulus via sound field speakers with a hearing aid on the right ear (the montage was reversed during the procedure due to noisy recordings).

Aided PTA Aided SRT Unaided SAT Threshold at 500 Hz Aided at 500 Hz 55 50 85 95 50

152

Subject 11

Subject 11: A 10 month old Caucasian female who was fitted for amplification at 3 months of age and had 7 moths of hearing aid use. Her language abilities were estimated at the 4 to 6 month range of ability. This subject received the /ba/ stimulus via sound field speakers with a hearing aid on the left ear.

Aided PTA Aided SRT Unaided SAT Threshold at 500 Hz Aided at 500 Hz 60 70 85 80 35

153