The Effect of Cognitive Load on Distractor Interference

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THE EFFECT OF COGNITIVE LOAD ON DISTRACTOR INTERFERENCE

MICHAEL KING

Submitted in partial fulfillment of the requirements for the degree of

Master of Arts

Department of Psychological Sciences

CASE WESTERN RESERVE UNIVERSITY

May, 2018 1

CASE WESTERN RESERVE UNIVERSITY

SCHOOL OF GRADUATE STUDIES

We hereby approve the thesis/dissertation of

Michael J. King

candidate for the degree of Master of Arts*.

Committee Chair

Brooke N. Macnamara, PhD

Committee Member

Heath Demaree, PhD

Committee Member

Robert Greene, PhD

Date of Defense

December 15, 2017

*We also certify that written approval has been obtained

for any proprietary material contained therein. 2

Table of Contents

Abstract 3

Introduction 4

Experiment 1 8

Experiment 2 18

Experiment 3 28

Experiment 4 31

General Discussion 38

Appendix 44

References 65

The Effect of Cognitive Load on Distractor Interference

Abstract

MICHAEL J. KING

Goal oriented attention is necessary to successfully ignore irrelevant distractors. When do distractors in our visual environment capture attention, interfering with goal-directed behavior, and when are distractors successfully ignored? To answer this question, a series of experiments was conducted investigating the effect of distraction under different types and amount of cognitive load. I found limited evidence supporting load theory (Lavie,

1995; 2004) that under low perceptual load, distraction interference is higher as compared to high load, whereas, under short-term memory load and working memory load distraction interference increases as load amount increases. Findings were inconsistent across experiments, suggesting that load theory is not a sufficient explanation for distractor processing.

Our ability to ignore distracting stimuli and maintain goal-directed attention is largely influenced by the demands of the task at hand. The extent to which distractors capture our attention influences how well we perform in a variety of everyday tasks whether driving a car, shooting a free throw in basketball, or taking an exam. In addition, many occupational tasks (e.g., air traffic control, working as a SWAT team member, airport baggage screening) demand high levels of vigilance and focused attention in order to prevent distraction. This research seeks to increase understanding of goal-directed attention during visual processing by investigating how different types of cognitive load affect our ability to ignore distractors.

Load theory (Lavie, 2005) argues that as perceptual load increases it consumes perceptual capacity and leads to reduced distractor processing, whereas working memory load reduces the ability to exert priority-based executive cognitive control over the task and results in increased distractor processing. Consistent with this theory, in one experiment Konstantinou, Beal, King, and Lavie (2014) found that presenting distractors during information encoding—thereby increasing perceptual load—when the memory maintenance set was large (high load), reduced distractor processing relative to when the maintenance set was small (low load), while in another experiment they found that presenting distractors during memory maintenance—thereby increasing working memory load—when the memory maintenance set was large (high load), increased distractor processing relative to when the maintenance set was small (low load). They concluded that high perceptual load reduced the amount of attentional capacity available resulting in the distractors not being captured by attention, while high working memory load reduced the cognitive control available to direct attention resulting in the distractors being 5

captured by attention. This conclusion is in line with others' findings on the role of

cognitive resources and distractor interference. For example, Conway, Cowan, and

Bunting (2001) found that individuals with high working memory capacity were less

likely to detect their names being spoken in an irrelevant message relative to individuals

with low working memory capacity, suggesting that those with low attentional resources

were unable to inhibit processing the irrelevant information. However, other studies have

found that distractors are more likely to be processed when cognitive resources are

available. For example, Forester and Lave (2007) found that people who report being

more distracted in everyday life show more distractor interference in tasks of low

perceptual load, but not in tasks of high load when perceptual capacity is more consumed

(see also, Benoni & Tsal, 2010, 2012, 2013; Brand-D’Abrescia & Lavie, 2007; Wilson et al., 2011).

Load Theory and Dilution

Research testing distractor interference under perceptual load generally supports the idea that the relevant perceptual processing demands determine the extent of processing for irrelevant information—i.e., as relevant processing demands increase, irrelevant processing decreases (e.g., Lavie, 1995; Lavie & Cox, 1997; Lavie et al.,

2004). However, a controversial explanation rivaling perceptual load theory has been put forward, suggesting that the reduction in distraction under high perceptual load is due to greater dilution of the distractor (Benoni & Tsal, 2010, 2012, 2013; Tsal & Benoni, 2010;

Wilson et al., 2011). According to this view, high perceptual load conditions are associated with reduced distractibility simply because the distractors compete with the additional relevant non-targets in high load displays (memory load information), rather 6 than exhaustion of attentional capacity under high perceptual load. Whereas both theories assume that distractors are more likely to be processed under high load conditions, the main difference between the load and dilution model is in the mechanisms underlying perceptual processing.

Load theory suggests that cognitive control functions, particularly working memory, are critical in late information processing selection (Lavie, 2010; Lavie et al.,

2004). Following this view, working memory plays a key role in maintaining attentional priorities, so that target and distractor-related information remain clearly separated in processing, and goal oriented behavior can successfully direct attention toward task- relevant information. In contrast, dilution involves a process of early selection (as compared to late selection). Following this view, whether or not a distractor is processed depends on perceptual characteristics of the visual display. As such, the dilution model makes no speciﬁc predictions regarding the result of distracting information that is not excluded from perceptual processing. Tsal & Benoni (2010) suggest that any additional increase in the load on attentional resources should reduce the likelihood that attentional resources spill over to the distractors. Following this view, an increase in attentional load, even when it does not affect perceptual task aspects, should be associated with reduced distractor processing.

Generally, in work using manipulations of working memory load during selective attention, there is much evidence that processing of task-irrelevant information is increased when working memory load is high, implying that cognitive control plays a role in the active filtering of distracting information (de Fockert, 2013). The effect of working memory on selective attention has been demonstrated in Stroop-type tasks, 7

where the distractor is associated with one of the task responses, but also in tasks in

which the distractor cannot lead to response activation, suggesting that the effect of

working memory has an early locus in attention (de Fockert, 2013). In contrast, there are

also examples in which high working load has not led to an increase in distractor processing during selective attention. These include situations in which the content of the working memory task overlaps with the processing of the distractor (rather than the target) in selective attention (e.g., Kim et. al., 2005). For example, high working memory load involving maintaining a set of letters leads to greater processing of the irrelevant color of a Stroop color word when the meaning of the word has to be attended (and the color ignored) and leads to reduced processing of the irrelevant word when the color has to be attended (and word meaning ignored) (Park et al., 2007). In contrast, high load on a

working memory task for spatial location has no effect on distractor processing in either

case (Kim et al., 2005; de Liaño et al., 2010). Distractor processing may be more likely to

increase under high working memory load when distractors are likely to cause

interference, either because they are associated with a task-relevant response, or because

they have an intermediate level of salience or occur unpredictably from trial to trial (de

Fockert, 2013). These ﬁndings imply that working memory can be loaded for a speciﬁc

stimulus type, and that this type has to overlap with target processing in order to lead to an increase in distractor processing.

Current Studies

The research presented here has three major objectives. The first objective is to

conduct a modified replication of a study supporting load theory, where increasing perceptual load leads to reduced distractor processing and increasing short-term memory 8

and working memory load leads to increased distractor processing. The second objective is to address methodological inconsistencies found in working memory load distraction research. These inconsistencies may have resulted in discrepancies as to whether or not

increases in working memory load reduces the ability to exert priority-based executive

cognitive control resulting in increased distractor processing. The third objective is to

investigate the role of cognitive control on distractor interference independent of memory

maintenance, to dissociate the roles of working memory and cognitive control during

goal directed selective-attention. The overarching goal is to provide key information on

the effects of different types of load on distractor interference in visual processing.

Experiment 1

The purpose of Experiment 1 was to attempt to replicate findings from previous

studies supporting load theory (Cartwright-Finch & Lavie, 2007; Chen, & Cave, 2013;

Forster & Lavie, 2008; Konstantinou et al., 2014; Lavie, 2014). This was done by

adapting the general experimental paradigm used by Konstantinou et al. (2014).

In Konstantinou et al. (2014), four separate experiments were conducted—one

examining perceptual load, two examining visual short-term memory load, and one examining verbal working memory load—that were compared to one another as though they were conditions within an experiment. In contrast, the present Experiment 1 utilized a within subjects, repeated-measures design that simultaneously tested the effects of cognitive load amount, cognitive load type, and their interaction on distractor processing.

In other words, one experiment was conducted instead of several in order to compare across conditions and appropriately examine interactions.

Method

Participants

Sixty PSCL 101 students at Case Western Reserve University participated in

exchange for partial course credit. Ten participants were not included in analyses due to accuracy rates lower than 50%.

Apparatus and Stimuli

The experiment was controlled using the open source application PsychoPy

(Peirce, 2007) on a 2014 9020 all-in-one Dell Optiplex desktop computer with a 15-in.

CRT monitor (90-Hz refresh rate). A viewing distance of 60 cm was maintained with a chinrest. Experimental trials consisted of a memory set and a target letter with or without a distractor letter.

Perceptual load condition. The memory set for the perceptual load condition consisted of a visual array of one (low load) or four (high load) shapes randomly placed on a transparent 3 × 3 grid (1.38° × 1.38°) at the center of the screen. The shapes differed from the stimuli (an array of colored squares) used in Konstantiou et al. (2014) in order to resemble the stimuli used in the other load conditions of this experiment. Surrounding the grid were 6 dots subtending 0.6° × 0.4° to form a circle. A target letter (either a “Z” or an

“N”) appeared in place of one of the 6 dots creating the circle. For two thirds of the low- load trials and two third of the high-load trials, a distractor letter (a “Z” or “N”, subtending 1° × 0.6°) was simultaneously presented on the left or right side of the screen, outside the perimeter of the memory set array. Half of these were incongruent with the target letter and half were congruent with the target letter. For the remaining third of the low- and high-load trials there was no distractor letter (control condition). This visual 10

array appeared on the screen for 150 ms. Following the visual array, a screen with a

question mark placed in the center appeared during which participants were tasked with

pressing the '1' key if the target letter was a 'Z' and the '2' key if the target letter was an 'N'

within 1,850 ms. Following this screen, a 2,000 ms retention period appeared.

Participants were then presented with a single shape for 3,000 ms and were asked if it

was one of the shapes presented during that trial's memory set. Participants responded by

pressing the 'S' key for yes and the 'A' key for no. Participants had 3,000 ms to respond.

Participants heard a beep if they responded incorrectly to the memory set probe.

Participants completed 2 blocks of 60 trials in the perceptual load condition. See Figure

Figure 1. Experimental paradigm for Experiment 1 perceptual load trials. High load (left)

and low load (right) with an incongruent (top), congruent (middle), or no (control; bottom) distractor letter.

Visual short-term memory condition. The memory set for the visual short-term

memory load condition consisted of a visual array of one (low load) or four (high load)

meaningless symbols randomly placed in any of six dots arranged in a circle of 2° in

radius centered at fixation, remaining on screen for 500 ms. These symbols were based

on the symbols used in Konstantinou et al. (2014)—straight black lines from capital

letters "shuffled" to create meaningless shapes. Participants were instructed to maintain 12 these symbols in visual memory by imagining them staying on the screen throughout the trial. Following a 1,850 ms retention period, a target letter (either a “Z” or an “N”) appeared in place of one of 6 dots creating a circle. For two thirds of the low-load trials and two third of the high-load trials, a distractor letter (a “Z” or “N”, subtending 1° ×

0.6°) was simultaneously presented on the left or right side of the screen, outside the perimeter of the memory set array. Half of these were incongruent with the target letter and half were congruent with the target letter. For the remaining third of the low- and high-load trials there was no distractor letter (control condition). This visual array appeared on the screen for 150 ms. Participants were tasked with pressing the '1' key if the target letter was a 'Z' and the '2' key if the target letter was an 'N' within 1,850 ms.

Participants were then presented with a single figure in place of one of the 6 dots and were asked if it was presented during that trial's memory set. Participants responded by pressing the 'S' key for yes and the 'A' key for no. Participants had 3,000 ms to respond.

Participants heard a beep if they responded incorrectly to the memory set probe.

Participants completed 2 blocks of 60 trials in the perceptual load condition. See Figure

Figure 2. Experimental paradigm for Experiment 1 visual short-term memory (VSTM) trials. High load (left) and low load (right) with an incongruent (top), congruent (middle), or no (control; bottom) distractor letter.

Verbal working memory condition. The memory set for the verbal working- memory load condition consisted of a visual array of one (low load) or six (high load) letters randomly placed in any of six dots arranged in a circle of 2° in radius centered at

fixation, remaining on screen for 500 ms. Participants were instructed to maintain these

letters in memory by mentally rehearsing them throughout the trial. Following a 1,850 ms

retention period, a target letter (either a “Z” or an “N”) appeared in place of one of the 6 14

dots creating the circle. For two thirds of the low-load trials and two third of the high-

load trials, a distractor letter (a “Z” or “N”, subtending 1° × 0.6°) was simultaneously

presented on the left or right side of the screen, outside the perimeter of the memory set

array. Half of these were incongruent with the target letter and half were congruent with

the target letter. For the remaining third of the low- and high-load trials there was no

distractor letter (control condition). This visual array appeared on the screen for 150 ms.

Participants were tasked with pressing the '1' key if the target letter was a 'Z' and the '2' key if the target letter was an 'N' within 1,850 ms. Participants were then presented with a single letter in place of one of the 6 dots and were asked if it was presented during that trial's memory set. Participants responded by pressing the 'S' key for yes and the 'A' key for no. Participants had 3,000 ms to respond. Participants heard a beep if they responded incorrectly to the memory set probe. Participants completed 2 blocks of 60 trials in the perceptual load condition. See Figure 3.

Figure 3. Experimental paradigm for Experiment 1 verbal working memory trials. High load (left) and low load (right) with an incongruent (top), congruent (middle), or no

(control; bottom) distractor letter.

Procedures

Each participant provided IRB-approved written informed consent. Participants completed the perceptual load block, the visual short-term memory block, and the verbal working memory condition block following a Williams Design Latin Squares ordering method. Trials within each block were presented in a random order. Participants read 16

instructions and completed 24 practice trials prior to each block. The experiment took

approximately 1 hour and 30 minutes.

Results

Konstantinou et al. calculated the congruency effect (incongruent reaction times –

congruent reaction times) as an estimate of distractibility. I calculated the incongruency

effect (incongruent reaction times – control reaction times) because congruent distractor

letters may facilitate reaction times. A 2 × 3 repeated measures ANOVA on the

incongruency effect was conducted.

There was a significant main effect of congruency type (see appendix, Table 5),

F(2,98) = 11.2, p <.001. The incongruency effect for high load trials (M = .026, SE =

.022) was marginally significantly higher than the incongruency effect for low load trials

(M = -.013, SE = .014), F(1,52) = 4.085, p = .048, partial η2 = .073. Short-term memory

load (M=.014, SE=.017), working memory load (M=.001, SE=.026), and perceptual load

(M = .006, SE = .017) congruency effects did not differ significantly, F(2, 104) = .161, p

= .851, partial η2 = .003. Cognitive load type and amount did not significantly interact,

F(2, 104)=.466, p=.629, partial η2 = .009. See Figure 4.

Figure 4. Graph depicting incongruency effect, incongruent – control reaction times

(RTs) for Experiment 1.

Discussion

The results of Experiment 1 indicated that participants are more, not less, distracted under high perceptual load than low perceptual load and that there was no significant interaction between cognitive load type and amount. Thus, Experiment 1 failed to replicate the findings from Konstantinou et al. (2014) and other research supporting perceptual load theory (Cartwright-Finch & Lavie, 2007; Chen, & Cave,

2013; Forster & Lavie, 2008; Konstantinou et al., 2014; Lavie, 2014).

What explains this discrepancy? It is possible that the difference in results is due to Konstantinou et al.'s (2014) less-than-ideal methodology. Konstantinou et al. (2014) 18 conducted individual experiments with a different load type per experiment, but compared across the experiments as though they were conditions within a single experiment. Their sample sizes were also small across experiments, as low as 13 participants in an experiment. The present study's results could be due to sampling error.

Another possibility is that experiencing prior conditions—the repeated measures design used—interfered with subsequent conditions in Experiment 1, although this is unlikely due to the differing types of stimuli used in the memory set for each type of cognitive load (perceptual load = shapes, visual short-term memory = symbols, working memory = letters). Finally, the effect could be stimulus-specific. That is, the pattern that conflicts with Konstantinuou et al.'s results—the perceptual load condition—is the one condition where I did not replicate Konstantinou et al.'s stimuli. Konstantinou et al. used an array of colored squares instead of the black shapes I used in the present study to better match the stimuli in the other conditions.

Experiment 2

Experiment 2 sought again to test the roles of cognitive load amount and type on distractor interference. Two major methodological changes were implemented. First, to de-confound stimuli with condition, I created consistent stimuli thorough the entirety of the experiment. Memory sets of colored squares and their locations on a grid, were used for perceptual, visual short-term memory, and working memory load types to manipulate cognitive load. The colored squares replicates Konstantinou et al.'s stimuli for their perceptual load experiment and one of their VSTM experiments. Second, working memory was operationalized by a mental rotation 90º clockwise of the colored squares in the memory set array. This manipulation is more consistent with the working memory 19

literature, as compared to mental rehearsal of letters, which is more in line with short-

term memory (Hyun & Luck, 2007).

Methods

Participants

Fifty eight PSCL 101 students at Case Western Reserve University participated in

exchange for partial course credit. Five participants were not included in data analysis

due to error rates greater than 50%.

Apparatus and Stimuli

The experiment was controlled using the open source application PsychoPy

(Peirce, 2007) on a 2014 9020 all-in-one Dell Optiplex desktop computer with a 15-in.

CRT monitor (90-Hz refresh rate). A viewing distance of 60 cm was maintained with a

chinrest. Experimental trials consisted of a memory set and a target letter with or without

distractor letters.

Perceptual load condition. The memory set of the perceptual load condition

consisted of a visual array of one (low load) or four (high load) different colored squares

randomly placed on a transparent 3 × 3 grid (1.38° × 1.38°) at the center of the screen.

Surrounding the grid were 6 dots subtending 0.6° × 0.4° to form a circle. A target letter

(either a “Z” or an “X”) appeared in place of one of the 6 dots creating the circle. For two

thirds of the low-load trials and two third of the high-load trials, a distractor letter (a “Z”

or “X”, subtending 1° × 0.6°) was simultaneously presented on the left or right side of the

screen, outside the perimeter of the memory set array. Half of these were incongruent

with the target letter and half were congruent with the target letter. For the remaining

third of the low- and high-load trials there was no distractor letter (control condition). 20

This visual array appeared on the screen for 150 ms. Following the this, a screen with a question mark placed in the center appeared during which participants were tasked with pressing the 'Z' key if the target letter was a 'Z' and the 'X' key if the target letter was an

'X' within 1,850 ms. Following this screen, a 2,000 ms retention period appeared.

Participants were then presented with a single colored square for 3,000 ms and were asked if it was one of the squares presented during that trial's memory set, in both color and location. Participants responded by pressing the '1' key for yes and the '2' key for no.

Participants had 3,000 ms to respond. Participants heard a beep if they responded incorrectly to the memory set probe. Participants completed 2 blocks of 60 trials in the perceptual load condition. See Figure 5.

Figure 5. Experimental paradigm for Experiment 2 perceptual load trials. High load (left)

and low load (right) with an incongruent (top), congruent (middle), or no (control;

bottom) distractor letter. For the memory set, different colored squares were chosen at random from blue, cyan, green, magenta, pink, red, and yellow (represented as different shades of grey here).

Visual short-term memory condition. The memory set of the visual short-term

memory load condition consisted of a visual array of one (low load) or four (high load)

different colored squares randomly placed on a transparent 3 × 3 grid (1.38° × 1.38°) at

the center of the screen, remaining on screen for 500 ms. Participants were instructed to 22

maintain the color and location of these squares in visual memory throughout the trial.

Following a 1,850 ms retention period, a target letter (either a “Z” or an “X”) appeared in

place of one of 6 dots creating a circle. For two thirds of the low-load trials and two third of the high-load trials, a distractor letter (a “Z” or “X”, subtending 1° × 0.6°) was simultaneously presented on the left or right side of the screen, outside the perimeter of the memory set array. Half of these were incongruent with the target letter and half were congruent with the target letter. For the remaining third of the low- and high-load trials there was no distractor letter (control condition). This visual array appeared on the screen

for 150 ms. Participants were tasked with pressing the 'Z' key if the target letter was a 'Z'

and the 'X' key if the target letter was an 'X' within 1,850 ms. Participants were then

presented with a single colored square for 3,000 ms and were asked if it was one of the

squares presented during that trial's memory set, in both color and location. Participants responded by pressing the '1' key for yes and the '2' key for no. Participants had 3,000 ms to respond. Participants heard a beep if they responded incorrectly to the memory set probe. Participants completed 2 blocks of 60 trials in the perceptual load condition. See

Figure 6.

Figure 6. Experimental paradigm for Experiment 2 visual short-term memory (VSTM)

trials. High load (left) and low load (right) with an incongruent (top), congruent (middle), or no (control; bottom) distractor letter. For the memory set, colored squares were chosen

from blue, cyan, green, magenta, pink, red, and yellow (represented as different shades of

grey here).

Working memory condition. The memory set of the working memory load

condition consisted of a visual array of one (low load) or four (high load) different

colored squares randomly placed on a transparent 3 × 3 grid (1.38° × 1.38°) at the center 24 of the screen, remaining on screen for 500 ms. Participants were tasked with maintaining the color and location of these squares in visual memory, while also mentally rotating the set 90º clockwise during the trial. Following a 1,850 ms retention period, a target letter

(either a “Z” or an “X”) appeared in place of one of 6 dots creating a circle. For two thirds of the low-load trials and two third of the high-load trials, a distractor letter (a “Z” or “X”, subtending 1° × 0.6°) was simultaneously presented on the left or right side of the screen, outside the perimeter of the memory set array. Half of these were incongruent with the target letter and half were congruent with the target letter. For the remaining third of the low- and high-load trials there was no distractor letter (comparison condition). This visual array appeared on the screen for 150 ms. Participants were tasked with pressing the 'Z' key if the target letter was a 'Z' and the 'X' key if the target letter was an 'X' within 1,850 ms. Participants were then presented with a single colored square for

3,000 ms and were asked if it was one of the squares presented during that trial's memory set, in both color and location, after rotating the set 90º counter-clockwise. Participants responded by pressing the '1' key for yes and the '2' key for no. Participants had 3,000 ms to respond. Participants heard a beep if they responded incorrectly to the memory set probe. Participants completed 2 blocks of 60 trials in the perceptual load condition. See

Figure 7.

Figure 7. Experimental paradigm for Experiment 2 working memory trials. High load

(left) and low load (right) with an incongruent (top), congruent (middle), or no (control; bottom) distractor letter. For the memory set, colored squares were chosen from blue, cyan, green, magenta, pink, red, and yellow (represented as different shades of grey here).

Procedures

Each participant provided IRB-approved written informed consent. Participants completed the perceptual load block, the visual short-term memory block, and the 26

working memory block following a Williams Design Latin Squares ordering method.

Trials within each block were presented in a random order. Participants read instructions

and completed 24 practice trials prior to each block. The experiment took approximately

1 hour and 30 minutes.

Results

A 2 × 3 repeated measures ANOVA on the incongruency effect (incongruent

reaction times – control reaction times) was conducted. There was a significant main effect of congruency type (see appendix, Table 6), F(2,98) = 6.71, p =.002. The incongruency effect for high load trials (M = .048, SE = .013) was higher, but not- significantly different than the incongruency effect for low load trials (M = -.041, SE =

.011), F(1,49) = .480, p = .492, partial η2 = .01. The ANOVA revealed a significant effect

of cognitive load type, F(2, 98) = 5.22, p = .007, partial η2 = .096. The incongruency

effect for short-term memory load (M = .063, SE = .014), was higher than in working

memory load (M = .047, SE = .013), and perceptual load (M = .023, SE = .013). These

findings were qualified by a borderline significant interaction between cognitive load

type and amount F(2, 98) = 3.234, p = .044, partial η2 = .062. This finding is consistent

with load theory findings (Lavie, 2005). These results show that under perceptual load,

participants are more distracted under low load than high load, under short-term memory

load participants are more distracted under high load than low load, and under working

memory load participants are more distracted under high load than low load. See Figure

Figure 8. Graph depicting incongruency effect, incongruent – control reaction times

(RTs) for Experiment 2.

Discussion

Results from the perceptual load condition in Experiment 2 differed starkly from that of Experiment 1. While Experiment 2 findings are consistent with perceptual load theory (Lavie, 2014), Experiment 1 found the opposite effect. This may be due to the differing types of stimuli used in the memory set for each type of cognitive load in

Experiment 1. Another possible explanation of these contrasting findings may be the differing types of stimuli used for perceptual load between Experiments 1 and 2 (black shapes vs. colored squares) However, Lavie (2014) tested perceptual load in three separate experiments, each utilizing a different type of stimuli in the memory set 28

(Experiment 1 contained letters, Experiment 2 contained colored squares, and Experiment

3 contained ambiguous characters) and found the same perceptual load effect in all three.

Experiment 3

Given that the major difference in results between E1 and E2 was the pattern observed for load amount in the perceptual load condition, the purpose of Experiment 3 was to replicate the methods and directly compare the perceptual load conditions from

Experiment 1 and 2. If both of the perceptual load conditions result in opposite findings, as was found in Experiment 1 and 2, respectively, then I can conclude that differing stimuli are causing opposite effects. However, if the results converge on one effect, I will conclude that one results was due to sampling error and come to a consensus on whether or not a perceptual load effect is found using the current methodology.

Methods

Participants

Sixty three PSCL 101 students at Case Western Reserve University participated in exchange for partial course credit. Four participants were not included in data analysis due to error rates greater than 50%.

Apparatus and Stimuli

The experiment was controlled using the open source application PsychoPy

(Peirce, 2007) on a 2014 9020 all-in-one Dell Optiplex desktop computer with a 15-in.

CRT monitor (90-Hz refresh rate). A viewing distance of 60 cm was maintained with a chinrest. Experimental trials consisted of a memory set and a target letter with or without distractor letters. 29

The perceptual load conditions were identical to the perceptual load conditions

found in Experiment 1 and Experiment 2. See Figure 1 and 4.

Procedures

Each participant provided IRB-approved written informed consent. Participants completed the perceptual load block, and the cognitive control block following a

Williams Design Latin Squares ordering method. Trials within each block were presented in a random order. Participants read instructions and completed 24 practice trials prior to each block. The experiment took approximately 45 minutes.

Results

A 2 × 2 repeated measures ANOVA on the incongruency effect (incongruent reaction times – control reaction times) was conducted. There was a significant main effect of congruency type (see appendix, Table 7), F(2,116) = 9.13, p <.001. The incongruency effect for high load trials (M = .042, SE = .188) was similar to the

congruency effect for low load trials (M = .074, SE = .191), F(1,58) = 1.721, p = .195,

partial η2 = .029. Experiment 1-method perceptual load (M=.056, SE=.020), and

Experiment 2-method perceptual load (M = .060, SE = .017) incongruency effects did not

differ significantly, F(1,58) = 0.41, p = .840, partial η2 = .01 Perceptual load type and

amount did not significantly interact, F(1, 58)= 1.77, p= .187, partial η2 = .03. See Figure

9. 30

Figure 9. Graph depicting incongruency effect, incongruent – control reaction times

(RTs) in Experiment 3.

Discussion

The results from the Experiment 1-method perceptual load condition differed

from the results found in Experiment 1. Whereas the incongruency effect increased with

load amount in Experiment 1, the opposite was found in Experiment 3. Supporting load

theory, I found that distractor interference was larger under low cognitive load, as

compared to high cognitive load.

The results from the Experiment 2-method perceptual load condition also differed

from the results found in Experiment 2. In Experiment 2, my findings supported 31

perceptual load theory, whereas distractor interference was larger under low cognitive

load than high cognitive load. Replicating the same methods in Experiment 3, I found

that there was no effect of load amount on the congruency effect under perceptual load.

While using the same methodology from previous experiments, both perceptual

load conditions failed to replicate the effects found in Experiments 1 and 2. While it is

possible that random error is influencing the current results, the magnitude of

Experiment’s 1-3 sample size as compared to previous research that finds a congruency

effect in perceptual load (Benoni & Tsal, 2010, 2012, 2013; Brand-D’Abrescia & Lavie,

2007; Konstantinou et al., 2014; Lavie, 2014) indicates that this is not a likely

explanation. The stark differences in findings across multiple experiments while utilizing

the same methodology, suggests that the perceptual load incongruency effect is not

reproducible.

Experiment 4

While perceptual load effects were inconsistent across studies, Experiments 1 and

2 were consistent with the finding that as working memory load increases distraction interference increases as well. The same effect was also found for visual short-term memory load. However, in both of these studies visual short-term memory had numerically larger distraction interference effects across load amount than when under working memory load. In other words, it appears that under visual short-term memory load distractors are slightly, though not significantly, more difficult to ignore, as compared to working memory load. This seems counterintuitive as working memory load conditions include an added manipulation requiring more cognitive effort than is required 32

for visual short-term memory conditions. Lavie (2005) attributes the effect of distraction on working memory load to a reduction in the ability to exert priority-based executive cognitive control over the task. Visual short-term memory conditions do not include a manipulation of cognitive control, which should allow for more cognitive control resources to be allocated towards ignoring irrelevant distractors, as compared to working memory load. It may be that any amount of attention directed at memory maintenance

(regardless if it is working memory or some other form of cognitive control) interferes with goal directed attention, resulting in higher distractor processing as maintenance demands increase. However, if it is a reduction in cognitive control resources due to higher load demands that results in increased distraction, then the same effect should also be found if distractors are presented during goal-directed information encoding instead of maintenance.

The purpose of Experiment 4 was to investigate the role of cognitive control on distractor interference independent of memory maintenance. To this end, I designed an experiment where participants were tasked with ignoring distractors during a visual search task. If distractor interference increases with search set size, we can conclude that the depletion of cognitive control resources is the source for increased distraction. On the other hand, if distractor interference decreases with search set size, we can conclude that attentional resources may be more impactful on distraction and goal-directed attention than the specific type of cognitive load.

Method

Participants 33

Sixty three PSCL 101 students at Case Western Reserve University participated in

exchange for partial course credit. Four participants were not included in data analysis

due to error rates greater than 50%. Participants in Experiment 4 were the same

participants from Experiment 3.

Apparatus and Stimuli

The experiment was controlled using the open source application PsychoPy

(Peirce, 2007) on a 2014 9020 all-in-one Dell Optiplex desktop computer with a 15-in.

CRT monitor (90-Hz refresh rate). A viewing distance of 60 cm was maintained with a chinrest. Experimental trials consisted of a memory set and a target letter with or without distractor letters.

Perceptual load condition. The memory set of the perceptual load condition

included a visual display consisting of either 2 (low cognitive load) or 6 (high cognitive

load) colored shapes. One of these shapes was always in a circle, while the other(s) were

always in diamond(s). Inside each shape was a black line. Inside the circle, the line was

always oriented either vertically or horizontally. Inside the diamonds the line was always

slightly tilted in any orientation other than vertically or horizontally. In half of the trials

all of the shapes around the black lines, including the circle, are green (distractor-absent condition). For the other half of the trials, all shapes were green except one diamond, which was red (distractor-present condition). The participant’s task was to search each visual display for the circle among the diamond(s) and indicate the orientation (vertical or horizontal) of the line inside of the circle. The display was presented for 150 ms, after which the participant had 1,850 seconds to make a response. The participant pressed the up arrow key if the line was vertical, and the left arrow key if it was horizontal. The 34

participants were instructed to make their response as quickly as possible. If the

participant responded incorrectly or failed to make a response then a short beeping noise was played in their headphones. Participants completed 2 blocks of 60 trials in the

perceptual load condition. See Figure 10.

Figure 10. Experimental paradigm for perceptual load trials for Experiment 4. High load

(left) and low load (right) with a distractor present (top) or absent (bottom). The outline

of the diamonds and circle were green (represented as black here), and the outline of the

distractor diamond was red (represented as a dotted black line here).

Cognitive control condition. The memory set of the cognitive control conditions was identical to the perceptual load conditions except that the display remained on the screen until either a response was made, or 4,000 ms passed. See Figure 11.

Figure 11. Experimental paradigm for cognitive control trials. High load (left) and low load (right) with a distractor present (top) or absent (bottom). The outline of the diamonds and circle were green (represented as black here), and the outline of the distractor diamond was red (represented as a dotted black line here).

Procedures

Each participant provided IRB-approved written informed consent. Participants completed the perceptual load block, and the cognitive control block following a

Results

A 2 × 2 repeated measures ANOVA on the incongruency effect (incongruent reaction times – control reaction times) was conducted. The incongruency effect for high

load trials (M = .008, SE = .004) was similar to the congruency effect for low load trials

(M = .010, SE = .003) (see appendix, Table 8), F(1,58) = .192, p = .663, partial η2 = .033.

The incongruency effect on cognitive control load trials (M = .015, SE = .035) was

significantly higher than the incongruency effect for perceptual load trials (M = .003, SE

= .025), F(1,58) = 8.213, p = .006, partial η2 = .124. Cognitive load type and amount did

not significantly interact, F(1, 58)=.243, p=.625, partial η2 = .004. See Figure 12.

Figure 12. Graph depicting incongruency effect, incongruent – control reaction times

(RTs) for Experiment 4.

Discussion

While non-significant, the results from the cognitive control condition in experiment 4 are consistent with the results from the working memory conditions in

Experiments 1 and 2. As cognitive load increases, the incongruency effect increases

suggesting there is more interference from irrelevant distractors under high load than low load while cognitive control resources are being depleted. However, the difference in the incongruency effect from high to low load in Experiment 4 was very minor, suggesting that there is more interference from irrelevant distractors while cognitive control 38

mechanisms are being used during memory maintenance as compared to information

encoding.

The results from the perceptual load condition in Experiment 4 were non-

significant, and inconsistent with the results found in Experiments 1-3. Cognitive load

amount appeared to have no effect on congruency effect for perceptual load. This

suggests that using the methodology in Experiment 4, where participants detected a

colored singleton among distractors, distractor interference affects performance equally

regardless if the perceptual load amount is high or low.

General Discussion

The presented research aimed to advance our understanding of the underlying cognitive mechanisms involved in visual processing and elucidate how these mechanisms

are affected by varying types of distraction and cognitive load.

In Experiment 1, I adapted the general experimental paradigm used by

Konstantinou et al. (2014) in an attempt to replicate findings from previous studies

supporting load theory (Cartwright-Finch & Lavie, 2007; Chen, & Cave, 2013; Forster &

Lavie, 2008; Konstantinou, et al., 2014; Lavie, 2014). The results from Experiment 1 indicated that participants are more distracted under high perceptual load than low perceptual load, opposing perceptual load theory. In addition, the key interaction between cognitive load type and amount was non-significant, failing to replicate the findings from

Konstantinou et al. (2014) and other research supporting perceptual load theory

(Cartwright-Finch & Lavie, 2007; Chen, & Cave, 2013; Forster & Lavie, 2008;

Konstantinou, et al., 2014; Lavie, 2014). I concluded that these differential findings may 39

be attributed to methodological issues, within experiment interference, or possible

random error.

Experiment 2 again tested the roles of cognitive load amount and type on

distractor interference with the purpose of producing effects found in load theory research. However, two methodological changes from Experiment 1 were implemented.

One, I created consistent stimuli throughout the entirety of the experiment in order to de-

confound stimuli with condition. Memory sets of colored squares and their locations on a

grid, were used for perceptual, visual short-term memory, and working memory load types to manipulate cognitive load. Two, working memory was operationalized by a mental rotation of the colored squares in the memory set array 90º clockwise. This manipulation is more consistent with the working memory literature, as compared to mental rehearsal of letters, which is more in line with short-term memory (Hyun & Luck,

2007). A significant effect of cognitive load type was found. The incongruency effect for short-term memory load was higher than in working memory load and perceptual load.

The key interaction between cognitive load type and amount was significant. These results show that under perceptual load, participants are more distracted under low load than high load, under short-term memory load participants are more distracted under high load than low load, and under working memory load participants are more distracted under high load than low load. My findings in Experiment 2 were consistent with perceptual load theory (Lavie, 2014), whereas in Experiment 1 I found the opposite effect. A potential reason for these opposing findings was due to the differing types of stimuli used in the memory set for each type of cognitive load in Experiment 1. 40

Therefore, in Experiment 3, I replicated the methods from the perceptual load conditions in Experiment 1 and 2. This was done to come to a consensus on whether or not a perceptual load effect is found using the current methodology or whether the patterns were stimuli-specific. The results from the Experiment 1-method perceptual load

condition in Experiment 3 differed from the results found in Experiment 1. Whereas the

incongruency effect increased with load amount in Experiment 1, the opposite was found

in Experiment 3. Supporting load theory, I found that distractor interference was larger

under low cognitive load, as compared to high cognitive load. The results from the

Experiment 2-method perceptual load condition in Experiment 3 also differed from the

results found in Experiment 2. In Experiment 2, my findings supported perceptual load

theory, whereas distractor interference was larger under low cognitive load than high

cognitive load. Replicating the same methods in Experiment 3, I found that there was no

effect of load amount on the congruency effect under perceptual load. The failure to

replicate suggests that the incongruency effect for perceptual load is not a consistent

effect. While Type II error is a possibility, the shift in pattern and direction, along with

sample sizes approximately 400% of Konstantinou et al.'s suggests that the effect of

perceptual load on distractor interference is not a reproducible effect.

In Experiments 1-3 I found inconsistent perceptual load effects. However,

Experiments 1 and 2 were consistent with the finding that as working memory load increases, distraction interference increases. The same effect was consistently found for visual short-term memory as well. Counterintuitively, in both of these studies visual short-term memory, which does not contain a cognitive control component, had

numerically larger distraction interference effects across load amount as compared to 41

working memory load, which contains a cognitive control component. It may be that any

amount of attention directed at memory maintenance (regardless if it is working memory

or some other form of cognitive control) interferes with goal directed attention, resulting

in higher distractor processing as maintenance demands increase. However, if it is a

reduction in cognitive control resources due to higher load demands that results in

increased distraction, then the same effect should also be found if distractors are

presented during goal-directed information encoding instead of maintenance. Thus, in

Experiment 4 I tested the role of cognitive control on distractor interference independent

of memory maintenance using an experiment where participants were tasked with

ignoring distractors during a visual search task. This required cognitive control resources

to ignore distractors during a selective attention task, while not requiring the maintenance

of a memory load.

The results from the cognitive control condition in Experiment 4 were consistent

with the results from the working memory conditions in Experiments 1 and 2: as

cognitive load increases, the incongruency effect increases numerically. This suggests

that there is more interference from irrelevant distractors under high load than low load

while cognitive control resources are being depleted. However, the difference in the

incongruency effect from high to low load in Experiment 4 was very minor and non- significant, suggesting that there is more interference from irrelevant distractors while cognitive control mechanisms are being used during memory maintenance as compared to information encoding. The results from the perceptual load condition in Experiment 4 were non-significant, and inconsistent with the results found in Experiments 1-3.

Cognitive load amount appeared to have no effect on congruency effect for perceptual 42

load. This suggests that using the methodology in Experiment 4, where participants

detected a colored singleton among distractors, distractor interference affects

performance equally regardless if the perceptual load amount is high or low.

Load theory (Lavie, 2005) argues that as perceptual load increases it consumes

perceptual capacity and leads to reduced distractor processing, whereas working memory

load reduces the ability to exert priority-based executive cognitive control over the task

and results in increased distractor processing. While there is a background of published

research that find this effect (Cartwright-Finch & Lavie, 2007; Chen, & Cave, 2013;

Forster & Lavie, 2008; Konstantinou et al., 2014; Lavie, 2014), there is also a camp that refutes this explanation and instead supports a dilution model (Benoni & Tsal, 2010,

2012, 2013; Brand-D’Abrescia & Lavie, 2007; Wilson et al., 2011). Overall, the research investigating both of these theories seem to contain inconsistent results, theoretical explanations, and methodologies.

It appears from the presented research that studies investigating load theory are possibly easily influenced by factors such as methodological issues, or within experiment interference. It may be that other studies' effects are due to Type I error, and the

perceptual load effect is not a true effect. However, the results from Experiment 2, and

the Experiment 3 findings of the replicated methods from Experiment 1 suggest

otherwise. Alternatively, it may be that Type II error is present in this research, and the

perceptual load effect is a true effect. Methodological issues may have also influenced the

results. However, the use of different stimuli and methods from Experiments 1 and 2

produced different results in Experiment 3 while attempting to replicate the findings. 43

Future research should continue to investigate load theory in order to understand

why the effect is found under certain conditions, and why it is not found in others.

Theoretical changes underlying both load theory and the dilution model, as well as the

validity of these theories should be considered. In addition, future research could include eye tracking to observe when eye movements are made to distractors, and when they are not, and compare this information to reaction times to further increase our understanding of when visual distractors actually enter the focus of attention. Importantly, future directions should also utilize meta-analytic methods to rigorously investigate the load theory literature. Meta-analytic moderation analyses and/or publication bias analyses may help us understand why some research finds this effect and why some fails to.

The purpose of load theory is to support how our visual information processing systems behave in real world situations. In order to establish ecological validity, it may be beneficial to first investigate behaviors in real world tasks to understand if these behaviors even support load theory. Applied research specifically aimed at understanding and improving attention during real-world tasks, such as air traffic control, surveillance, and baggage screening should be investigated.

Appendix

Memory Component

A 2 x 3 x 3 repeated measures ANOVA on the Experiment 1 accuracy rates (see

Table 1A) for the memory component was conducted. There was a significant main effect of cognitive load type, F(2,100) = 136.6, p =.002. Pairwise comparisons showed that there was a significant difference in accuracy rates between short-term memory and perceptual

load (p <.001), and between working memory and perceptual load (p <.001). Participants were less accurate on perceptual load trials as compared to short-term memory and working memory trials. There was not a significant difference between short-term memory and working memory (p =.067). There was not a main effect of congruency type, F(2,100) =

2.40, p =.09. There was not an interaction between congruency and cognitive load type,

F(4,200) = 1.67, p = .16.

A 2 x 3 x 3 repeated measures ANOVA on the Experiment 2 accuracy rates (see

Table 2A) for the memory component was conducted. There was a significant main effect of cognitive load type, F(2,104) = 344.3, p <.001. Pairwise comparisons showed that there was a significant difference in accuracy rates between short-term memory and perceptual load (p <.001), between working memory and perceptual load (p <.001), and between short-term memory and working memory (p <.001). Accuracy was higher for short-term

memory load than both working memory and perceptual load. Working memory load

accuracy was higher than perceptual load accuracy. There was not a main effect of

congruency type, F(2,104) = 1.77, p =.18. There was not an interaction between

congruency and cognitive load type, F(4,208) = 2.69, p =.10. 45

A 2 x 2 x 3 repeated measures ANOVA on the Experiment 3 accuracy rates (see

Table 3A) for the memory component was conducted. There was a significant main effect

of cognitive load type, F(1,58) = 103.7, p <.001. Pairwise comparisons showed that there

was a significant difference in accuracy rates between Experiment 1 perceptual load and

Experiment 2 perceptual load (p <.001). Experiment 1 perceptual load was less accurate than Experiment 2 perceptual load. There was not a main effect of congruency type,

F(1,58) = 3.08, p =.09. There was not an interaction between congruency and cognitive load type, F(2,116) = 1.77, p =.18.

A 2 x 2 x 2 repeated measures ANOVA on the Experiment 4 accuracy rates (see

Table 4A) was conducted. There was not a significant main effect of cognitive load type,

F(1,58) = 3.12, p =.09. There was not a main effect of distractor presence F(1,58) = 1.98 ,

p =.16. There was not an interaction between distractor presence and cognitive load type,

F(1,58) = 2.44, p =.12.

Target Letter Component

A 2 x 3 repeated measures ANOVA on the Experiment 1 accuracy rates (see

Table 1C) for the attention component was conducted. There was a significant main effect

of cognitive load type, F(2,100) = 97.2, p <.001. Pairwise comparisons showed that there

was a significant difference in accuracy rates between short-term memory and perceptual

load (p <.001), between working memory and perceptual load (p <.001), and between

short-term memory and working memory (p <.001). Accuracy was higher for working

memory load than both short-term memory and perceptual load. Short-term memory load

accuracy was higher than perceptual load accuracy. There was not a main effect of 46

congruency type, F(2,100) = 2.43, p =.09. There was not an interaction between

congruency and cognitive load type, F(4,200) = 1.59 , p = .18.

A 2 x 3 repeated measures ANOVA on the Experiment 2 accuracy rates (see Table

2C) for the attention component was conducted. There was a significant main effect of

cognitive load type, F(2,104) = 80.8, p <.001. Pairwise comparisons showed that there was a significant difference in accuracy rates between short-term memory and perceptual load

(p <.001), between working memory and perceptual load (p =.014), and between short- term memory and working memory (p <.001). Accuracy was higher for short-term memory load than both working memory and perceptual load. Working memory load accuracy was higher than perceptual load accuracy. There was not a main effect of congruency type,

F(2,104) = 2.21 , p =.11. There was not an interaction between congruency and cognitive load type, F(4,208) = 1.74 , p =.16.

A 2 x 2 repeated measures ANOVA on the Experiment 3 accuracy rates (see Table

3C) for the attention component was conducted. There was a significant main effect of cognitive load type, F(1,58) = 6.15, p =.016. Experiment 1 perceptual load was more accurate than Experiment 2 perceptual load. There was not a main effect of congruency type, F(1,58) = 2.13, p =.15. There was not an interaction between congruency and cognitive load type, F(2,116) = 2.59, p =.08.

Discussion of Accuracy Analyses

The analysis of accuracy rates in the target letter task show that Perceptual Load trials had significantly lower accuracy rates as compared to both Short-term Memory and

Working Memory loads. Importantly, the RT data show that Perceptual load trials had slower reaction times across Experiments 1-2 as compared to Short-term Memory and 47

Working Memory trials, indicating that participants did not forego speed of response for

accuracy or vice-versa. The analysis of accuracy rates for the different congruency types

(incongruent, congruent, control) indicate there is not a significant difference between

incongruent, congruent, or control letters in all four experiments. This suggests that the

reaction time data for congruency types are due to the ability of distractor letters to capture

attention, and not due to difficulty of the task.

Regarding the analysis of accuracy rates for the memory component: Across experiments 1-2, the Perceptual Load trials had significantly lower accuracy rates as compared to both Short-term Memory and Working Memory loads. This is not surprising because the information is flashed very quickly on the screen, making errors more likely.

This appears to reflect task difficulty. Additionally, across Experiments 1-3 the accuracy

analyses on the amount of load (low, high) was significant with high load trials resulting

in lower accuracy rates than low load trials. This also should be the case, because more

information is more difficult to retain than less information.

In the perceptual load literature, the difficulty of the high load conditions are

theorized to be the cause for the smaller congruency effect (incongruent distractor RTs -

control RTs). In other words, the amount of perceptual load is so consuming that distractors

are often not processed, resulting in similar reaction times for incongruent, congruent, and

control trials. In the case of at least Experiment 1, this doesn't seem to be the case. While

the Perceptual Load trials are more difficult, i.e., more errors and slower RTs, than for

other cognitive load types, I did not find the smaller congruency effect under high load as

theorized. Rather, the highest memory set error rates were for the Perceptual High Load 48 trials in Experiments 1 and 2. However, accuracy and response times for the target letters were the same regardless of load amount.

Table 1A

Accuracy Rates for Experiment 1 Memory Component (Included Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Short-term Memory .80 (.02) .89 (.02)

Working Memory .77 (.02) .93 (.01)

Perceptual .71 (.02) .91 (.01) Note. N = 50.

Table 1B

Accuracy Rates for Experiment 1 Memory Component (Excluded Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Short-term Memory .56 (.09) .70 (.08)

Working Memory .48 (.08) .76 (.07)

Perceptual .49 (.06) .72 (.08) Note. N = 10.

Table 1C Accuracy Rates for Experiment 1 Target Letter Response (Included Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Short-term Memory .93 (.01) .91 (.02)

Working Memory .93 (.02) .94 (.02)

Perceptual .90 (.02) .90 (.01) Note. N = 50.

Table 1D

Accuracy Rates for Experiment 1 Target Letter Response (Excluded Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Short-term Memory .69 (.09) .70 (.09)

Working Memory .66 (.10) .79 (.10)

Perceptual .63 (.10) .72 (.09) Note. N = 10.

Table 2A

Accuracy Rates for Experiment 2 Memory Component (Included Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Short-term Memory .88 (.01) .93 (.01)

Working Memory .80 (.02) .92 (.02)

Perceptual .77 (.02) .92 (.02) Note. N = 53.

Table 2B

Accuracy Rates for Experiment 2 Memory Component (Excluded Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Short-term Memory .13 (.10) .49 (.12)

Working Memory .43 (.16) .21 (.17)

Perceptual .45 (.02) .39 (.07) Note. N = 5.

Table 2C

Accuracy Rates for Experiment 2 Target Letter Response (Included Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Short-term Memory .91 (.02) .94 (.02)

Working Memory .91 (.02) .90 (.02)

Perceptual .89 (.01) .91 (.01) Note. N = 53.

Table 2D

Accuracy Rates for Experiment 2 Target Letter Response (Excluded Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Short-term Memory .69 (.18) .36 (.11)

Working Memory .55 (.20) .37 (.14)

Perceptual .45 (.02) .38 (.07) Note. N = 5.

Table 3A

Accuracy Rates for Experiment 3 Memory Component (Included Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Perceptual (Experiment 1) .74 (.02) .88 (.02)

Perceptual (Experiment 2) .77 (.02) .90 (.02) Note. N = 59.

Table 3B

Accuracy Rates for Experiment 3 Memory Component (Excluded Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Perceptual (Experiment 1) .50 (.04) .30 (.07)

Perceptual (Experiment 2) .49 (.05) .34 (.02) Note. N = 4.

Table 3C

Accuracy Rates for Experiment 3 Target Letter Response (Included Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Perceptual (Experiment 1) .89 (.02) .92 (.01)

Perceptual (Experiment 2) .90 (.02) .90 (.01) Note. N = 59.

Table 3D

Accuracy Rates for Experiment 3 Target Letter Response (Excluded Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Perceptual (Experiment 1) .41 (.01) .60 (.02)

Perceptual (Experiment 2) .39 (.09) .49 (.02) Note. N = 4.

Table 4A

Accuracy Rates for Experiment 4 Memory Component (Included Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Perceptual .92 (.02) .93 (.02)

Cognitive Control .92 (.01) .94 (.01) Note. N = 59.

Table 4B

Accuracy Rates for Experiment 4 Memory Component (Excluded Participants)

Load Amount

High Low

Cognitive Load M (SE) M (SE)

Perceptual .49 (.21) .74 (.20)

Cognitive Control .73 (.18) .71 (.19) Note. N = 4.

Table 5A

Experiment 1 Means and Standard Deviations of Individuals’ Median Reaction Times for the Target Letter Response Under High Load

Congruency Cognitive Load Mean (SD)

Congruent Perceptual .89 (.20)

Congruent Short-term Memory .78 (.15)

Congruent Working Memory .75 (.16)

Incongruent Perceptual .92 (.20)

Incongruent Short-term Memory .83 (.17)

Incongruent Working Memory .79 (.17)

Control Perceptual .90 (.21)

Control Short-term Memory .75 (.15)

Control Working Memory .73 (.15)

Note. N = 50

Table 5B

Experiment 1 Means and Standard Deviations of Individuals’ Median Reaction Times for the Target Letter Response Under Low Load

Congruency Cognitive Load Mean (SD)

Congruent Perceptual .87 (.20)

Congruent Short-term Memory .83 (.15)

Congruent Working Memory .76 (.16)

Incongruent Perceptual .91 (.19)

Incongruent Short-term Memory .86 (.14)

Incongruent Working Memory .77 (.16)

Control Perceptual .88 (.18)

Control Short-term Memory .80 (.15)

Control Working Memory .73 (.15)

Note. N = 50

Table 6A

Experiment 2 Means and Standard Deviations of Individuals’ Median Reaction Times for the Target Letter Response Under High Load

Congruency Cognitive Load Mean (SD)

Congruent Perceptual .87 (.30)

Congruent Short-term Memory .58 (.21)

Congruent Working Memory .67 (.18)

Incongruent Perceptual .91 (.28)

Incongruent Short-term Memory .61 (.18)

Incongruent Working Memory .73 (.19)

Control Perceptual .89 (.25)

Control Short-term Memory .61 (.16)

Control Working Memory .77 (.22)

Note. N = 53

Table 6B

Experiment 2 Means and Standard Deviations of Individuals’ Median Reaction Times for the Target Letter Response Under Low Load

Congruency Cognitive Load Mean (SD)

Congruent Perceptual .87 (.21)

Congruent Short-term Memory .57 (.14)

Congruent Working Memory .66 (.14)

Incongruent Perceptual .87 (.23)

Incongruent Short-term Memory .63 (.17)

Incongruent Working Memory .66 (.16)

Control Perceptual .90 (.21)

Control Short-term Memory .62 (.18)

Control Working Memory .70 (.14)

Note. N = 53

Table 7A

Experiment 3 Means and Standard Deviations of Individuals’ Median Reaction Times for the Target Letter Response Under High Load

Congruency Cognitive Load Mean (SD)

Congruent Perceptual E1 .82 (.24)

Congruent Perceptual E2 .94 (.25)

Incongruent Perceptual E1 .86 (.22)

Incongruent Perceptual E2 .98 (.21)

Control Perceptual E1 .96 (.26)

Control Perceptual E2 .87 (.26)

Note. N = 59

Table 7B

Experiment 3 Means and Standard Deviations of Individuals’ Median Reaction Times for the Target Letter Response Under Low Load

Congruency Cognitive Load Mean (SD)

Congruent Perceptual E1 .86 (.23)

Congruent Perceptual E2 .90 (.26)

Incongruent Perceptual E1 .89 (.26) 60

Incongruent Perceptual E2 .96 (.25)

Control Perceptual E1 .83 (.22)

Control Perceptual E2 .87 (.26)

Note. N = 59

Table 8A

Experiment 4 Means and Standard Deviations of Individuals’ Median Reaction Times for the Target Letter Response Under High Load

Congruency Cognitive Load Mean (SD)

Present Perceptual .44 (.08)

Present Cognitive Control .65 (.10)

Absent Perceptual .44 (.08)

Absent Cognitive Control .63 (.08)

Note. N = 59

Table 8B

Experiment 4 Means and Standard Deviations of Individuals’ Median Reaction Times for the Target Letter Response Under Low Load

Congruency Cognitive Load Mean (SD)

Present Perceptual .40 (.08)

Present Cognitive Control .61 (.08)

Absent Perceptual .39 (.07)

Absent Cognitive Control .59 (.07)

Note. N = 59

Memory Component Accuracy Rates

Figure 1. Graphs depicting accuracy rates for the memory component in Experiment 1.

Figure 2. Graphs depicting accuracy rates for the memory component in Experiment 2.

Figure 3. Graphs depicting accuracy rates for the memory component in Experiment 3.

Figure 4. Graphs depicting accuracy rates in Experiment 4.

Target Letter Component Accuracy Rates

Figure 5. Graphs depicting accuracy rates for the target letter component in Experiment 1.

Figure 6. Graphs depicting accuracy rates for the target letter component in Experiment 2.

Figure 7. Graphs depicting accuracy rates for the target letter component in Experiment 3.

References

Benoni, H., & Tsal, Y. (2012). Controlling for dilution while manipulating load:

perceptual and sensory limitations are just two aspects of task difficulty.

Psychonomic Bulletin & Review, 19(4), 631-638. https://doi.org/10.3758/s13423-

012-0244-8.

Benoni, H., & Tsal, Y. (2010). Where have we gone wrong? Perceptual load does not

affect selective attention. Vision Research, 50(13), 1292-1298.

https://doi.org/10.1016/j.visres.2010.04.018.

Benoni, H., & Tsal, Y. (2013). Conceptual and methodological concerns in the theory of

perceptual load. Frontiers in Psychology, 4, 522.

https://doi.org/10.3389/fpsyg.2013.00522.

Brand-D’Abrescia, M., & Lavie, N. (2007). Distractor effects during processing of words

under load. Psychonomic Bulletin & Review, 14(6), 1153-1157.

https://doi.org/10.3758/BF03193105.

Cartwright-Finch, U., & Lavie, N. (2007). The role of perceptual load in inattentional

blindness. Cognition, 102(3), 321-340.

https://doi.org/10.1016/j.cognition.2006.01.002.

Chen, Z., & Cave, K. R. (2013). Perceptual load vs. dilution: the roles of attentional

focus, stimulus category, and target predictability. Frontiers in Psychology, 4,

327. https://doi.org/10.3389/fpsyg.2013.00327. 66

Conway, A. R., Cowan, N., & Bunting, M. F. (2001). The cocktail party phenomenon

revisited: The importance of working memory capacity. Psychonomic Bulletin &

Review, 8(2), 331-335. https://doi.org/10.3758/BF03196169.

De Fockert, J. W. (2013). Beyond perceptual load and dilution: a review of the role of

working memory in selective attention. Frontiers in Psychology, 4, 287.

https://doi.org/10.3389/fpsyg.2013.00287. de Liaño B., Umiltà C., Stablum F., Tebaldi F., Cantagallo A. (2010). Attentional

distractor interference may be diminished by concurrent working memory load in

normal participants and traumatic brain injury patients. Brain Cognition, 74, 298–

305. https://doi.org/10.1016/j.bandc.2010.08.009.

Forster, S., & Lavie, N. (2007). High perceptual load makes everybody equal.

Psychological Science, 18(5), 377-381. https://doi.org/10.1111/j.1467-

9280.2007.01908.x.

Forster, S., & Lavie, N. (2008). Failures to ignore entirely irrelevant distractors: the role

of load. Journal of Experimental Psychology: Applied, 14(1), 73.

https://doi.org/10.1037/1076-898X.14.1.73.

Hyun, J. S., & Luck, S. J. (2007). Visual working memory as the substrate for mental

rotation. Psychonomic Bulletin & Review, 14(1), 154-158.

https://doi.org/10.3758/BF03194043.

Kim, S. Y., Kim, M. S., & Chun, M. M. (2005). Concurrent working memory load can

reduce distraction. Proceedings of the National Academy of Sciences of the United 67

States of America, 102(45), 16524-16529.

https://doi.org/10.1073/pnas.0505454102.

Konstantinou, N., Beal, E., King, J. R., & Lavie, N. (2014). Working memory load and

distraction: dissociable effects of visual maintenance and cognitive control.

Attention, Perception, & Psychophysics, 76(7), 1985-1997.

https://doi.org/10.3758/s13414-014-0742-z.

Lavie, N., & Cox, S. (1997). On the efficiency of visual selective attention: Efficient

visual search leads to inefficient distractor rejection. Psychological Science, 8(5),

395-396. https://doi.org/10.1111/j.1467-9280.1997.tb00432.x.

Lavie, N. (1995). Perceptual load as a necessary condition for selective attention. Journal

of Experimental Psychology: Human Perception and Performance, 21(3), 451.

https://doi.org/10.1037/0096-1523.21.3.451.

Lavie, N., Hirst, A., De Fockert, J. W., & Viding, E. (2004). Load theory of selective

attention and cognitive control. Journal of Experimental Psychology: General,

133(3), 339. https://doi.org/10.1037/0096-3445.133.3.339.

Lavie, N. (2005). Distracted and confused?: Selective attention under load. Trends in

cognitive sciences, 9(2), 75-82. https://doi.org/10.1016/j.tics.2004.12.004.

Lavie, N. (2010). Attention, distraction, and cognitive control under load. Current

Directions in Psychological Science, 19(3), 143-148.

https://doi.org/10.1177/0963721410370295. 68

Park, S., Kim, M. S., & Chun, M. M. (2007). Concurrent working memory load can

facilitate selective attention: evidence for specialized load. Journal of

Experimental Psychology: Human Perception and Performance, 33(5), 1062.

https://doi.org/10.1037/0096-1523.33.5.1062.

Peirce, J. W. (2007). PsychoPy—psychophysics software in Python. Journal of

neuroscience methods, 162(1), 8-13.

https://doi.org/10.1016/j.jneumeth.2006.11.017.

Tsal, Y., & Benoni, H. (2010). Diluting the burden of load: perceptual load effects are

simply dilution effects. Journal of Experimental Psychology: Human Perception

and Performance, 36(6), 1645. https://doi.org/10.1037/a0018172.

Wilson, D. E., Muroi, M., & MacLeod, C. M. (2011). Dilution, not load, affects distractor

processing. Journal of Experimental Psychology: Human Perception and

Performance, 37(2), 319. https://doi.org/10.1037/a0021433.