Mechanisms of attentional processing during visual search: how distraction is handled by the brain by Gaspar, John Manuel M.A. (Psychology), Simon Fraser University, 2012 Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in the Department of Psychology Faculty of Arts and Social Sciences John Manuel Gaspar 2016 SIMON FRASER UNIVERSITY Fall 2016
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Mechanisms of attentional processing during
visual search: how distraction is handled by the
brain
by
Gaspar, John Manuel
M.A. (Psychology), Simon Fraser University, 2012
Thesis Submitted in Partial Fulfillment of the
Requirements for the Degree of
Doctor of Philosophy
in the
Department of Psychology
Faculty of Arts and Social Sciences
John Manuel Gaspar 2016
SIMON FRASER UNIVERSITY
Fall 2016
ii
Approval
Name:
Degree:
Title:
Examining Committee:
John Manuel Gaspar
Doctor of Philosophy
Mechanisms of attentional processing during visual search: how distraction is handled by the brain
Chair: Thomas Spalek Professor
John McDonaldSenior Supervisor Professor
Mario LiottiSupervisorProfessor
Urs RibarySupervisor Professor
Sam DoesburgInternal ExaminerAssociate ProfessorDepartment of Biomedical Physiology and Kinesiology
Joseph Hopfinger External ExaminerProfessor Department of Psychology and NeuroscienceUniversity of North Carolina at Chapel Hill
Date Defended/Approved: November 23, 2016
iii
Ethics Statement
iv
Abstract
In order to effectively search the visual environment, an observer must continually locate
objects of interest amid an abundance of irrelevant and distracting stimuli. These visual
distractors can sometimes inadvertently attract attention to their locations, even when an
observer is attempting to search for an entirely different object. To deal with visual
distractors, it has been well established that the visual system can implement a
suppression mechanism to filter out irrelevant stimuli. Within the past decade, event-
related potential (ERP) recordings have isolated an attentional component that is thought
to reflect this suppressive processing. This ERP component—termed the distractor
positivity (PD)—has been used to demonstrate that the sensory processing of irrelevant
information can be strongly modulated in line with the visual search goals of an observer.
Here, four electrophysiological studies of attention are presented which focus on yielding
insight into how the visual system deals with irrelevant information during visual search
and seeks to further our understanding of the PD component. Chapter 2 tests the stimulus
conditions necessary to elicit the distractor suppression indexed by the PD by examining
how differences in the salience of an irrelevant stimuli affect visual search. Chapter 3
explores how individual differences in target and distractor processing are associated with
variations in visual working memory (vWM) capacity. Chapter 4 asks how distractor
processing is altered during a disruption of attentional control by examining how visual
search is affected during the attentional blink (AB). Chapter 5 explores how high levels of
trait anxiety alter inhibitory control and the ability to ignore distracting information. In the
final chapter, future directions are discussed and a model for attentional processing is
Approval .......................................................................................................................... ii Ethics Statement ............................................................................................................ iii Abstract .......................................................................................................................... iv Dedication ....................................................................................................................... v Table of Contents ........................................................................................................... vi List of Figures................................................................................................................. ix List of Acronyms ............................................................................................................ xiii
General Introduction ............................................................................... 1 1.1. How objects are prioritized for selection in the visual environment? ........................ 2 1.2. Top-down versus bottom-up processing: the debate .............................................. 4
1.3. An alternative to the dichotomy: signal suppression ............................................... 7 1.3.1. The ERP technique and components associated with attention ................. 8 1.3.2. Evidence for the signal suppression hypothesis....................................... 10 1.3.3. The additional singleton task and signal suppression .............................. 11 1.3.4. Other evidence for signal suppression ..................................................... 13
1.4. Extending our knowledge of signal suppression ................................................... 13 1.4.1. Chapter 2: Eliciting signal suppression during visual search .................... 14 1.4.2. Chapter 3: Individual differences in working memory and visual
search ..................................................................................................... 15 1.4.3. Chapter 4: Signal suppression during a transient loss of attentional
control ..................................................................................................... 16 1.4.4. Chapter 5: Individuals with high levels of trait anxiety show
differences in selective attentional processing ......................................... 17
Eliciting signal suppression during visual search .............................. 19 2.1. Introduction ........................................................................................................... 19 2.2. Methods ............................................................................................................... 22
2.2.1. Materials and Methods ............................................................................ 22 2.2.2. Participants .............................................................................................. 23 2.2.3. Behavioural Pilot Stimuli and Apparatus .................................................. 23 2.2.4. Behavioural Pilot Procedure .................................................................... 23 2.2.5. Visual Search Task Stimuli and Apparatus .............................................. 24 2.2.6. Visual Search Task Procedure ................................................................ 25 2.2.7. Behavioural Analysis ............................................................................... 25 2.2.8. Electrophysiological Recording and Analysis ........................................... 26
2.3. Results ................................................................................................................. 28 2.3.1. Both high- and low-salience distractors produce behavioural
interference ............................................................................................. 28 2.3.2. High- but not low-salience distractors vary as a function of target-
distractor distance ................................................................................... 30 2.3.3. Interference without evidence of attentional capture ................................ 31
vii
2.3.4. Only salient distractors are suppressed during additional singleton search. .................................................................................................... 32
2.3.5. Distractor suppression can be indirectly observed in differences in N2pc amplitude. ....................................................................................... 33
3.3. Results ................................................................................................................. 45 3.3.1. Behaviour in Change-Detection Task ...................................................... 45 3.3.2. Behavior in Visual Search Task ............................................................... 46 3.3.3. Neural activity associated with distractor suppression ............................. 46 3.3.4. Neural activity associated with distractor suppression predicts
individual differences in vWM .................................................................. 48 3.3.5. Neural activity associated with target processing ..................................... 51 3.3.6. Neural activity associated with target processing does not predict
individual differences in vWM .................................................................. 52 3.4. Discussion ............................................................................................................ 54
Signal suppression during a transient loss of attentional control .................................................................................................... 57
4.3. Results ................................................................................................................. 65 4.3.1. Visual search is delayed during the attentional blink ................................ 65 4.3.2. The N2pc is delayed within the attentional blink....................................... 66 4.3.3. The PPC is unaffected during the attentional blink ................................... 67 4.3.4. Individuals cannot recruit distractor suppression during the
attentional blink........................................................................................ 68 4.3.5. Behavioural evidence during the AB revisited .......................................... 69
Individuals with high levels of trait anxiety show differences in selective attentional processing ........................................................... 74
5.3. Results ................................................................................................................. 82 5.3.1. STAI scores ............................................................................................. 82 5.3.2. Search performance does not differ between individuals with high-
and low-anxiety individuals ...................................................................... 82 5.3.3. Suppression is preceded by an attentional shift to the distractor in
high-anxiety individuals ............................................................................ 84 5.3.4. Differences in target processing between high-anxiety and low-
General Discussion ............................................................................... 94 6.1. Attentional capture revisited.................................................................................. 94 6.2. The PD is a measure of top-down signal suppression ........................................... 96 6.3. What is the clinical value of the PD as an index of attentional processing? ........... 98
6.3.1. ADHD ...................................................................................................... 98 6.3.2. Aging and attention .................................................................................. 98 6.3.3. Molecular biology, genetics, and selective attention ................................ 99
6.4. A proposed stream for visual processing ............................................................ 100
Figure 2.1. Trial Types. Example stimulus displays from the two experimental conditions. Subjects were instructed to attend to the yellow circle and to identify the orientation of the line inside of it. On 66% of trials, a distractor singleton was simultaneously presented within the display. ............................................................................................. 22
Figure 2.2. RTs associated with distractor interference. Mean response times (across participants; in milliseconds) for blue distractor, red distractor, and distractor absent (x) trials for Condition 1 and Condition 2 (left). Mean response times were then collapsed to create high-salience, low-salience, and distractor absent trials across the two experimental conditions (right). ....................................... 29
Figure 2.3. Target-distractor RT distance effects. Mean response times (across participants; in milliseconds) for five target-distractor distances (d1- d5) for both high- and low-salience distractor trials.......... 31
Figure 2.4. ERPs elicited by displays containing a midline target and a lateral distractor for each non-target condition. Time 0 reflects the onset of the search display, and negative voltage deflections are plotted above the x-axis, by convention. Waveforms were recorded over the lateral occipital scalp (electrodes PO7 and PO8). (A) ERPs recorded contralateral and ipsilateral to a high-salience distractor. (B) ERPs recorded contralateral and ipsilateral to a low-salience distractor. ............................................................................................... 33
Figure 2.5. ERPs elicited by displays containing a lateral target and a midline distractor for each non-target condition. ERPs are presented as contralateral-minus-ipsilateral difference waveforms for displays containing a lateral target and a distractor singleton, recorded over the lateral occipital scalp (electrodes PO7 and PO8). Difference waveforms are separated for trials where the high- and the low-salience distractor were presented in both (A) Condition 1 and (B) Condition 2. ............................................................................................ 34
Figure 3.1. ERPs elicited by displays containing a midline target and a lateral distractor. Time 0 reflects the onset of the search display, and negative voltage deflections are plotted above the x-axis, by convention. Waveforms were recorded over the lateral occipital scalp (electrodes PO7 and PO8). (A) ERPs recorded contralateral and ipsilateral to a high-salience distractor. (B) ERPs recorded contralateral and ipsilateral to a low-salience distractor. (C) Contralateral-minus-ipsilateral difference waveforms for both conditions. .............................................................................................. 47
x
Figure 3.2. Neural activity associated with salient distractor suppression predicts visual working memory capacity. (A) ERP waveforms recorded contralateral and ipsilateral to the salient distractor plotted separately for high-, medium-, and low-capacity groups. (B) Contralateral-minus-ipsilateral difference waveforms for high-, medium-, and low-capacity groups. ........................................................ 49
Figure 3.3. Neural activity associated with salient distractor suppression predicts visual working memory capacity. (a) Correlation between memory capacity (k) and the mean amplitude of the PD. (b) Correlation between memory capacity (k) and the “pure” PD area. The “pure” PD area reflects the area of the signed positive voltage under the curve between 200-350 ms minus the area of the signed positive voltage in the baseline between -150-0 ms prior to the onset of the search array. ................................................................. 51
Figure 3.4. Neural activity associated with target processing not predictive of visual working memory capacity. (A) Correlation between memory capacity (k) and pure N2pc area for lateral-target displays of interest. (B) Contralateral-minus-ipsilateral difference waveforms for high-, medium-, and low-capacity groups. ......................................... 53
Figure 4.1. Example stimulus display from the experiment. T1 was a number presented amongst letters in an RSVP stream. T2 was an additional singleton search display where participants were instructed to identify the orientation of the line inside the yellow colour singleton. Participants were instructed to give a speeded response to the search array first and then identify the number as either even or odd. ................................................................................. 61
Figure 4.2. Main behavioural results: (A) Accuracy rates for T1 and T2 on both lag 2 and lag 8 trials. (B) Mean response times (across participants; in milliseconds) for lag 2 and lag 8 trials. ............................ 66
Figure 4.3. ERPs elicited by trials with displays containing a lateral target and a midline distractor. Time 0 reflects the onset of the search display, and negative voltage deflections are plotted above the x-axis, by convention. Waveforms were recorded over the lateral occipital scalp (electrodes PO7 and PO8). (A) ERPs recorded contralateral and ipsilateral to a distractor for lag 8 and lag 2 trials. (B) Contralateral-minus-ipsilateral difference waveforms for lag 8 and lag 2 trials. ....................................................................................... 67
Figure 4.4. ERPs elicited by trials with displays containing a midline target and a lateral distractor. Time 0 reflects the onset of the search display, and negative voltage deflections are plotted above the x-axis, by convention. Waveforms were recorded over the lateral occipital scalp (electrodes PO7 and PO8). (A) ERPs recorded contralateral and ipsilateral to a distractor for lag 8 and lag 2 trials. (B) Contralateral-minus-ipsilateral difference waveforms for lag 8 and lag 2 trials. ....................................................................................... 69
xi
Figure 4.5. Target-distractor RT distance effects. Mean response times (across participants; in milliseconds) for lag 2 and lag 8 trials where the target and distractor appeared adjacent to one another and on trials where they appeared furthest from one another. ................ 70
Figure 5.1. Trial Types. Example stimulus displays from the two experimental conditions. Subjects were instructed to attend to the yellow circle and to identify the orientation of the line inside of it. On 50% of trials, a salient distractor singleton was simultaneously presented within the display. ................................................................................... 77
Figure 5.2 Target-distractor RT distance effects. Mean response times (across participants; in milliseconds) for five target-distractor distances (d1- d5) for both high- and low-anxiety individuals. ................. 83
Figure 5.3 PD ERPs elicited by trials with displays containing a midline target and a lateral distractor. Time 0 reflects the onset of the search display, and negative voltage deflections are plotted above the x-axis, by convention. Waveforms were recorded over the lateral occipital scalp (electrodes PO7 and PO8). (A) ERPs recorded contralateral and ipsilateral to a distractor for high- and low-anxiety individuals. (B) Contralateral-minus-ipsilateral difference waveforms for high- and low-anxiety individuals. .................................... 85
Figure 5.4 High-anxiety group ERPs for displays containing a midline target and a lateral distractor, separately for fast- and slow-response trials. (A) ERPs recorded contralateral and ipsilateral to a distractor for fastest and slowest trials. (B) Contralateral-minus-ipsilateral difference waveforms. ............................................................ 86
Figure 5.5 N2pc ERPs elicited by trials with displays containing a lateral target and no distractor. Time 0 reflects the onset of the search display, and negative voltage deflections are plotted above the x-axis, by convention. Waveforms were recorded over the lateral occipital scalp (electrodes PO7 and PO8). (A) ERPs recorded contralateral and ipsilateral to a target for high- and low-anxiety individuals. (B) Contralateral-minus-ipsilateral difference waveforms for high- and low-anxiety individuals. .................................... 88
Figure 5.6 ERPs for displays containing a midline target and a lateral distractor, separately for fast- and slow-response trials. (A) High-anxiety group ERPs recorded contralateral and ipsilateral to a distractor for fastest and slowest trials. (B) High anxiety group contralateral-minus-ipsilateral difference waveforms for high- and low-anxiety individuals............................................................................ 89
Figure 6.1. Adapted from Janatti et al., 2013, a proposed hypothetical processing stream thought to occur during the fixed-feature variant of the additional singleton search task. Listed below each stage is the ERP component associated with that particular level of processing. ....................................................................................... 100
xii
Figure 6.2. Hypothetical resolving of a visual search task based on the input image shown. The stars (top) represent the stimuli’s activation on the saliency map, with increased brightness denoting greater salience. The saliency map is then scanned by attention and suppression/enhancement are applied contingent on top-down attentional templates. ........................................................................... 101
xiii
List of Acronyms
ACT Attentional Control Theory
ADHD Attentional-deficit/hyperactivity disorder
ANOVA Analysis of variance
BOLD Blood oxygen level dependent
CIE Commission Internationale de l’Éclairage (International Commission on
Illumination)
EEG Electroencephalography
EOG Electrooculogram
ERP Event-related potential
ERPSS Event-related Potential Software System
Hz Hertz
K Estimate of vWM capacity
LAI Localized Attentional Interference
ms Millisecond
N2pc N2-posterior-contralateral component
PD Distractor positivity
PO Parieto-occipital
PPC Positivity, posterior contralateral
RSVP Rapid serial visual presentation
RT Reaction time
STAI State-trait anxiety inventory
T1 First target
T2 Second Target
xiv
µV Microvolts
vWM Visual working memory
1
General Introduction
Making sense of our visually complex world requires we be able to rapidly search
through the visual environment and appraise the information within it. From infinite
combinations of shapes, colours, and boundaries, the visual system works to ascribe
meaning to the objects that comprise our world. Yet, at any given moment, our brain lacks
the capacity to process all objects in a visual scene to a level of complete perceptual
Theeuwes, 2005), can all lead to reflexive, automatic shifts of attention.
1.2. Top-down versus bottom-up processing: the debate
Top-down and bottom-up processes do not work in isolation but rather interact
dynamically to motivate attentional selection. Under certain conditions, however, conflict
can arise between the volitional goals of an observer and the strength of irrelevant sensory
inputs. In a typical cluttered visual scene where multiple stimuli are competing for
attention, can an observer bias processing toward a behaviourally relevant object or will
competing salient-but-irrelevant objects automatically capture attention? This precise
question has resulted in a longstanding controversy regarding the nature of attentional
biasing and the extent to which top-down processing can counteract the influence of
conspicuous competing stimuli.
5
1.2.1. Stimulus-driven capture
Decades of research has resulted in two predominant models of attention that fall
at opposing ends of the theoretical spectrum. At one end of the debate is the stimulus-
driven capture hypothesis (e.g., Theeuwes, 2010). According to this perspective,
attentional priority is driven entirely by the bottom-up features of a stimulus. This stimulus-
driven prioritization of processing occurs regardless of the intentions or expectations of
the observer and the most salient object in a visual scene will always automatically capture
attention. Top-down attentional settings can work to disengage and redeploy attention to
a behaviourally relevant stimulus but only subsequent to this involuntary initial shift.
Evidence for the stimulus-driven capture hypothesis comes primarily from visual
search studies using the additional singleton paradigm (Theeuwes, 1991, 1992, 1994). In
these tasks, participants search an array of non-targets for a target defined by a feature
unique to it alone (i.e., a singleton). For example, the non-targets might be green ellipses
and the target a green diamond. Typically, observers report the orientation of a line
segment contained within the target (e.g., horizontal or vertical). On a subset of trials, one
of the non-targets is also a singleton, and its salience can be greater than the target’s
(e.g., a red ellipse). The presence of this salient distractor results in longer response times
(RTs) to the target, and the magnitude of this behavioural interference cost varies with the
predictability of the stimuli. If the features of the target and distractor are randomly
swapped from trial to trial, the presence of a salient distractor singleton can delay RTs by
100-150 ms (Theeuwes, 1991). When the features of the target and distractor remain fixed
across trials, the presence of a salient distractor singleton delays RTs by 20-25 ms
(Theeuwes, 1992). This lattermost finding is notable because observers can configure
their attentional set perfectly for the target and the non-targets, and yet the behavioural
interference effect persists 1. Stimulus-driven capture accounts for this by holding that the
1 According to the stimulus-driven capture hypothesis, capture itself is associated with this 20-25
ms interference cost. The increased RT interference observed in the mixed-feature variant of the additional singleton cost is not associated with increased capture but rather with target uncertainty. Additional dwell time is necessary to determine whether the item selected is either a target or a distractor (Theeuwes, 2010).
6
initial deployment of attention is always made to the most salient item in view before being
redeployed to a target.
Opponents of this stimulus-driven capture hypothesis have proposed two
alternative explanations for the distractor interference observed in the additional singleton
task. The first explanation holds that the RT interference is not related to stimulus-driven
capture, but rather to the use of a singleton-detection strategy. By this account,
participants prime themselves to detect any unique singleton, as opposed to detecting a
singleton of a specific identity, even when they know the identity of the to-be-located
target. By altering the experimental parameters and by having participants search for a
target feature instead of a unique singleton, Bacon & Egeth (1994) showed that the
interference associated with a color singleton could be eliminated; RT inference was no
longer present even on trials where the displays were physically identical to those
presented in Theeuwes’ 1992 study. The authors concluded that the use of a singleton-
detection strategy leaves observers susceptible to interference from singletons defined by
task-irrelevant features. The second explanation attributes distractor interference to a non-
spatial filtering cost (Kahneman, Treisman & Burkell, 1983). By this account, search
displays with a target and a distractor singleton result in an increased amount of
competition between the two items. Additional filtering is necessary to suss out the target
singleton, which delays the deployment of attention to that item. Critically, no shift of
attention is made to the distractor. Evidence for this non-spatial filtering cost come from
experiments that show distractor singletons produce an additional RT cost in the absence
of any evidence for attentional capture (Folk & Remington, 2006; Folk & Remington, 1998;
Wykowska & Schubö, 2011).
1.2.2. Contingent-capture
At the opposite end of the debate is the contingent-capture hypothesis (e.g., Folk,
inconspicuous distractors have been found to elicit the PD in other studies (Hickey et al.,
2009; Hilimire et al., 2012), thereby obscuring the conditions under which active
suppression is required to resolve competition for attention.
To address this question, EEGs were recorded while participants performed a uni-
dimensional variant of the well-known additional singleton search paradigm (Theeuwes,
1992) that pitted a target against one of two potential distractors. Participants were
instructed to search a circular multi-item display for a pre-specified color singleton while
attempting to ignore a task-irrelevant color singleton that could potentially appear in the
same display. Distractor absent trials consisted of a yellow target singleton presented
alongside nine uniformly coloured non-targets. On distractor present trials, one non-target
item was replaced with one red or blue distractor singleton (Trials types can be observed
in Figure 2.1). The color of the non-targets was varied across experimental conditions (all
green or all orange) to disentangle distractor salience from distractor color. Specifically, in
Condition one the red distractor was the most salient singleton against green non-targets,
whereas in Condition two the blue distractor was the most salient singleton against orange
non-targets (which was confirmed in a behavioral pilot experiment). Target- and distractor-
related ERPs were then measured separately for low- and high-salience distractor trials
to determine whether or not attentional suppression occurred.
22
Figure 2.1. Trial Types. Example stimulus displays from the two experimental conditions. Subjects were instructed to attend to the yellow circle and to identify the orientation of the line inside of it. On 66% of trials, a distractor singleton was simultaneously presented within the display.
2.2. Methods
2.2.1. Materials and Methods
The Research Ethics Board at Simon Fraser University approved the research
protocol used in this study.
23
2.2.2. Participants
Fifty-five subjects from Simon Fraser University participated after giving informed
consent. Students received course credit for their participation as part of a departmental
research participation program. A grand total of 48 participants, 24 in Condition 1 (20
women, age 20.8 ± 2.2 y; 0 left-handed), and 24 in Condition 2 (13 women, age 20.0 ± 2.9
y; 1 left-handed) participated in the study. All subjects reported normal or corrected-to-
normal visual acuity and were tested for typical colour vision using Ishihara colour test
plates.
2.2.3. Behavioural Pilot Stimuli and Apparatus
To ensure only one distractor (per condition) was considerably more salient than
the target, an initial singleton-detection task was performed. The three singleton colors
were selected so that the salience of the target would be approximately equal to that of
one distractor and considerably less than that of the other distractor. Salience was
considered in two ways: as the local contrast between the (uniform) non-targets and each
color singleton, and as the rapidity with which each singleton could be detected. Local
contrast was measured as the distance in CIE [Commission Internationale de l’Éclairage
(International Commission on Illumination)] chromaticity space between a singleton and
the surrounding non-targets (herein called color distance). In each condition, the color
distance was considerably larger for one distractor (e.g., red distractor vs. green non-
targets) than for the target (e.g., yellow target vs. green non-targets). The method used to
measure the rapidity of item selection is described in the next section.
2.2.4. Behavioural Pilot Procedure
After candidate colors for all five items were selected, a behavioural pilot
experiment was conducted wherein participants (n = 8) were required to detect any
singleton (yellow, red, or blue) appearing with either the green or orange non-targets.
Stimuli were presented on a 23 inch, 120 Hz LCD monitor viewed from a distance of 57
cm. The six combinations of colors were presented in separate blocks, and on each trial,
24
there was an equal probability the target would be present or absent. Participants were
instructed to press a button when they detected the singleton. The mean RTs for the pilot
were analyzed in a repeated-measures ANOVA with factors for non-target color (green,
orange) and singleton color (yellow, blue, red). With green non-targets, RTs were shorter
for the red singleton (363 ms) than for the blue or yellow singleton (387 ms, 405 ms). With
orange non-targets, RTs were shorter for the blue singleton (364 ms) than for the red or
yellow singleton (411 ms, 402 ms). This pattern of results led to a significant interaction
between the non-target color and the singleton color [F(2,28) = 12.4; P < 0.001]. Planned
Bonferroni-corrected t tests confirmed the following: on green non-target trials, RTs to the
yellow singleton were longer than RTs to the red singleton [t(7) = 4.9; P = 0.003] but not
the blue singleton [t(7) = 2.1; P = 0.27]; on orange non-target trials, RTs to the yellow
singleton were significantly longer than RTs to the blue singleton [t(7) = 4.4; P = 0.008]
but not the red singleton [t(7) = 1.0; P = 0.37].
2.2.5. Visual Search Task Stimuli and Apparatus
Stimuli were presented on the same 23 inch, 120 Hz LCD monitor used in the
previous section. Viewing distance was 57 cm. Visual search arrays comprised 10 unfilled
circles presented equidistant (9.2°) from a central fixation point. Each circle was 3.4° in
diameter with a 0.3° thick outline. Eight or nine of the circles were uniformly coloured non-
targets, one was a target colour singleton, and one was a distractor color singleton (on
distractor-present trials). The target was dark yellow (x = 0.416, y = 0.519, 7.9 cd/m2), and
the distractor was either red (x = 0.640, y = 0.324, 7.0 cd/m2) or blue (x = 0.179, y = 0.199,
7.9 cd/m2). A randomly oriented vertical or horizontal gray line (x = 0.295, y = 0.361, 7.9
cd/m2) was contained within each of the circles. In Condition 1, the non-target circles were
green (x = 0.288, y = 0.636, 7.9 cd/m2), and in Condition 2, they were orange (x = 0.563,
y = 0.402, 7.9 cd/m2). All stimuli were presented on a uniform black background (0.5
cd/m2).
25
2.2.6. Visual Search Task Procedure
On each trial, a search display was presented after an 800-1,200 ms fixation
period, during which only the central fixation point was visible. Participants were instructed
to maintain fixation on the central point and to identify the orientation of the gray line inside
the target singleton by pressing one of two response buttons as quickly as possible. The
search array remained visible for 100 ms after a response was registered, at which point
the next trial began.
Displays contained a target singleton and one distractor singleton on 66% of trials
(distractor-present trials). On half of these trials, the distractor singleton was more salient
than the target (high-salience distractor trials), and on the other half of these trials, it was
no more salient than the target (low-salience distractor trials). On the remaining 33% of
trials, the target was the only singleton in the array (distractor-absent trials).
Target and distractor locations were varied to produce the following display
configurations: lateral target, no distractor (22.0%); midline target, no distractor (11.3%);
salience distractor; (v) midline target, lateral low-salience distractor. ERPs to these search
displays were created by collapsing across left and right visual hemifields and left and
right electrodes (P07 and P08) to produce waveforms recorded ipsilateral and
contralateral to distractor stimuli. Negative voltages were plotted upward, so that the N2pc
and PD would appear in these difference waveforms as upward and downward deflections,
respectively. Lateralized ERP difference waveforms were then derived by subtracting the
ipsilateral waveform from the corresponding contralateral waveform. All ERP statistics
were computed using contralateral minus ipsilateral difference values.
PD and N2pc components were measured using a conventional mean-amplitude
approach. By convention, electrodes and time windows were selected a priori based on
existing studies that measured mean amplitudes (thereby avoiding problems of multiple
implicit comparisons; Luck, 2014). Both components were measured at lateral occipital
electrodes PO7/PO8, as in most previous papers. The N2pc window and the PD window
was measured 250-290 ms post stimulus onset and were chosen to replicate the
methodology used in Gaspar and McDonald’s (2014) study. Latency statistics were
computed 200-350 ms post stimulus onset using jackknifed averages. Latency onsets
were defined as the point at which the voltage of the component reached 50% of the peak
amplitude.
28
2.3. Results
2.3.1. Both high- and low-salience distractors produce behavioural
interference
For the main experiment, participants were instructed to search a circular multi-
item array for a yellow target singleton that appeared among green (Condition 1) and
orange (Condition 2) non-targets. On a subset of trials, a red or a blue distractor singleton
would replace a non-target item. Between the two conditions, only the colour of non-target
items were varied. This was done in order to disentangle the effects of distractor colour
from those of distractor salience. Colours were selected based on an initial pilot study to
gauge salience (See: 2.2.4. Behavioural Pilot Procedure). Among green non-targets, the
red distractor was selected to be more salient than the yellow target and the blue
distractor, while the blue distractor was selected to be nominally salient to the target.
Among orange non-targets, the blue distractor was selected to be more salient than the
yellow target and the red distractor, while the red distractor was selected to be nominally
salient to the target.
To determine the effectiveness of this manipulation in the visual search task,
median reaction times (RTs) were separately computed for each condition, for trial types
where the red or blue distractor appeared with the target. Inter-participant mean RTs were
then derived by averaging participant median RTs across these different trial types. RTs
from distractor-present trials were analysed as a function of distractor colour (red, blue)
and non-target colour (green, orange). As anticipated, the main effect was not significant,
[F(1,46) = .65; P = .425] but the distractor colour × non-target colour interaction was found
to be significant [F(1,46) = 55.9; P < .001]. Figure 2.2 illustrates the basis for this
interaction across the two conditions: RTs were slower when the display contained a high-
salience distractor than when the display contained a low-salience distractor, regardless
of the specific combination of distractor and non-target colours.
29
Figure 2.2. RTs associated with distractor interference. Mean response times (across participants; in milliseconds) for blue distractor, red distractor, and distractor absent (x) trials for Condition 1 and Condition 2 (left). Mean response times were then collapsed to create high-salience, low-salience, and distractor absent trials across the two experimental conditions (right).
This preliminary RT analysis confirmed that distractor salience rather than
distractor colour modulated performance in the additional singleton task employed here.
Accordingly, RT data from the two distractor colours were combined with RT data from the
two non-target colours to yield high- and low-salience distractor types. A distractor-absent
level was added to assess the overall effects of high- and low-salience distractors on
search performance. The results showed inter-participant mean RTs were shortest on
and longest in the high-salience distractor trials (628 ms), leading to a significant main
effect of distractor type [F(2,92) = 75.5; P < .001]. Inter-participant mean RTs across the
three levels were all found to be statistically different from one another by pair-wise
comparison (Ps < .001). As can be seen in Figure 2.2, although both distractors delayed
search, the high-salience distractor caused a longer delay (22 ms) than did the low-
salience distractor (8 ms).
30
2.3.2. High- but not low-salience distractors vary as a function of
target-distractor distance
RT interference has been shown to vary not only as a function of distractor salience
(as shown here) but also as a function of target-distractor distance, with nearby distractors
causing more interference than more distant distractors (Gaspar & McDonald, 2014;
Hickey & Theeuwes, 2011; Jannati et al., 2013; Mounts, 2000). To examine the
dependency of interference on target-distractor distance for the different salience
conditions, RTs were submitted to an ANOVA with two within-subject factors—Target-
Distractor Distance (1, 2, 3, 4, 5; see Methods) and Distractor Salience (high, low)—and
a between-subject factor for Non-target Colour (green, orange). Overall, RTs were longer
for nearby distractors than distant distractors and for high-salience distractors than low-
salience distractors, resulting in significant main effects for Target-Distractor Distance;
F(4,184) = 37.09, P < .001, and Distractor Salience, F(4,46) = 55.07, P < .001,
respectively. Critically, a significant interaction between Target-Distractor Distance and
Distractor Salience was also found, F(4,184) = 38.30, P < .001. No between subjects
effects were observed for non-target colour [F(1,46) = 1.48, P = .23], further confirming
the success of the salience manipulation. Figure 2.3 illustrates the basis for this
interaction: RTs decreased in a monotonic fashion as the distance between target and
distractor increased for high-salience-distractor trials, but the interference effect changed
little over the five target-distractor distances for low-salience trials.
31
Figure 2.3. Target-distractor RT distance effects. Mean response times (across participants; in milliseconds) for five target-distractor distances (d1- d5) for both high- and low-salience distractor trials.
2.3.3. Interference without evidence of attentional capture
Target-distractor distance effects like the one observed here for high-salience
distractors have previously been attributed to distractor-driven attentional capture by some
(Hickey & Theeuwes, 2011; Mounts, 2000) and distractor suppression by others (Gaspar
& McDonald, 2014; Jannati et al., 2013). According to the capture account, attention is
deployed first to the location of the more salient distractor, and a concomitant zone of
inhibition around that location impairs selection of nearby targets. According to the
suppression account, inhibitory signals associated with the unattended distractor conflict
with excitatory signals associated with the to-be-attended target, leading to perceptual
ambiguity when the two singletons fall within the same receptive fields. While it is difficult
to disambiguate between these accounts on the basis of the behavioural evidence alone,
one aspect of the RT data favours a suppression account: the most distant salient
distractors (target-distractor distance d5) did not delay search relative to distractor-absent
trials [606 ms vs. 606 ms, respectively, t(47) = .04, P = .97]. That is to say, there was no
behavioural evidence to indicate that attention was inadvertently deployed to salient
distractors that appeared far away from the target.
32
2.3.4. Only salient distractors are suppressed during additional
singleton search.
The primary goal of this chapter was to determine whether all distractors or only
particularly salient ones are suppressed during visual search. To this end, ERPs were
examined separately for(i) displays containing a lateral, high-salience distractor and a
midline target and (ii) displays containing a lateral, low-salience distractor and a midline
target. Any lateralized ERP activity observed in response to such displays can be ascribed
to the distractor singleton because target singletons appearing above or below fixation are
incapable of eliciting such ERP lateralizations (Hickey et al., 2006, 2009; Luck, 2014;
Woodman & Luck, 2003).
The resultant PD ERPs confirmed the prediction that the visual system acts to
suppress the processing of high- but not low-salient items. As shown in Figure 2.4a, the
high-salience distractor elicited the PD in both non-target-colour conditions (green non-
targets, t(23) = 2.5; P = 0.02; orange non-targets, t(23) = 2.1; P = 0.046). Neither the onset
latency (274 ms vs. 293 ms; tc = -1.3; P = 0.19) nor the amplitude (0.53 vs. 0.44 μV; t[46]
= 0.3; P = 0.756) of the PD was found to differ significantly between the two conditions. As
shown in Figure 2.4b, no PD was in evidence on low-salience distractor trials (green non-
targets, t(23) = -1.0; P = 0.345; orange non-targets, t(23) = 0.7; P = 0.493.
To evaluate the differences statistically, PD amplitudes were analysed using an
ANOVA with a within-subject factors for Distractor Salience (high, low) and a between-
subject factor for Non-target Colour (green, orange). As anticipated, the PD was
significantly larger for high-salience distractors than for low-salience distractors, F(1,46) =
7.51, P = .009. Neither the Non-target Colour main effect nor the Distractor Salience x
Non-target Colour interaction (Fs < 1) were significant.
33
Figure 2.4. ERPs elicited by displays containing a midline target and a lateral distractor for each non-target condition. Time 0 reflects the onset of the search display, and negative voltage deflections are plotted above the x-axis, by convention. Waveforms were recorded over the lateral occipital scalp (electrodes PO7 and PO8). (A) ERPs recorded contralateral and ipsilateral to a high-salience distractor. (B) ERPs recorded contralateral and ipsilateral to a low-salience distractor.
2.3.5. Distractor suppression can be indirectly observed in
differences in N2pc amplitude.
Figured 2.5 shows grand averaged contralateral minus ipsilateral difference
waveforms for lateralized target singleton trials for the various display configurations. The
N2pc was measured as the difference in mean amplitude between contralateral and
ipsilateral activity at electrodes PO7/PO8 from 250 to 290 ms after the onset of the search
array. For Condition 1, a significant N2pc was observed in both high and low-salience
distractor conditions for the i) lateral target, contralateral distractor, ii) lateral target, midline
distractor, and iii) lateral target, ipsilateral distractor display configurations (t’s > 2.63, p <
34
.02). For Condition 2, a significant N2pc was observed for the same six display
configurations [t > 4.19, p < .001].
Figure 2.5. ERPs elicited by displays containing a lateral target and a midline distractor for each non-target condition. ERPs are presented as contralateral-minus-ipsilateral difference waveforms for displays containing a lateral target and a distractor singleton, recorded over the lateral occipital scalp (electrodes PO7 and PO8). Difference waveforms are separated for trials where the high- and the low-salience distractor were presented in both (A) Condition 1 and (B) Condition 2.
When attentional selection and distractor suppression coincide, the similar
temporal profiles of the N2pc and PD will result in the two components overlapping.
Specifically, on a search display trial that elicits target selection and distractor
35
suppression, the negative-going voltage of the N2pc will sum linearly with the positive-
going voltage of the PD (Hickey et al., 2009). The overlap of the two components results
in an observed difference in the amplitude of the more dominant N2pc component: the
N2pc is largest when the target and distractor appear on opposite sides of fixation,
intermediate when the distractor appears on the midline, and smallest when the target and
distractor appear on the same side of fixation (Gaspar & McDonald, 2014).
In line with the summation hypothesis outlined above, amplitude differences in the
N2pc can be interpreted as indirect evidence of the presence of the PD and distractor
suppression. Namely, if distractor suppression has occurred, the N2pc waves associated
with lateral-target displays will vary linearly due to their summation with the PD.
Alternatively, if distractor suppression has not occurred, the N2pc waves associated with
lateral-target displays will not change as a function of the relative distractor location (same
side, opposite side).
As shown in Figure 2.5, amplitude differences were observed for trials that
contained a high-salience distractor singleton. As would be predicted, for Condition 1 the
target N2pc was largest when the distractor was on the opposite side of fixation (mean
amplitude in 250-290 ms window: -1.60 µV), intermediate when the distractor was on the
vertical midline (-.91 µV), and smallest when the distractor was on the same side of fixation
(-.63 µV). The same pattern of results was observed for Condition 2 (-1.93 µV, -1.47 µV,
-1.25 µV respectively). These differences in N2pc amplitude were found to differ
significantly for all high-salience distractor trials across the three lateral-target
configurations [F(2,94) = 9.0, p < .001]. In contrast, low-salience distractor trials elicited
no differences in N2pc amplitudes across the same three display configurations [Condition
To visually assess the relationship between vWM capacity and ERP components
of interest, participants were evenly apportioned into a high-, medium-, and low-capacity
subgroup based on their vWM capacity estimates (n = 16 per group).
Lastly, the split-half reliability of the N2pc and PD components were computed by
randomly splitting the data into two halves and computing correlations of the half-data
mean amplitude averages for each component. All split-half correlations were corrected
for using the standard method (Anastasi & Urbina, 1997).
3.3. Results
3.3.1. Behaviour in Change-Detection Task
vWM capacity was measured for each participant using a change detection task
(Luck and Vogel, 1997). The average K estimate was 2.5, with scores ranging from 1.8 to
46
4.0. The K estimates were not found to differ significantly across the two non-target-colour
conditions [2.47 vs. 2.52; t(46) = 0.3; P = 0.778].
3.3.2. Behavior in Visual Search Task
Here, the relationship between vWM capacity and behavioural performance were
assessed for both response variability (RT standard deviation) and speed of processing
(median RT). Such measures have been linked to attentional control and shown to be
associated with differences in working memory capacity (Castellanos & Tannock, 2002,
Frye & Hale, 1996; Schachar & Logan, 1990). RTs were collapsed across all conditions in
order to create an overall participant speed and standard deviation estimate. Consistent
with previous findings, both median RT and RT standard deviation were found to
negatively correlate with vWM capacity in the present study (rs > -0.39; P < 0.007). This
indicates that vWM capacity was associated with faster and less variable responses.
3.3.3. Neural activity associated with distractor suppression
Having confirmed the success of the salience manipulation in Chapter 2, ERPs for
participants from both non-target conditions were combined to create three new main trial
types: high-salience distractor, low-salience distractor, and distractor absent trials.
Collapsed ERPs for lateral distractor present trials are shown in Figure 3.1a and 3.1b.
When collapsed, the mean amplitude of the PD remained significant for midline target,
lateral high-salience distractor trials [t(47) = 3.3; P = 0.002]. The data was then randomly
split into two equal halves of trials in order that the split-half reliability of the PD could be
computed. The PD constructed from the first half of data was found to moderately correlate
with the PD constructed from the second half of data (r = 0.57; P < 0.001).
47
Figure 3.1. ERPs elicited by displays containing a midline target and a lateral distractor. Time 0 reflects the onset of the search display, and negative voltage deflections are plotted above the x-axis, by convention. Waveforms were recorded over the lateral occipital scalp (electrodes PO7 and PO8). (A) ERPs recorded contralateral and ipsilateral to a high-salience distractor. (B) ERPs recorded contralateral and ipsilateral to a low-salience distractor. (C) Contralateral-minus-ipsilateral difference waveforms for both conditions.
In addition to the conventional mean-area approach, a novel signed area approach
was devised to measure the magnitude of the PD component. The signed area approach
used here has three primary benefits versus the conventional mean-area approach. First,
an unbiased and wide measurement window can be set without components of the
opposite polarity cancelling out their contribution. Second, by casting a wide measurement
window, subject variability is better represented within the measurement. The wide
window better detects the specific contribution of a participant’s component rather than
48
their contribution within a narrow window centered around the mean. This is particularly
important for the present experiment, as subject variability was central to the main
hypotheses. Third, and specific to the approach used here, baseline noise in the ERPs is
taken into consideration, reducing the likelihood of erroneously detecting a component
that does not exist. Here, the signed positive area of the PD was measured in an interval
from 200-350 ms post stimulus onset. This area was then subtracted from the signed
positive area in an equal interval within the baseline (-150-0 ms). The resultant magnitude
of the PD was found to be both statistically significant [t(47) = 4.1; P < 0.001] and internally
reliable (r = 0.61; P < 0.001).
3.3.4. Neural activity associated with distractor suppression predicts individual differences in vWM
In order to explore the basis for a relationship between distractor suppression and
vWM capacity, participants were equally divided into three groups contingent on their
behavioral K estimates to produce a high-, medium, and low-capacity group. ERP
waveforms recorded contralateral and ipsilateral to the salient distractor were then
averaged for the high, medium, and low K estimate groups (Figure 3.2a). vWM estimates
were 2.73 to 4.03 for the high-capacity group, 2.16 to 2.73 for the medium-capacity group,
and 1.60 to 2.13 for the low-capacity group. As can be seen in Figure 3.2b, the PD was
largest for the high-capacity group, reduced for the medium capacity group, and diminutive
for the low-capacity group. The differences between groups were significant for both the
mean amplitude and the signed positive area: F’s > 8.4 (P’s < 0.001).
49
Figure 3.2. Neural activity associated with salient distractor suppression predicts visual working memory capacity. (A) ERP waveforms recorded contralateral and ipsilateral to the salient distractor plotted separately for high-, medium-, and low-capacity groups. (B) Contralateral-minus-ipsilateral difference waveforms for high-, medium-, and low-capacity groups.
T-tests for both the mean amplitude and signed positive area confirmed the
presence of the PD in the high- and medium-capacity group (Ps < 0.006); however, the PD
was not found to be statistically significant in the low-capacity group (Ps > 0.18).
Additionally, in the low-capacity group a contralateral negativity was observed prior to the
non-significant contralateral positivity. Similar distractor elicited negativities (distractor
N2pcs) have been shown to reflect attentional capture by the distractor singleton (e.g.,
Burra & Kerzel, 2013; Hickey et al., 2006; Jannati et al., 2013). The mean amplitude of
the distractor elicited N2pc observed here was determined to be statistically significant
[t(15) = 2.3; P = 0.03]. Together, the results here indicate that while the majority of
participants were able to actively suppress the distractor singleton, individuals with the
50
lowest vWM capacities were not. As a result, the inability to suppress led to the attentional
capture of the salient-but-irrelevant singleton.
Next, correlations were used to investigate the relationship between the magnitude
of distractor suppression processing indexed by the PD component and vWM capacity. As
can be seen in Figure 3.3, the mean amplitude of the PD was observed to correlate
positively with vWM capacity (r = 0.55; P < 0.001), as was the signed positive area (r =
0.59; P < 0.001). In addition to differences in magnitude, the tertile split of the data also
revealed differences in the timing of the PD component. The PD appeared to begin earlier
for individuals with higher vWM capacity estimates relative to those with lower vWM
capacity estimates. To test this prediction, jackknifed estimates of PD onset were
correlated with each participant’s behavioral K estimate. Jackknifed estimates of PD onset
were found to also correlate positively with vWM capacity (r = -0.39; P < 0.006), confirming
a positive relationship between the onset of the PD and vWM capacity.
51
Figure 3.3. Neural activity associated with salient distractor suppression predicts visual working memory capacity. (a) Correlation between memory capacity (k) and the mean amplitude of the PD. (b) Correlation between memory capacity (k) and the “pure” PD area. The “pure” PD area reflects the area of the signed positive voltage under the curve between 200-350 ms minus the area of the signed positive voltage in the baseline between -150-0 ms prior to the onset of the search array.
3.3.5. Neural activity associated with target processing
In order to isolate the lateralized processing of the target, ERPs were first
constructed for lateral target, midline high-salience distractor trials. These trials allowed
for target processing to be assessed under the same stimulus load condition used to
assess distractor processing (Section 3.3.3). Prior to collapsing across the two non-target
52
conditions, an analysis was performed to ensure the target N2pc was present for both
experimental conditions and did not vary as a function of non-target colour. The lateral
target was confirmed to elicit an N2pc in each condition using both mean amplitude and
signed negative area measures [green non-targets: t(23) > 3.2 (P < 0.004); orange non-
targets: t(23) > 5.5 (P < 0.001)]. Neither N2pc mean amplitude nor signed negative area
was found to differ between the non-target conditions [t(23) > 1.6 (P < .15)], confirming
the conditions did not differ.
Distractor absent trials were additionally tested to assess the relationship between
target processing and vWM capacity. These trials offered a more isolated representation
of target enhancement in the absence of the concurrent suppression of the salient
distractor. Lateral target stimuli were again confirmed to elicit an N2pc in each condition
using both mean amplitude and signed negative area measures [green non-targets: t(23)
> 4.0 P < 0.001); orange non-targets: t(23) > 4.4; P < 0.001)]. Both N2pc mean amplitude
and negative signed area were found not to differ between the non-target conditions [t(23)
> .47 (P < .65)]. The split-half reliability estimates were observed to be significant for both
mean amplitude and signed negative area measures (rs > 0.67; Ps < 0.001).
3.3.6. Neural activity associated with target processing does not predict individual differences in vWM
The relationship between vWM capacity and target processing was assessed in
two ways. First, to visualize the relationship between vWM capacity and target processing,
participants were again apportioned into three subgroups contingent on their vWM
capacity (Figure 3.4a). In contrast to the differences observed for the PD component, one-
way ANOVAs revealed no significant differences for the N2pc across the K subgroups
Fs < 0.6; Ps > 0.552). Next, correlations were computed to assess the relationship
between target processing and vWM capacity. As shown in Figure 3.4a and 3.4b, neither
the mean amplitude nor the signed negative area of the N2pc was found to correlate with
vWM capacity in either of the display configurations (rs < 0.08; Ps > 0.59). In addition to
this, the jackknifed estimates of N2pc onset latency were also found to not correlate with
vWM capacity (rs < 0.13; Ps > 0.38). In contrast to the relationship observed for distractor
53
suppression, the results here reveal no discernable association between the
enhancement of the target singleton and vWM.
Figure 3.4. Neural activity associated with target processing not predictive of visual working memory capacity. (A) Correlation between memory capacity (k) and pure N2pc area for lateral-target displays of interest. (B) Contralateral-minus-ipsilateral difference waveforms for high-, medium-, and low-capacity groups.
54
3.4. Discussion
Cognitive-control based theories of vWM propose that individual differences in
performance are closely associated with variability in attentional control (e.g., Engle &
Spitzer, Desimone & Moran, 1988; Yeshurun & Carrasco, 1998). Over the years, the
neural bases of the mechanisms controlling selective attention have been investigated
using electrophysiological recordings in humans (see Carrasco, 2011 and Luck, 2014 for
comprehensive reviews). Many of these electrophysiological studies have tracked
attention using the N2pc, an ERP component known to index spatially selective
processing during visual search (Luck & HIllyard, 1994a, 1994b; Hickey et al., 2009;
Mazza et al., 2009; Eimer, 1996). When a laterally presented item is attended, the N2pc
component typically presents as a greater negativity over posterior electrode sites
contralateral (versus ipsilateral) to the item. This processing is thought to reflect the
enhanced processing of an attended target when presented in competition among other
irrelevant items (Hickey et al., 2009; Luck, 2012, Mazza et al., 2009a, 2009b).
In addition to the enhanced processing of a relevant target item, the visual system
can also act to suppress the processing of irrelevant distractor items. In humans, studies
of visual attention have reported that task-irrelevant distractors can be inhibited in a top-
down manner when they are anticipated. This inhibitory mechanism serves to actively
58
suppress distractor representations and prevent these irrelevant objects from erroneously
capturing attention, even when they are especially salient (e.g., Gaspar & McDonald,
2014; Gaspelin et al., 2015; Hickey et al., 2009; Janatti, Gaspar & McDonald, 2013). The
electrophysiological correlate of this process is a contralateral positive-going voltage
recorded from electrodes over posterior-occipital scalp—an ERP component termed the
PD. The distractor suppression indexed by the PD is thought to reflect an active mechanism
that inhibits certain stimuli based on the parameters of an observer’s top-down attentional
set (e.g., Gaspar & McDonald, 2014; Hickey et al., 2009; Hilimire et al., 2012; Jannati et
al., 2013; Sawaki & Luck, 2010; Sawaki, Geng & Luck, 2011); however, direct evidence
for this active suppression is limited. Alternatively, it is possible that the PD may reflect
processing associated with the bottom-up physical properties of an object rather than the
object’s top-down status (Fortier-Gauthier et al., 2013).
If the PD is strongly related to endogenous attentional factors, it should be impaired
in situations where top-down control would be severely restricted. The primary purpose of
the present chapter was to investigate this possibility by disrupting attentional control
during visual search and examining how distractor processing is affected. One manner of
producing a disruption of attentional control is by presenting a critical target in rapid
succession of another. Although participants are easily able to identify the first target (T1),
their ability to identify the second target (T2) depends on the amount of time separating
the two items. Specifically, if the second target is presented within 200-500 ms of the first,
accuracy for the second target is heavily impaired. This impairment for processing the
second target is termed the attentional blink (AB; Broadbent & Broadbent, 1987;
Raymond, Shapiro, & Arnell, 1992). Although there is no consensus regarding the precise
nature of the mechanism(s) underlying the AB, most theories agree that the deficit in
processing T2 is associated with attentional resources being transiently disrupted by the
processing of T1 (Chun & Potter, 1995; Raymond, Shapiro, & Arnell, 1995; however, see
Olivers & Meeter, 2008; and Taatgen, Juvina, Schipper, Borst & Martens, 2009 for
alternative explanations).
In the present study, both the N2pc and PD, as well as behavioural performance,
were measured while participants performed a modified rapid serial visual presentation
(RSVP)/visual search task. The task here combined attentional-blink methodology with
59
those of the visual additional singleton search paradigm. The first target (T1) was a
number within an RSVP stream of letters and the second target (T2) was a colour singleton
that appeared within a visual search array that also contained a salient distractor singleton
(Figure 4.1). Subjects were instructed to first make a speeded response to T2 (by
identifying the orientation of a line inside the target singleton) and were then subsequently
probed to respond to T1 (by identifying whether the number in the RSVP stream had been
even or odd). Target and distractor processing ERPs to the T2 search array at short (within
the attentional blink) and at long (outside the attentional blink) separations from T1 were
then separately examined. Based on previous electrophysiological studies, it was
anticipated that target processing during visual search would be delayed during the blink
(Lagroix, Grubert, Spalek, Di Lollo & Eimer, 2015; Pomerleau, et al., 2014). Alternatively,
it was less clear was how distractor processing would be affected. If the distractor
suppression indexed by the PD reflects an active mechanism contingent on the observer
maintaining a high level of attention control, then it is expected that the AB would disrupt
this mechanism. However, if the PD reflects an exogenous process that is instead sensitive
to the physical properties of a stimulus, the component should remain unimpaired during
the AB.
4.2. Methods
4.2.1. Materials and Methods
The Research Ethics Board at Simon Fraser University approved the research
protocol used in this study.
4.2.2. Participants
Twenty students from Simon Fraser University participated after giving informed
consent. These students were given course credit for their participation as part of a
departmental research participation program. Eighteen subjects were included in the EEG
analysis (8 women, age 19.61, SD = 1.97; 3 left-handed), as two were excluded due to
excessive noise in the ocular channels. All subjects reported normal or corrected-to-
60
normal visual acuity and were tested for typical color vision, using Ishihara color test
plates.
4.2.3. Attentional Blink Task Stimuli and Apparatus
Stimuli were presented on a 23-inch, 120-Hz LCD monitor viewed from a distance
of 57 cm. RSVP streams were comprised of digits (x = 0.295, y = 0.361, 7.9 cd/ m2) and
uppercase letters (x = 0.295, y = 0.361, 7.9 cd/ m2) presented at a central fixation point.
Alphanumeric characters were approximately 1° in height and varied proportionally in
width. Visual search arrays were comprised of 10 unfilled circles presented equidistant
(9.2°) from a central fixation point. Each circle was 3.4° in diameter with a 0.3° thick outline.
Eight of the circles were uniformly colored non-targets, one was a target color singleton,
and one was a distractor color singleton. The target was dark yellow (x = 0.416, y = 0.519,
7.9 cd/ m2) and the distractor was red (x = 0.640, y = 0.324, 7.0 cd/ m2), and the non-target
circles were green (x = 0.288, y = 0.636, 7.9 cd/ m2). The red distractor singleton was the
most salient item in the search array (see: Gaspar & McDonald, 2014). A randomly
oriented vertical or horizontal gray line (x = 0.295, y = 0.361, 7.9 cd/ m2) was contained
within each of the circles. All stimuli were presented on a uniform black background (0.5
cd/ m2).
61
Figure 4.1. Example stimulus display from the experiment. T1 was a number presented amongst letters in an RSVP stream. T2 was an additional singleton search display where participants were instructed to identify the orientation of the line inside the yellow colour singleton. Participants were instructed to give a speeded response to the search array first and then identify the number as either even or odd.
4.2.4. Attentional Blink Task Procedure
For each trial, the display sequence was preceded by an 800-1,200 ms fixation
period. During this time, only the central fixation point was visible (Figure 4.1). In
preparation for the presentation of the display sequence, participants were instructed to
maintain fixation on the central point. The display sequence consisted of an initial 14-item
RSVP stream comprised of 13 letters and a single digit. Letter stimuli (A, B, C, D, E, F, G,
H, J, K, L, M, N, P, Q, R, S, T, U, V, W, X, Y, Z) were selected at random with the constraint
that the same letter could not appear twice in the stream. A digit stimulus (1, 2, 3, 4, 5, 6,
7, 8) was selected at random with the constraint that an equal number of even and odd
numbers would be presented within each block. The stimulus onset asynchrony (SOA)
between successive items in the RSVP stream was 100 ms. Upon the completion of the
RSVP stream, a search display was presented for 200 ms. The search array was
subsequently masked for 200 ms.
The first target (T1) was the digit inserted into the RSVP stream that appeared at
either the seventh (lag 8) or thirteenth (lag 2) position. The second target (T2) was the
target singleton in the search array. Participants were instructed to first make a speeded
response to T2 by identifying the orientation of the gray line inside the target singleton by
pressing one of two response buttons as quickly as possible. Participants were then
62
probed to indicate whether T1 had been an even or an odd number. After a response was
made to the probe, the next trial began.
The search display (T2) contained one target singleton and one highly salient
distractor singleton. Target and distractor locations were varied to produce the following
O2. Horizontal EOGs were recorded using two electrodes positioned 1 cm lateral to the
external canthi, and vertical EOGs were recorded using two electrodes positioned above
and below the right eye. All EEG and EOG signals were digitized at 512 Hz, referenced in
real time to an active common-mode electrode, and low-pass filtered using a fifth-order
sinc filter with a -3 dB cutoff at 104 Hz. Electrode offsets were monitored to ensure the
quality of the data. After the data acquisition, EEG data for each channel were high-pass
filtered (-3 dB point at 0.05 Hz) and then converted from 24-bit to 12-bit integers.
EEG processing and ERP averaging were performed using event-related potential
software system (ERPSS) (University of California, San Diego). A semi-automated
procedure was used to discard epochs of EEG contaminated by blinks, eye movements,
or excessive noise (Green et al., 2008). Any trial with an artifact within a 1-s interval (-200-
800 ms post-stimulus) was rejected. Artifact-free epochs associated with the various
display configurations of interest were then averaged separately to create ERP
waveforms. The resulting ERPs were digitally low-pass filtered (-3 dB point at 32 Hz) and
digitally re-referenced to the average of the left and right mastoids. All ERP amplitudes
and baselines were computed using a 200 ms pre-stimulus window. The averaged event-
related horizontal EOGs did not exceed 2 μV for any individual participant, indicating their
gaze remained within 0.3° of the fixation point for a majority of the trials (McDonald &
Ward, 1999).
The primary analysis focused on ERPs elicited by search displays with following
display configurations: (1) lag 2, lateral target, midline distractor; (2) lag 2, midline target,
lateral distractor, (3) lag 8, lateral target, midline distractor; (4) lag 8, midline target, lateral
distractor. On each trial, a search display contained a lateral singleton and a midline
singleton. Biasing a singleton to the midline on each trial allowed for an equal number of
trials where the N2pc and PD could be isolated.
For each participant, ERPs to the various search displays were collapsed across
left and right visual hemi-fields, as well as left and right electrodes, to produce waveforms
indexing the processing of a lateralized singleton. Lateralized ERP difference waveforms
were then computed for the display configurations of interest by subtracting the ipsilateral
waveform from the corresponding contralateral waveform at electrode sites P07 and P08.
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All statistics were performed on lateralized ERP difference waveforms. For all ERPs
shown here, negative voltages were plotted upward so that the N2pc would appear in
these difference waveforms as an upward deflection and the PD as a downward deflection.
The mean-amplitude of the N2pc was first measured in a window 230-290 ms post
stimulus onset. This window was determined a priori based on the findings of Hickey and
colleagues (2009) and was identical to the N2pc window set in Chapter 3. As it was
anticipated that the N2pc would be delayed during the AB, the window for lag 2 trials was
shifted by 30 ms to match the ~30 ms latency shift observed by Lagroix et al., 2015.
The PD was computed in a window 290-330 ms post stimulus onset, approximately
centered around the peak of the observed component. The 40 ms duration of the window
used to measure the component was selected to mirror the size of the statistical windows
used in the previous chapters but shifted later in time to account for later onset observed
here. Because the component appeared later than it had in the previous chapters, an
unbiased signed area measurement was also used to confirm the presence of the
component. Identical to what was done in Chapter 3, the signed positive area of the PD
was computed using each individual participant’s difference waveforms in a wide 200-350
ms post-stimulus interval. The signed positive area of the PD was subtracted from the
signed positive area of the baseline from -150-0 ms. This signal-minus-noise difference
was then statistically assessed using standard parametric statistics.
On midline target, lateral distractor trials, the PPC was computed in a 50 ms
window from 120-170 ms. This window is consistent with previous studies that have
typically reported the PPC to occur between 120-190 ms (Fortier-Gauthier et al., 2012;
Jannati et al., 2014; Leblanc, Prime, & Jolicœur, 2008).
Latency onsets were defined as the 50%-of-peak-amplitude voltage in the 0-200
ms interval for the PPC and 200-400 ms interval for the N2pc and PD. Statistical tests were
performed on jackknife-averaged ERPs and statistical thresholds were adjusted
accordingly (Ulrich and Miller, 2001). All statistics were computed relative to a 100 ms pre-
stimulus interval.
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4.3. Results
4.3.1. Visual search is delayed during the attentional blink
Response accuracy data is shown in Figure 4.2. The mean proportion of correct
responses to the first target (T1) was 91.2%. A t-test performed on the T1 data yielded no
significant difference for Lag 2 versus Lag 8 trials [t(17) = 1.23, P = .23]. As is common
procedure, the accuracy for the second target (T2) was computed using only those trials
where the T1 had been identified correctly. The mean proportion of correct responses to
T2 was 94.7%. A t-test performed on the T2 data also yielded no significant effect of lag
[t(17) = .50, P = .62].
The absence of an effect of lag on either T1 or T2 accuracy was not unexpected
given the experimental design used here. The present study sought to maximize response
accuracy in order that a maximal number of trials might be retained for the ERP analysis.
In order to deal with the response ceiling for accuracy, RTs were used as the dependent
measure of the attentional blink. The idea that response speed can be used to index the
AB was initially proposed by Ruthruff and Pashler (2001) and has been since supported
by studies that have used RT as a dependent measure (e.g., Ghorashi, Smilek & Di Lollo,
2007; LaGroix et al., 2015). Estimates of the RT were again based exclusively on trials
where correct responses were made to both T1 and T2. Median RTs to the onset of the
T2 search array were calculated for each observer at both lag 2 and lag 8. As shown in
Figure 4.2b, responses to the T2 search array were slower on lag 2 trials (890 ms) than
on lag 8 trials (816 ms). This 64 ms RT difference was found to be significant [t(17) =
11.05, p < .001], confirming that a substantial AB deficit had occurred on lag 2 trials.
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Figure 4.2. Main behavioural results: (A) Accuracy rates for T1 and T2 on both lag 2 and lag 8 trials. (B) Mean response times (across participants; in milliseconds) for lag 2 and lag 8 trials.
4.3.2. The N2pc is delayed within the attentional blink
Figured 4.3a shows grand averaged ERP waveforms contralateral and ipsilateral
to the lateral T2 target singleton for both lag 2 and lag 8 trials. For lag 8 trials, the N2pc
was measured as the difference in mean amplitude between contralateral and ipsilateral
activity at electrodes PO7/PO8 from 230 to 290 ms after the onset of T2. For lag 2 trials,
the window was shifted by 30 ms from 260 to 320 ms after the onset of T2. The mean
N2pc amplitudes for the lateral-target display configurations were found to differ
significantly from zero for both lag 2 [t(17) = 2.29, P = .03] and lag 8 [t(17) = 2.38, P = .03]
trials. A follow-up t-test further revealed that there was no difference in amplitude across
the two lag conditions [-.58 µV vs. -.56 µV; t(17) = .07, P = .94].
As shown in Figure 4.3b, although the N2pc did not differ in amplitude between
Lag 2 and Lag 8 trials, clear differences in the onset latency of the N2pc were evident,
with the N2pc occurring earlier on lag 8 trials than on lag 2 trials. A paired samples t tests
revealed that the N2pc to the T2 search array did in fact emerge 36 ms sooner at lag 8
than at lag 2 [288 ms vs. 252 ms; tc = 2.5, P = 0.02], confirming an AB in N2pc onset
latency. These findings corroborate the hypothesis that visual search is postponed during
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the period of the AB (Ghorashi et al., 2007) and are consistent with other ERP studies of
the AB that have shown the N2pc to be delayed when the lag between targets was shorter
(Lagroix et al., 2015; Pomerleau et al., 2014).
Figure 4.3. ERPs elicited by trials with displays containing a lateral target and a midline distractor. Time 0 reflects the onset of the search display, and negative voltage deflections are plotted above the x-axis, by convention. Waveforms were recorded over the lateral occipital scalp (electrodes PO7 and PO8). (A) ERPs recorded contralateral and ipsilateral to a distractor for lag 8 and lag 2 trials. (B) Contralateral-minus-ipsilateral difference waveforms for lag 8 and lag 2 trials.
4.3.3. The PPC is unaffected during the attentional blink
A PPC (positivity posterior contralateral) component was observed to occur on
midline target, lateral distractor trials. Thought to reflect pre-attentive sensory processing,
the PPC presents as an early positivity in the time interval of the N1 over parieto-occipital
scalp (Fortier-Gauthier et al., 2012; Jannati et al., 2013; Pomerleau et al., 2014). In the
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present study, the PPC component can be clearly seen in the difference waveforms on
trials where the salient distractor was the lateralized singleton (Figure 4.4b). To confirm
the presence of the PPC components, a pairwise t test compared the difference in mean
amplitude at electrodes PO7/PO8 from 120 to 170 ms post the onset of T2. The PPC was
determined to be significant on both Lag 2 [t(17) = 3.01, P = .008] and Lag 8 [t(17) = 2.94,
P = .009] trials. The PPC did not differ in either amplitude [t(17) = .64, P = .53] or latency
[tc = .22, P = .73] for either of the two lag conditions. Collectively, these data are consistent
with a pre-attentive role for the PPC: the proportional amplitudes and latencies for lag 2
and lag 8 trials support the idea that, unlike the PD, the PPC reflects a process unaffected
by a disruption of attentional control.
4.3.4. Individuals cannot recruit distractor suppression during the attentional blink
One of the principle questions asked in this chapter was whether the processing
indexed by the PD reflects an active mechanism contingent on top-down control. To test
this possibility, distractor processing was compared under conditions where the availability
of top-down control was restricted (during the AB) and unrestricted (outside of the AB).
Figured 4.4a shows grand averaged ERP waveforms contralateral and ipsilateral to the
lateralized T2 distractor singleton for both lag 2 and lag 8 trials. The PD was measured as
the difference in mean amplitude between contralateral and ipsilateral activity at
electrodes PO7/PO8 from 290 to 330 ms after the onset of T2. A one-way ANOVA on PD
mean amplitude yielded a main effect of lag [F(1,34) = 5.8, P = .02]. The presence of the
component was further confirmed using a paired samples t-test. The PD differed
significantly from zero on lag 8 [t(17) = 3.90, P = .001] but not on lag 2 [t(17) = 1.22, P =
.24] trials, which indicates that the distractor suppression mechanism was not recruited
during the AB. This finding was corroborated when the signed positive area was compared
to baseline noise [lag 8: t(17) = 3.31, P = .004; lag 2: t(17) = 1.19, P = .25]. The absence
of an observable PD on lag 2 trials indicates that the distractor suppression mechanism
indexed by the PD was not recruited during the AB.
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Figure 4.4. ERPs elicited by trials with displays containing a midline target and a lateral distractor. Time 0 reflects the onset of the search display, and negative voltage deflections are plotted above the x-axis, by convention. Waveforms were recorded over the lateral occipital scalp (electrodes PO7 and PO8). (A) ERPs recorded contralateral and ipsilateral to a distractor for lag 8 and lag 2 trials. (B) Contralateral-minus-ipsilateral difference waveforms for lag 8 and lag 2 trials.
4.3.5. Behavioural evidence during the AB revisited
In instances where the distractor is more salient than the target, behavioural
interference increases as target-distractor separation decreases. This pattern of
interference has been used to argue the misallocation of attention to a distractor (Caputo
2000a, 2000b, 2005; Mounts & Gavett, 2004), while others have attributed it to distractor
inhibition spreading to the location of a nearby target (Gaspar & McDonald, 2014; Jannati
70
et al., 2013). To test these competing interpretations here, a proximity analysis was
conducted on RT data for both lag 2 and lag 8. RTs were separated for the nearest-
distractor and farthest-distractor conditions and a repeated measures ANOVA with the
factors lag (lag 2 vs. lag 8) and proximity (Nearest-distractor vs. Farthest-distractor) was
computed to statistically assess the data. This test revealed no main effect for proximity
[F(1,17) = .903, P = .355] but a main effect for lag [F(1,17) = 66.10, p < .001]. The
interaction between proximity and lag was also found to be significant [F(1,34) = 13.42, P
= .001]. As illustrated in Figure 4.5, these results indicate two distinct patterns of
interference during visual search. For Lag 8 trials participants were slower (22 ms) to
respond to the target when it appeared close to the distractor versus when it appeared
furthest. For Lag 2 trials participants were instead faster (14 ms) to respond to the target
when it appeared close to the distractor versus when it appeared furthest.
Figure 4.5. Target-distractor RT distance effects. Mean response times (across participants; in milliseconds) for lag 2 and lag 8 trials where the target and distractor appeared adjacent to one another and on trials where they appeared furthest from one another.
4.4. Discussion
The purpose of the present research was to examine how mechanisms of object
selection are impacted by a transient disruption to attentional control. To this end,
electrophysiological activity was recorded while participants completed a task comprised
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of two well-known attention paradigms—the additional singleton paradigm, to measure
selective object processing, and the RSVP paradigm, to elicit the attentional blink. The AB
is a well-known behavioural consequence of the limitations of attention that can be
observed in dual-task paradigms where two target stimuli are presented in rapid
succession. The AB manifests as a deficit in reporting the second target stimulus (T2)
compared to the first target stimulus (T1). Although there is a vast literature dedicated to
debating precisely what causes the AB, it has been shown to be an effective means of
disrupting attention control (Akyürek et al., 2010; Brisson & Jolicœur, 2007; Dell'acqua et
al., 2006; Jolicoeur et al., 2006a; 2006b; Zhang et al., 2009). The present experiment
required participants perform the visual search task both within (lag 2) and outside of (lag
8) the AB to study how target and distractor processing were independently affected by
the availability of attentional control.
To date, a handful of electrophysiological studies have explored how selective
attentional processing during visual search is affected by the AB (e.g., Pomerleau et al.,
2011; Lagroix et al., 2015). These studies have revealed that the AB produces a transient
disruption in the ability to process the T2 visual search targets—that is, the AB results in
an impairment in guiding attention towards a relevant object in a timely manner (e.g.
Ghorashi and colleagues, 2007). Both the behavioural and ERP findings in the present
study are consistent with this hypothesis. Using visual search RT performance as the
dependent measure, a deficit in the processing of T2 was observed during the AB.
Relative to lag 8 trials, on lag 2 trials RTs were slower and the onset of the target N2pc
was delayed. These findings are consistent with those of Pomerleau et al. (2014), which
showed similar behavioural and electrophysiological delays during the AB period.
By comparison, only a single study has explored how distractor processing is
affected by the AB during visual search (Pomerleau et al., 2011). A primary motivation for
the current study was to examine whether the suppression of salient (but irrelevant) stimuli
is accomplished during the AB, if at all. In doing so, the current study also resolves an
important, outstanding question regarding the cognitive mechanism indexed by the PD.
The PD is thought to reflect a voluntary and flexible suppressive mechanism that can be
modulated by task instructions (Hickey et al., 2009; Hilimire et al., 2012). Such
endogenous processing would likely be disrupted during the AB interval, and would be
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evidenced by a delay and/or attenuation of the mean amplitude of the PD. Several studies
have offered evidence for this view and have shown the PD to reflect a top-down process
that allows observers to actively suppress salient, task irrelevant items and prevent
capture (e.g., Gaspar and McDonald, 2014; Jannati et al., 2013; Sawaki & Luck, 2010).
However, an alternate account of the PD is that it reflects an automatic process that
indexes the location—but does not necessarily the suppression of—expected, salient
distractors. According to this view, the PD is activated by the bottom-up properties of an
object and not based on top-down control (Fortier-Gauthier, Dell'Acqua & Jolicœur, 2013).
If this were the case, the PD should not be affected by the AB and should therefore be
approximately equal in both timing and amplitude at both lags. The present study
disconfirmed this latter hypothesis, as the PD elicited by the T2 display varied considerably
between lag 2 and lag 8. Whereas the PD was elicited to the lateralized distractor singleton
on lag 8 trials (outside of the AB), it was altogether absent on lag 2 trials (within the AB).
This result is consistent with the interpretation that there was a transient disruption in the
ability to suppress salient distractors during the AB while selective processing
mechanisms remain engaged processing T1.
Previous studies have found that observers are slower to respond to objects
presented in close proximity of a salient object, and that this behavioral search penalty is
reduced as the distance between the target and distractor increases (Awh, Matsukura &
Callejas & Lupiáñez, 2010). Behaviourally, this has been shown in antisaccade tasks
where individuals are instructed to make an eye movement away from an emotionally
neutral abrupt-onset stimulus presented in the periphery. High anxiety individuals are
slower to initiate a saccade away from this stimulus (Derakshan et al., 2009; Wieser, Pauli
& Mühlberger, 2009), which suggests that they have a reduced ability to volitionally
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override orienting toward a stimulus and commensurately reduced top-down attentional
control necessary to counteract the reflexive processes (Hutton & Ettinger, 2006).
Furthermore, high-anxiety individuals perform worse still on these antisaccade tasks under
higher levels of cognitive load (Berggren, Hutton, Derakshan, 2011; Berggren et al, 2013).
However, one shortcoming of the antisaccade task is that the salient stimulus is always
task-relevant—participants must first direct their attention to the stimulus onset in order to
make an eye movement away from it. This makes it difficult to determine whether the
slower saccades in high-anxiety individuals are the result of a deficit in the ability to inhibit
the stimulus or are the result of a deficit in executing a shift of attention away from the
stimulus.
Recently, it has been argued that an optimal way to assess salience- and goal-
driven attentional selection in high-anxiety individuals is with the additional singleton
paradigm (Moser et al., 2012; Moran & Moser, 2015; Moser, Moran & Leber, 2015). In the
additional singleton paradigm, observers locate a salient target defined by a unique
feature (i.e. a singleton, often a unique form) while simultaneously ignoring a more salient
distractor (often an item of a unique color). Using the additional singleton task, studies
have shown distractor interference to be exaggerated for individuals with high levels of
trait anxiety (Moran & Moser, 2015; Moser et al., 2012). These findings have been
interpreted as reflecting enhanced susceptibility in anxious individuals for distraction by
physically salient but irrelevant information. Using additional singleton paradigms, similar
findings have been reported for patients with other anxiety-related affective disorders
including depression (Bredemeier, Berenbaum, Brockmole, Boot, Simons & Most, 2011)
and posttraumatic stress disorder (PTSD; Esterman, Rosenberg & Noonan, 2013).
Collectively, these findings have provided strong support for an influential model
of anxiety known as the Attentional Control Theory (ACT; Derakshan & Eysenck, 2009
and Eysenck et al., 2007). According to ACT, individuals with high trait anxiety suffer from
a general deficit in top-down attentional control. This deficit is thought to primarily impair
inhibitory processing, increasing the influence of bottom-up attention and leading to a
greater sensitivity for irrelevant and distracting information. To compensate for this deficit,
high-anxiety individuals are hypothesized to invest additional processing resources,
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thereby allowing them to reach a standard level of behavioural performance under certain
circumstances (Eysenck et al., 2007).
Recent models of anxiety have further proposed that the impaired inhibitory control
exhibited by high-anxiety individuals may be associated with the impoverished ability to
engage proactive attentional control (Braver et al., 2007; Braver, 2012; Aron, 2011).
Proactive attentional control is necessary for the active maintenance of goal-related
information and serves to facilitate preparatory attentional biasing. Such proactive control
can anticipate distractor representations and prevent them from interfering with the
processing of task-relevant information (Geng, 2014). Alternatively, high-anxiety
individuals are thought to engage attention in a reactive manner by exerting processing
resources as needed, typically after a salient-but-irrelevant stimulus is encountered. The
default use of reactive attention is thought to reflect a deficit in maintaining an active and
persistent top-down attentional set, leading to an increased distractibility in anxious
individuals.
While trait anxiety appears to disrupt the ability to ignore distracting information,
the neural correlates of this effect are not well understood. Differences in attentional
biases between high- and low-anxiety individuals may be due to a reduced ability to apply
active suppression to irrelevant stimuli, a greater reliance on reactive shifts of attention,
or both. To investigate this, individuals were initially screened using the State-Trait Anxiety
Inventory (STAI; Spielberger et al., 1983), a 40-item self-evaluation questionnaire
pertaining to anxiety affect. Those whose trait anxiety scores were among the highest and
lowest were selected to participate in the ERP experiment. To measure the neural
correlates of attention, EEG was recorded while subjects performed an additional
singleton search task identical to that previously used by Gaspar and McDonald (2014).
In this task participants searched for a color-singleton target and on 50% of trials
attempted to ignore a more salient color-singleton distractor (Figure 5.1). Participants were
instructed to indicate whether the orientation of the line inside the target was either
horizontal or vertical. The relationship between anxiety and i) target processing ERPs and
ii) distractor suppression processing ERPs were then separately assessed.
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Figure 5.1. Trial Types. Example stimulus displays from the two experimental conditions. Subjects were instructed to attend to the yellow circle and to identify the orientation of the line inside of it. On 50% of trials, a salient distractor singleton was simultaneously presented within the display.
5.2. Methods
5.2.1. Materials and Methods
The Research Ethics Board at Simon Fraser University approved the research
protocol used in this study.
5.2.2. STAI Prescreen
In total, 218 students from Simon Fraser University volunteered to be prescreened
for potential inclusion into an EEG experiment. Students were prescreened using the
State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983), a 40-item self-evaluation
questionnaire pertaining to anxiety affect. Subjects were contacted and invited to
participate in the full EEG experiment if their trait-anxiety score was above 50 (N = 20;
high-anxiety group) or below 35 (N = 20; low-anxiety group).
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5.2.3. Participants
Forty students from Simon Fraser University participated after giving informed
consent. These students were given course credit for their participation as part of a
departmental research participation program. Prior to the EEG collection, subjects were
again asked to complete the STAI to ensure that they still fulfilled the predetermined
criteria for high- or low-anxiety. Of the 40 subjects, one was excluded due to excessive
noise in the ocular channels and another was excluded for failing to answer all questions
on the STAI. Of the remaining 38 participants, 19 (16 women, age 20.26, SD = 1.97; 1
left-handed) were characterized as high-anxiety and 19 (14 women, age 20.94, SD = 5.60;
4 left-handed) were characterized as low-anxiety. All subjects reported normal or
corrected-to-normal visual acuity and were tested for typical color vision, using Ishihara
color test plates.
5.2.4. Visual Search Task Stimuli and Apparatus
Stimuli were presented on a 23-inch, 120-Hz LCD monitor viewed from a distance
of 57 cm. Visual search arrays were comprised of 10 unfilled circles presented equidistant
(9.2°) from a central fixation point. Each circle was 3.4° in diameter with a 0.3° thick outline.
Eight or nine of the circles were uniformly colored non-targets, one was a target color
singleton, and one was a distractor color singleton (on distractor-present trials). The target
was dark yellow (x = 0.416, y = 0.519, 7.9 cd/m2) and the distractor was red (x = 0.640, y
= 0.324, 6.95 cd/m2), and the non-target circles were green (x = 0.288, y = 0.636, 7.85
cd/m2). A randomly oriented vertical or horizontal gray line (x = 0.295, y = 0.361, 7.89
cd/m2) was contained within each of the circles. All stimuli were presented on a uniform
black background (0.5 cd/m2).
5.2.5. Visual Search Task Procedure
On each trial, a search display was preceded by an 800-1,200 ms fixation period.
During this time only the central fixation point was visible. Upon the presentation of the
search display, participants were instructed to maintain fixation on the central point and to
identify the orientation of the gray line inside the target singleton by pressing one of two
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response buttons as quickly as possible. The search array remained visible for 100 ms
after a response was registered, at which point the next trial began.
Displays contained a target singleton and one distractor singleton on 50% of trials
(distractor-present trials). On the remaining 50% of trials, the target was the only singleton
in the array (distractor-absent trials). Target and distractor locations were varied to
produce the following display configurations: lateral target, no distractor (22.0%); midline
lateral target, no distractor. As previously mentioned, displays containing a lateral
singleton and a midline singleton enable isolation of lateralized the N2pc and PD
components because these midline singletons do not trigger ERP lateralizations
(Woodman & Luck, 2003; Hickey et al., 2009).
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For each participant, ERPs to the various search displays were collapsed across
left and right visual hemifields, as well as left and right electrodes, to produce waveforms
indexing the processing of a lateralized singleton. Lateralized ERP difference waveforms
were then computed for the display configurations of interest by subtracting the ipsilateral
waveform from the corresponding contralateral waveform at electrode sites P07 and P08.
As with all ERPs shown here, negative voltages were plotted upward so that the N2pc
would appear in these difference waveforms as an upward deflection and the PD as a
downward deflection. The mean amplitude of the PD was computed in a window 270-310
ms post stimulus onset, approximately centered around the peak of the component for
both groups. The 40 ms duration of the window was selected to mirror the size of the
statistical windows used in previous chapters but shifted later in time to account for later
onset observed here. Because the component appeared later than had been predicted a
priori, an unbiased signed area measurement was also used to confirm the presence of
the component. The signed positive area was measured within a 200-350 ms window and
subtracted from a baseline of equal duration.
On midline target, lateral distractor trials, mean amplitudes for an early N2pc was
computed in a 50 ms window from 170-220 ms. The early N2pc window used here was
identical to that used by Eimer and Kiss (2007) for testing early N2pcs to emotionally
salient stimuli. On lateral target, midline distractor trials, mean amplitudes for the N2pc
were computed in the same 230-290 ms post stimulus onset window used in the previous
chapters. All mean amplitudes were computed relative to a 100 ms pre-stimulus interval.
Finally, in addition to the mean amplitude measures, signed negative area was measured
within a 200-400 ms window from each individual participant’s contralateral-minus-
ipsilateral difference waveform. The signed negative area was then subtracted from a
baseline of equal duration, from -200-0 ms. The procedures used to compute signed area
in this chapter are identical to those described in Chapter 3 (Section 3.3.6.).
ERPs were also assessed separately for fast-response and slow-response trials.
Individual trials with RTs falling below or above the median RT for the display configuration
of interest were defined as fast-response and slow-response trials, respectively.
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Split-half reliability of the N2pc and PD components were conducted by randomly
splitting the data into two halves and computing correlations of the half-data mean
amplitude averages for each component. All split-half correlations were corrected for using
the standard method (Anastasi & Urbina, 1997).
5.3. Results
5.3.1. STAI scores
Subjects were recruited for the EEG experiment subsequent to an initial screening
that determined their STAI trait-anxiety score. To maximize the power to detect potential
differences in brain responses, an extreme-groups design was used (Yarkoni et al., 2010).
Subjects were chosen for these groups contingent on their prescreen score on the STAI
trait-anxiety scale: high-anxiety individuals were defined as those scoring 50 or more and
low-anxiety individuals were defined as those scoring 35 and below. These thresholds
were chosen based on similar thresholds from other recent ERP studies of anxiety (Fox,
Derakshan & Leor, 2008). Prior to their participation in the EEG experiment, subjects were
again asked to complete the STAI. Mean trait anxiety was 62.37 (SD = 6.0) for the high-
anxiety individuals (N = 20) and 26.79 (SD = 3.5) for the low-anxiety individuals (N = 20).
5.3.2. Search performance does not differ between individuals with high- and low-anxiety individuals
Differences in behavioral performance between high- and low-anxiety groups was
tested using a repeated measure analysis of variance (ANOVA) with ‘trial type’ (distractor
present and distractor absent) and ‘group’ (high and low) as factors. The ANOVA revealed
that responses were faster for distractor absent (671 ms) relative to distractor present
trials [693 ms; F(1,36) = 114.10, p < .001]. Although low-anxiety individuals were
marginally faster than high-anxiety individuals on both distractor absent (664 vs. 678) and
distractor present (685 vs. 702) trials, this difference was not found to be statistically
significant [F(1,36) = .28, P = .65]. The magnitude of the interference effect (measured as
the RT difference between distractor present and distractor absent trials) was also not
83
found to differ between groups [t(18) = .46, P = .65]; RT interference was nearly identical
for both the high- and low-anxiety group (23 ms and 21 ms, respectively).
Search performance was also assessed as a function of target-distractor distance
for both high- and low-anxiety participants. Similar to what was reported in Chapter 2, RTs
were observed to mostly decrease as the target and distractor appeared farther from one
another (Figure 5.2). To examine the dependency of interference on target-distractor
distance for the different anxiety groups, RTs were submitted to an ANOVA with a within-
subject factors of Target-Distractor Distance (1, 2, 3, 4, 5; see Methods) and a between-
subject factor for anxiety (high, low). Overall, RTs were longer for nearby distractors than
distant distractors, resulting in significant main effects for Target-Distractor Distance
[F(4,36) = 47.43, P < .001]; however, no between subjects effect was observed for anxiety
[F(1,36) = .28, P = .60]. This suggests that although RTs differed as a function of the target
and distractor proximity, this RT effect did not differ between the high- and low-anxiety
group.
Figure 5.2 Target-distractor RT distance effects. Mean response times (across participants; in milliseconds) for five target-distractor distances (d1- d5) for both high- and low-anxiety individuals.
Lastly, RT standard deviations were computed to determine if response speed was
more variable among either group. RT standard deviation was not found to differ between
high- and low-anxiety participants for either distractor present or distractor absent trials (ts
< 0.66, ps > .52).
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5.3.3. Suppression is preceded by an attentional shift to the distractor in high-anxiety individuals
Figured 5.3a shows grand averaged ERP waveforms for midline target, lateral
distractor trials for both high- and low-anxiety individuals. The PD was measured as the
difference in mean amplitude between contralateral and ipsilateral activity at electrodes
PO7/PO8 from 270 to 310 ms after the presentation of the search array. The mean PD
amplitudes for the lateral-target display configurations were found to differ significantly
from zero for both high- [t(18) = 2.25, P = .04] and low-anxiety [t(18) = 2.49, P = .02]
individuals. A split half reliability test found the PD to have a low but significant reliability
across the two halves of data (r = 0.39; P = 0.02).
The presence of the PD component was additionally confirmed by computing the
signed positive area within a 150 ms time window and subtracting it from an equally wide
pre-stimulus baseline (noise) interval (See methods). The PD was significant for both high-
[t(18) = 2.32, P = .03] and low-anxiety [t(18) = 2.65, P = .02] individuals. A follow-up t-test
further revealed that the PD did not differ across the high- and low-anxiety groups for either
mean amplitude [.47 µV vs. .55 µV; t(18) = .26, P = .80] or latency [278 ms vs. 273 ms; tc
= .35, P = .73].
For high-anxiety individuals, an N2pc was observed prior to the onset of the PD
component, with its early phase overlapping with the N1 component. Although beginning
quite early—at approximately 170 ms—this enhanced negativity is consistent with
2014). The early N2pc was measured as the difference in mean amplitude between
contralateral and ipsilateral activity at electrodes PO7/PO8 from 170 to 220 ms after the
presentation of the search array. The mean N2pc amplitude for the lateral-target display
configuration was found to differ significantly from zero for high-anxiety [t(18) = 3.00, P =
.008] but not for low-anxiety [t(18) = .66, P = .52] individuals.
85
Figure 5.3 PD ERPs elicited by trials with displays containing a midline target and a lateral distractor. Time 0 reflects the onset of the search display, and negative voltage deflections are plotted above the x-axis, by convention. Waveforms were recorded over the lateral occipital scalp (electrodes PO7 and PO8). (A) ERPs recorded contralateral and ipsilateral to a distractor for high- and low-anxiety individuals. (B) Contralateral-minus-ipsilateral difference waveforms for high- and low-anxiety individuals.
In the high-anxiety group, the presence of an N2pc preceding the PD may indicate
that—after an initial shift of attention to the distractor singleton—a corrective mechanism
was invoked to suppress the distractor and reorient attention toward the target (see Geng,
2014). This may reflect a distinct search strategy among high-anxiety individuals, whereby
reactive, rather than proactive, mechanisms of attentional control are more readily invoked
during visual search (Braver, Gray & Burgess, 2007; Fales et al., 2008). However, an
alternative explanation is that high-anxiety individuals exhibit greater variability in their
capacity to maintain top-down attentional control which could lead to a different sequence
of processing on different trials. In line with this notion, it is plausible that the distractor
86
captured attention only on the most inefficient subset of trials, whereas on trials where
performance was optimal, this initial capture of attention did not occur and distractor
processing would closely resemble that of the low-anxiety group. To test these
possibilities, distractor processing in high-anxiety individuals was separately assessed for
both fast and slow-response trials. Figure 5.5 illustrates the difference in distractor
processing ERPs for high-anxiety individuals on fast- and slow-response trials. Both the
early N2pc and PD component were present on both the fastest and slowest half of trials.
Statistically, neither the N2pc nor the PD were observed to differ in amplitude when tested
in the same windows used above (ts < 1.21, P > .24). A similar analysis also found no
difference in PD amplitude for the low-anxiety group [t(18) = 1.09, P = .29].
Figure 5.4 High-anxiety group ERPs for displays containing a midline target and a lateral distractor, separately for fast- and slow-response trials. (A) ERPs recorded contralateral and ipsilateral to a distractor for fastest and slowest trials. (B) Contralateral-minus-ipsilateral difference waveforms.
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5.3.4. Differences in target processing between high-anxiety and low-anxiety individuals
To assess the relationship between selective target processing and anxiety, target
N2pc waves were isolated for lateral target, distractor absent display configurations. Trials
where the distractor was absent were used to assess target processing here, as the N2pc
elicited on these trials would in no way be confounded by any attentional processing
associated with the salient distractor (see Chapter 2 for an explanation of how N2pc
amplitude can be modulated by distractor processing). Figured 5.5a shows grand
averaged ERP waveforms for lateral target, distractor absent trials for both high- and low-
anxiety individuals. The N2pc was measured as the difference in mean amplitude between
contralateral and ipsilateral activity at electrodes PO7/PO8 from 230 to 290 ms after the
presentation of the search array. The mean N2pc amplitudes for these lateral-target
display configurations were found to differ significantly from zero for both high- [t(18) =
5.57, p < .001] and low-anxiety [t(18) = 2.87, P = .01] individuals. An internal consistency
test found this N2pc to be highly reliable (r = 0.69; P < 0.001).
Figure 5.5b illustrates the difference in target processing ERPs for high- and low-
anxiety individuals. In addition to the conventional mean amplitude, the N2pc was isolated
from the waveform by computing the signed negative area within a 200 ms time window
and subtracted from an equally wide pre-stimulus baseline (noise) interval. Despite
appearing to differ in Figure 5.5b, neither the mean of the resultant N2pc area nor mean
amplitude were not found to reach statistical significance [t(18) = 1.702; P < .11; t(18) =
1.49; P = .15]2. The onset latency was also not found to differ between high- and low-
anxiety individuals [244 ms vs. 250 ms; tc = .95, P = .36].
2 It should be noted that the resultant mean amplitudes did not significantly differ due to a single
outlier in the high-anxiety group that had a large positivity in the N2pc time range. When the subject with the most extreme positive amplitude was removed from each group, this difference was found to reach significance [t(17) = 2.195, P = .04].
88
Figure 5.5 N2pc ERPs elicited by trials with displays containing a lateral target and no distractor. Time 0 reflects the onset of the search display, and negative voltage deflections are plotted above the x-axis, by convention. Waveforms were recorded over the lateral occipital scalp (electrodes PO7 and PO8). (A) ERPs recorded contralateral and ipsilateral to a target for high- and low-anxiety individuals. (B) Contralateral-minus-ipsilateral difference waveforms for high- and low-anxiety individuals.
To determine if response efficiency was associated with a unique sequence of
target processing, differences in target selection ERPs were examined separately for fast-
and slow-response trials. As can be seen in Figure 5.6, the N2pc component did not differ
for the high-anxiety group on fast- versus slow-response trials [t(18) = 0.05, P = .96]. In
contrast, the N2pc was observed to be markedly attenuated for the low-anxiety group on
slow-response trials [-0.24 vs. -0.87 μV; t(18) = 3.38, P = .003]. A reduction in the
amplitude of the N2pc component on slow response trials has been previously reported
by Jannati and colleagues (2013). Considered together, the results here indicate that
89
inefficient search is associated with a reduction in target processing for low-anxiety
individuals; however, no such relationship exists for the high-anxiety group.
Figure 5.6 ERPs for displays containing a midline target and a lateral distractor, separately for fast- and slow-response trials. (A) High-anxiety group ERPs recorded contralateral and ipsilateral to a distractor for fastest and slowest trials. (B) High anxiety group contralateral-minus-ipsilateral difference waveforms for high- and low-anxiety individuals.
5.4. Discussion
High levels of trait anxiety are associated with an increased sensitivity to threat-
related information, even when that information is known to be behaviourally
inconsequential (Bar-Haim et al., 2007). This negative attentional bias has been linked to
an impairment in the ability to filter out emotionally salient information (e.g., Ansari &
Future studies should seek to use the PD to explore whether this impaired suppression of
distracting information may serve as a useful index for differentiating the variable impact
of the aging process. The PD may prove a functional marker for identifying differences in
cognitive processing that could predict healthy aging and preserved top-down modulation
in older adults.
6.3.3. Molecular biology, genetics, and selective attention
Although the clear majority of research on selective attention has sought to
understand the neural mechanisms associated with processing task-relevant and task-
irrelevant stimuli, separate from this line of inquiry are other studies that have sought to
assess the role particular neurotransmitters have on attentional control. For example,
neurotransmitters, such as dopamine, norepinephrine, and acetylcholine are often
implicated in the control of attention. Neurons that produce these neurotransmitters—
found largely throughout the brainstem and midbrain nuclei—send dense projections to
the prefrontal cortex, where attentional control signals are generated, as well as to
posterior sensory regions, where ERP correlates of selective attention manifest. Although
the clinical significance of these neurotransmitter systems and attentional control has been
extensively researched, not much extant evidence has sought to directly relate differences
in neurotransmitter production to differences in neural signals. Future research might seek
to assess these relationships by examining how functional gene variants that affect
neurotransmission might also affect attentional neural processing. It would be interesting
to see if there exists a relationship between an individual's genotype, distraction, and the
PD component. Such a study would be the first of its kind, to link molecular genetics with
an attentional ERP component.
100
6.4. A proposed stream for visual processing
Figure 6.1. Adapted from Janatti et al., 2013, a proposed hypothetical processing stream thought to occur during the fixed-feature variant of the additional singleton search task. Listed below each stage is the ERP component associated with that level of processing.
Adapted from Figure 7 in Jannati et al. (2013), Figure 6.1 illustrates an updated
proposal for a hypothetical attentional processing stream during visual search. At the pre-
attentive stage, the visual system first processes an entire scene in mass parallel,
encoding all objects on a topographical salience map proportional to their sensory inputs.
These sensory inputs can over time be altered by cognitive inputs that reflect dimensional
weighting, training, selection history, etc... Next, at the attentive stage, the saliency map
is scanned and the objects that elicit the greatest activations generate “attend-to-me”
signals and are selected. Over time, attention has built up a top-down module/heuristic
that contains a functional template of what the target and the distractor are. The location
of singleton that matches the target template is selected for enhanced processing while
the location of the singleton that matches the distractor template is selected for
suppression. Only information located at the enhanced location can be subsequently
identified and consolidated in memory.
The proposed model relies on several theoretical assumptions on how attention
may work during a competitive visual search task. First, the model necessitates that
individuals be able to simultaneously select more than one spatial location at a given
moment. Evidence for the parallel allocation of attention to multiple spatial locations come
101
from a series of recent papers by Grubert and Eimer (2015; 2016), who report that—when
an observer is instructed to report multiple feature-specific targets—the attentional set can
be flexibly configured to select the items in parallel. Since the top-down attentional
templates necessary for visual search are assumed to be stored in visual working memory,
the upper limit of the number of objects that can be selected in parallel would likely
correspond to an individual’s working memory capacity. This notion is consistent with the
finding reported in Chapter 3, where the group of individuals with lowest vWM scores
(ranging from 1.60 to 2.13), failed to elicit the PD—that is, they failed to maintain a template
for two items (the target and the distractor).
Figure 6.2. Hypothetical resolving of a visual search task based on the input image shown. The stars (top) represent the stimuli’s activation on the saliency map, with increased brightness denoting greater salience. The saliency map is then scanned by attention and suppression/enhancement are applied contingent on top-down attentional templates.
Another assumption of this proposed model is that top-down control is applied both
at pre-attentive and attentive stages of processing, albeit in functionally distinct ways. At
a pre-attentive stage, top-down control can act to increase or decrease the sensitivity for
sensory processing based on low-level features (e.g., colours, orientations, intensities).
This form of top-down control would serve to up-weight and down-weight the feature
dimensions of behaviourally relevant and irrelevant objects, altering their representation
on the salience map. This is consistent with several other models of selection which
propose top-down control to have an impact prior to the construction of a master saliency
Itti & Koch, 2001). This form of top-down control would be more reflexive, more easily
reset, and more sensitive to aspects such as selection history. In contrast, top-down
control at the attentive stage would reflect a more specialized process that would serve to
determine the flow processing instructions. This form of top-down modulation would more
closely resemble a Labergian module of attentional control (LaBerge, 2002). Here, this
control module requires iterative feedback to instantiate the higher-order attentional
instruction, be it to enhance or suppress processing. After a number of trials, the task
becomes routine, the instructions are consolidated and the attention module activated.
Although a distinction between forms of top-down attentional control is consistent with
some limited empirical findings (e.g., Ganis & Kosslyn, 2007), future research will be
necessary to establish the scope and the influence for such mechanisms to bias
attentional selection.
103
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