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Neural correlates of cue retrieval, task set
reconfiguration, and rule mapping in the explicit
cue task switching paradigm
STEPHANIE TRAVERSa and ROBERT WESTb
aDepartment of Psychology, Luther College, Decorah, Iowa, USAbDepartment of Psychology, Iowa State University, Ames, Iowa, USA
Abstract
Event-related brain potentials (ERPs) were used in two experiments to examine the neural correlates of processes
underlying task switching in the information-reduction task switching paradigm. Each experiment included 22
participants. The paradigm included two cues for each task. This element of the design allowed us to differentiate the
ERP correlates of cue retrieval, task set reconfiguration, and rulemapping. TheERPdata revealed a parietal slowwave
that was sensitive to processes associated with cue retrieval and task set reconfiguration and a frontal-polar slow wave
that was sensitive to processes associated with rule mapping. These findings further the proposal that an endogenous
act of control supporting processes related to task set reconfiguration and rule mapping may facilitate performance of
the explicit cue task switching paradigm.
Descriptors: Task switching, Cognitive control, Event-related potentials, Stroop task
The ability to flexibly switch between tasks has been taken as a
hallmark of efficient executive or cognitive control (Meyer &
Kieras, 1997; Miller & Cohen, 2001; Rogers & Monsell, 1995).
Studies incorporating behavioral methodologies have revealed
that multiple cognitive processes (e.g., cue retrieval, task set
reconfiguration, and rule mapping) may support one’s ability to
switch between tasks (Allport, Styles, & Hsieh, 1994; Logan &
Bundesen, 2003, 2004; Mayr & Kliegl, 2003; Monsell & Mizon,
2006; Schneider & Logan, 2005). There has also been some
progress made in using event-related brain potentials (ERPs) to
examine the temporal dynamics of processes underlying task
switching (Kieffaber & Hetrick, 2005; Kray, Eppinger, &
Mecklinger, 2005; Rushworth, Passingham, & Nobre, 2002,
2005). This research has revealed that task switching can elicit
modulations of the ERPs that are distributed over the frontal and
parietal regions of the scalp that may be differentially related to
discrete processes underlying task switching (Kieffaber &
Hetrick, 2005; Kray et al., 2005; Nicholson, Karayanidis,
Bumak, Poboka, & Michie, 2006). One limitation of the extant
ERP literature involves an ambiguity in associating distinct
modulations of the ERPs with the different cognitive processes
that are thought to underlie task switching. The current study
sought to address this issue using a paradigm that allowed us to
isolate the neural correlates of processes associated with cue
retrieval, task set reconfiguration, and rule mapping.
The information-reduction task switching paradigm allows
one to distinguish the influence of processes associated with cue
retrieval (i.e., the recovery of the cue–task association from
memory), task set reconfiguration (i.e., preparing the informa-
tion processing system for one or another task), and rule
mapping (i.e., maintenance of an association between arbitrary
cue–task pairs) on the efficiency of task switching (Logan &
Bundesen, 2003; Mayr & Kliegl, 2003; Monsell &Mizon, 2006).
The development of this paradigm was motivated by the
confounding of these processes that is inherent in the typical
comparison of task repetitions and task alternations in studies of
task switching (Logan & Bundesen, 2003; Mayr & Kliegl, 2003).
The confounding of these processes results from the fact that for
task repetitions both the cue and task are the same on consecutive
trials, whereas for task alternations both the cue and the task
change on consecutive trials. This characteristic of task alterna-
tions makes it impossible to determine whether differences
between task alternations and task repetitions arise from the
influence of processes supporting the retrieval of the task set from
memory or the influence of processes supporting preparation for
the upcoming task.
In the information-reduction paradigm each task is associated
with two cues, allowing one to consider three types of trials. Cue
repetitions are functionally identical to task repetitions in the
typical task switching paradigm and represent trials where the
cue and task are the same on consecutive trials. Task repetitions
represent trials where the cue changes from one trial to the next
but the task remains the same. Task alternations reflect trials
where both the cue and the task change on consecutive trials.Address reprint requests to: Robert West, W112 Lagomarcino Hall,
Iowa StateUniversity, Ames, IA 50011,USA. E-mail: [email protected]
Psychophysiology, 45 (2008), 588–601. Wiley Periodicals, Inc. Printed in the USA.Copyright r 2008 Society for Psychophysiological ResearchDOI: 10.1111/j.1469-8986.2008.00658.x
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Within this paradigm the influence of processes related to cue
retrieval can be localized to differences between cue repetitions
and task repetitions, and the influence of processes related to task
set reconfiguration and rule mapping can be localized to
differences between task repetitions and task alternations (Mayr
& Kliegl, 2003).
Studies using the information-reduction paradigm have
provided behavioral evidence indicating that cue retrieval, task
set reconfiguration, and rule mapping may all contribute to task
switching. A number of studies have revealed slower response
time for task repetitions than for cue repetitions, providing
evidence for the influence of cue retrieval on task switching
(Logan & Bundesen, 2003; Mayr & Kliegl, 2003; Monsell &
Mizon, 2006). The size of this effect decreases as the cue-to-
stimulus interval (CSI) increases (i.e., as individuals have more
time to retrieve the cue–task association from memory; Mayr &
Kliegl, 2003; Monsell & Mizon, 2006) and with practice (i.e., as
the cue–task association becomes stronger or easier to retrieve
from memory; Logan & Bundesen, 2003). The reliability of
differences in response time between task repetitions and task
alternations has been somewhat mixed across studies. Beginning
withMayr and Kliegl, a number of investigators have found that
this difference is significant across a variety of tasks (Monsell &
Mizon, 2006; Nicholson et al., 2006) providing evidence for the
influence of processes associated with task set reconfiguration
and rule mapping. In contrast, Logan and Bundesen found that
response time for task repetitions and task alternations did not
differ in a number of experiments. This latter finding led Logan
and Bundesen to conclude that cue retrieval, rather than task set
reconfiguration, was the primary determinant of response
slowing related to task switching.
One principal difference between the studies of Mayr and
Kliegl (2003) and Logan and Bundesen (2003) is reflected in the
use of nontransparent task cues (i.e., where there is no a priori
association between the cues and tasks) or transparent task
cues (i.e., where there is an a priori association between the
cues and tasks), respectively. As an example, if the task is to
identify the shape or color of a stimulus, a transparent task cue
for the shape taskmight be ‘‘shape’’ or ‘‘S’’ and a nontransparent
task cue might be ‘‘##’’ or some other arbitrary stimulus. The
effect of cue type was examined in a study where performance
was directly compared for transparent and nontransparent
task cues (Logan & Bundesen, 2004). Data from this study
revealed response slowing between task alternations and task
repetitions when nontransparent cues were used that was
eliminated with extended practice. This finding led to the
suggestion that response slowing between task repetitions and
task alternations was primarily related to acquiring the novel
cue–task associations (i.e., rule mapping; Logan & Bundesen,
2004; Logan & Schneider, 2006; Mayr & Kliegl, 2003) rather
than task set reconfiguration. However, other work has
revealed reliable slowing of response time between task alterna-
tions and task repetitions with transparent task cues when task
alternations reflect no more than 25%–33% of the total trials
(Monsell & Mizon, 2006). This finding has been interpreted as
indicating that processes related to task set reconfiguration may
also contribute to task switching in some contexts (Monsell &
Mizon, 2006).
A number of investigators have used the explicit cue task
switching paradigm in conjunction with ERPs to consider the
neural correlates of task switching (Kieffaber & Hetrick, 2005;
Kray et al., 2005; Rushworth et al., 2002, 2005; West, 2004).
Examination of the cue-locked data has revealed modulations of
the ERPs that are sensitive to processes underlying task
switching. Task switching may be related to an increase in the
amplitude of the frontal P2/frontal P3 (Rushworth et al., 2002,
2005) and is consistently related to an increase in the amplitude of
the parietal P3 (hereafter P3) and the parietal slow wave
(Kieffaber & Hetrick, 2005; Rushworth et al., 2002, 2005; West
& Moore, 2005). Specifically, Kieffaber and Hetrick used
spatiotemporal principal components analysis to demonstrate
that the P3 and parietal slow wave reflected overlapping but
distinct components that were differentially sensitive to task
mixing (i.e., P3) or task switching (i.e., parietal slow wave).
Research using ERPs to examine the neural correlates of task
switching has incorporated a variety of cues, stimuli, and tasks,
leading to the suggestion that the influence of task switching on
the P3 and parietal slow wave reflects the expression of a set of
processes that are not limited to the particular set of task
demands.
Within the context of the information-reduction paradigm,
the effect of task switching on the parietal slowwave could reflect
the influence of processes associated with cue retrieval, task set
reconfiguration, or rule mapping (Nicholson et al., 2006). The
association of the parietal slow wave with cue retrieval would
follow from work examining the neural correlates of episodic
memory retrieval, where the ERPs are typically more positive
over the parietal region for recognition hits than for new items or
misses (i.e., parietal old/new effect) beginning around 400 ms
after stimulus onset (for a review, see Rugg, 2004). In contrast,
the finding that the influence of task switching on the parietal
slowwave is sensitive to the demands of the to-be-performed task
(West & Moore, 2005) may indicate that this modulation of the
ERPs is associated with processes underlying task set reconfi-
guration. Data from a study by Nicholson et al. seem most
consistent with the latter interpretation of the parietal slowwave,
as in this study the amplitude of this modulation was greater for
task alternations than for task repetitions.
In addition to effects of task switching on the P3 and parietal
slow wave, there is some evidence that task switching can elicit
slow wave activity over the frontal region of the scalp (Rush-
worth et al., 2005). West and Moore (2005) observed greater
positivity over the left frontal region for task alternations than
for task repetitions in a study using Stroop stimuli (Stroop,
1935). The frontal slow wave related to task switching was
greater in amplitude for color identification trials than for word
identification trials. Variation in the amplitude of the frontal slow
wave between the color and word tasks may indicate that this
modulation of the ERPs was sensitive to factors affecting task set
reconfiguration such as differences in response dominance
between the tasks (Allport et al., 1994; MacDonald, Cohen,
Stenger, & Carter, 2000). In contrast to the findings of West and
Moore, frontal slowwave activity has not been observed in other
studies that employed simple tasks requiring perceptual judg-
ments (Kieffaber & Hetrick, 2005; Nicholson et al., 2006;
Rushworth et al., 2002). Together these data may indicate that
frontal slow wave activity related to task switching is somewhat
dependent upon task demands.
EXPERIMENT 1
In the current experiments we used the information-reduction
task switching paradigm to examine the processes underlying
ERPs and task switching 589
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modulations of the ERPs that are sensitive to task switching. In
the task, individuals received one of four task cues followed by an
incongruent Stroop color–word stimulus (e.g., RED presented in
blue; Stroop, 1935). Stroop stimuli were used in order to
capitalize on the natural dominance of word reading over color
naming so that the effects of task difficulty onmodulations of the
ERPs related to task switching could be considered (MacDonald
et al., 2000; West & Moore, 2005). Twenty-five percent of the
trials were task alternations, which, according to the findings of
Monsell and Mizon (2006), should maximize the likelihood of
eliciting processes associated with task set reconfiguration.
Finally, a relatively long CSI was used so as to reduce the
temporal confounding of processes elicited by the cues and the
target stimuli. We limited our consideration to the cue-locked
ERP data because this is where one might expect the neural
correlates of cue retrieval, task set reconfiguration, and rule
mapping to be expressed (Kieffaber & Hetrick, 2005; Monsell &
Mizon, 2006).
Our predictions were relatively straightforward. If variation
in the amplitude of the P3, parietal slow wave, or frontal slow
wave elicited during the CSI is related to cue retrieval, the
amplitude of these components should be greater for task
repetitions and task alternations than for cue repetitions (Logan
& Bundesen, 2003). In contrast, if the parietal and frontal slow
waves are associated with processes underlying task set
reconfiguration or rule mapping, the amplitude of these
modulations of the ERPs should be greater for task alternations
than for cue and task repetitions (Logan & Bundesen, 2004;
Mayr & Kliegl, 2003; Nicholson et al., 2006). Furthermore, if
these modulations of the ERPs are sensitive to processes
underlying task set reconfiguration, their amplitude may differ
for the color and word tasks, given the differential attentional
demands of color and word identification (Allport et al., 1994;
MacDonald et al., 2000). In contrast, if the parietal and frontal
slow waves reflect processes associated with rule mapping, the
amplitude of these modulations of the ERPs may be similar for
the color and word tasks, as the cue–task association is equally
novel for both cases.
Method
Participants
Twenty-two individuals (10 men and 12 women) participated in
the study for course credit. The age of the participants ranged
from 18 to 22 years (M5 19.68). Twenty of the participants were
right-handed and 2 were left-handed. The Human Subjects
Institutional Review Board of the university approved the study,
and all participants provided informed consent.
Materials and Procedure
The experiment consisted of a key acquisition phase, a cue
practice phase, and an experimental phase. Throughout the
experiment, task cues and target stimuli were presented on a
black background on a 17-in. CRTcomputer monitor. The cues
and targets were presented in the center of the display.
Participants advanced to the next phase or block of the task by
pressing the space bar.
The key acquisition phase included 16 trials (4 for each color)
and was designed to establish the mapping between the colors
and the appropriate response keys. In this phase, participants
viewed strings of Xs that were presented in one of four colors.
Participants used the index and middle fingers of the right and
left hands to respond by pressing a key that corresponded to the
color in which the Xs appeared (v5 red5 left middle,
b5 blue5 left index, n5 green5 right index, and m5 yel-
low5 right middle).
The purpose of the cue practice phase was to establish the
mapping between the cues and the tasks. The practice phase
included 48 trials and followed the key acquisition phase. The
word and color tasks were intermixed during the practice phase.
Half of the trials required a word response and half of the trials
required a color response. Each trial began with the presentation
of a cue that indicated whether the word or the color was relevant
for that trial. There were two cues for each task (word cues
@@@and%%%; color cues ### and $$$) that were presented
equally often during the practice phase. Task cues were presented
for 250 ms in light gray at the center of the display. Following the
task cues the screen was blank for 750 ms and then the target
stimuli were presented. The 12 target stimuli were incongruent
Stroop color–words that represented all possible pairings of the
colors and words. During the practice phase the target stimuli
remained on the screen until a response was made. Following the
response, visual feedbackwas presented on the display indicating
whether the response was ‘‘CORRECT’’ or ‘‘INCORRECT.’’
The feedback was presented for 1000 ms. The screen was blank
for 500 ms following the feedback, and then the task cue for the
next trial was presented.
The experimental phase included mixed and pure task blocks
and followed the practice phase. The mixed blocks were
completed before the pure blocks. The mixed blocks included
three types of trials (cue repetitions, task repetitions, and task
alternations), and 10 blocks of 84 trials each. There were 2 pure
task blocks of 97 trials each. One pure task block required word
identification and the other required color identification.
Although uninformative, each of the task cues was presented
for the pure trials in order to match the presentation and timing
parameters of the mixed blocks. Half of the participants
completed the color block first, and the other half completed
the word block first.
Participants were randomly assigned to one of two trial lists in
the experimental phase. Within these lists, the presentation order
of the trials was guided by the following constraints. The pairing
of the four task cues, four responses, and 12 incongruent color–
word stimuli appeared equally often within the blocks. No trial
type appeared consecutively on more than two trials, and no
single Stroop stimulus appeared on consecutive trials. Therewere
420 switch trials (task repetitions or task alternations) and 420
nonswitch trials (cue repetitions). Half of the trials required a
word response and the remaining trials required a color response.
For the switch trials, there were 210 task repetitions and 210 task
alternations. The four task cues were distributed equally across
the blocks with the following constraint. Because the number of
cue combinations that can indicate a change in task is twice that
of the number of cue combinations used for the switch and
nonswitch trials (Mayr & Kliegl, 2003), only one cue transition
was used for each of the task switch conditions (e.g., ### to
@@@ for the switch from color to word). To ensure that
roughly equal numbers of trials contributed to the analyzed data
for each trial type, 210 cue repetitions were excluded from the
analyses. The excluded trials were determined a priori and were
equally distributed within the blocks. This resulted in 210 cue
repetitions, 210 task repetitions, and 210 task alternations, which
were equally divided between color andword identification trials,
being available for the analyses. The timing parameters were the
590 S. Travers and R. West
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same as in the practice phase with the exception that the target
stimuli were presented for 400 ms and then the screen was blank
until 500 ms after the response.
Electrophysiological Recording and Analysis
The electroencephalogram (EEG, bandpass 0.01–100 Hz,
digitized at 256 Hz, gain 2500, 12 bit A/D conversion) was
recorded from an array of 45 tin electrodes sewn into an Electro-
cap or affixed to the skinwith an adhesive patch (Fpz, Fz, Pz, Oz,
Iz, Fp1, Fp2, Af3, Af4, F3, F4, F7, F8, F9, F10, Fc1, Fc2, Fc5,
Fc6, Ft9, Ft10, C3, C4, T7, T8, Cp1, Cp2, Cp5, Cp6, P3, P4, P7,
P8, Po3, Po4, O1, O2, Po9, Po10, leftmastoid, rightmastoid, left
lateral ocular, right lateral ocular, left inferior ocular, and right
inferior ocular) that was interfaced to an Isolated Bioelectric
Amplifier (James Long Company, Carogo Lake, NY) and a
Daqbook/112 (IO Tech, Inc., Cleveland, OH) digitizer. Vertical
and horizontal eye movements were recorded from the ocular
electrodes. During recording all electrodes were referenced to
electrode Cz. For data analysis, electrodes were referenced to an
average reference (Picton et al., 2000), electrodeCzwas reinstated,
and a 20-Hz zero-phase-shift low-pass filter was applied.
ERP epochs were extracted off-line and included 200 ms of
activity before and 1000 ms of activity after presentation of the
task cue. Ocular artifacts associated with blinks were corrected
using a covariance technique that simultaneously modeled
artifact and artifact-free EEG (Sourcesignal Imaging, San
Diego, CA). Trials contaminated by other artifacts (peak-to-
peak deflections over 100 mV) were rejected before averaging.
ERPs were averaged for correct responses for color pure trials
(M5 90.14, SD5 3.62), word pure trials (M5 91.14,
SD5 3.88), color cue repetitions (M5 89.68, SD5 6.39), word
cue repetitions (M5 89.86, SD5 5.38), color task repetitions
(M5 90.55, SD5 6.21), word task repetitions (M5 93.23,
SD5 5.71), color task alternations (M5 86.59, SD5 9.33),
and word task alternations (M5 92.41, SD5 5.89). Mean
differences in ERP amplitude across task conditions were
quantified in a series of 2 (dimension) � 2 (trial) � 3 or 5
(electrode) ANOVAs using the Huynh–Feldt (1976) epsilon
adjusted degrees of freedom when necessary (Jennings, 1987).
For these analyses mean amplitude was measured in four
consecutive epochs (200–400 ms, 400–600 ms, 600–800 ms,
800–1000 ms). The first epoch was intended to capture the time
course of the P3 and the three remaining epochs the time course
of the parietal and frontal-polar slow waves. When significant
effects were observed across consecutive intervals, further
analyses were performed including the additional variable epoch
to examine possible differences in amplitude over time. The
analyses for the P3 and parietal slow wave included electrodes
P3, Pz, and P4 and the analyses for the frontal-polar slow wave
included electrodes F7, Fp1, Fpz, Fp2, and F8. Selection of the
electrodes for the P3 and parietal slow wave was based on the
findings of previous research (Kieffaber &Hetrick, 2005; Kray et
al., 2005; Rushworth et al., 2002, 2005); because the frontal-
polar slow wave has not been well characterized in previous
research, the selection of electrodes for the analyses was guided
by where the modulation appeared to be maximal in amplitude
across the scalp. Significant interactions involving the variable
electrode were followed by analyses of normalized voltage
(McCarthy & Wood, 1985). The results of the analyses for the
normalized data are reported in the text. When post hoc analyses
required more than one comparison, the Bonferroni adjusted
p value was used (i.e., .05/number of comparisons).
Results
All inferential statistics are significant at the po.05 level unless
otherwise noted and partial eta-squared (Z2p) is reported as an
index of effect size.
Behavioral Data
The proportion of correct responses and mean response time
data for Experiment 1 are reported in Table 1. The effect of task
mixing was examined in a pair of 2 (dimension) � 2 (trial: pure
trials or cue repetitions) ANOVAs. These analyses revealed
lower accuracy, F(1,21)5 54.63, Z2p 5 .72, and slower response
time, F(1,21)5 242.18, Z2p 5 .92, for cue repetitions than for pure
trials. The effect of cue retrieval was examined in a pair of 2
(dimension) � 2 (trial: cue repetitions or task repetitions)
ANOVAs. In these analyses the main effect of trial was
marginally significant for response accuracy, F(1,21)5 4.06,
p5 .06, Z2p 5 .16, and was not significant for response time,
F(1,21)5 2.29, p4.15, Z2p 5 .10, indicating that cue retrieval had
relatively little impact on the behavioral data. Theweak influence
of cue retrieval probably resulted from the long CSI. The effect of
task switchingwas examined in a pair of 2 (dimension) � 2 (trial:
task repetition or task alternation) ANOVAs. Response
accuracy was similar for these two trial types, F(1,21)5 1.31,
p4.25, Z2p 5 .06, and response time was slower for task
repetitions than for task alternations, F(1,21)5 10.77, Z2p 5 .34.
This latter finding reflects the opposite ofwhatwould be expected
based on previous research.
In summary, the behavioral data from Experiment 1 were
only partially consistent with findings from previous research.
These data revealed significant effects of taskmixing on response
time and accuracy, with individuals being slower and less
accurate for cue repetitions than for pure trials. The effect of
cue retrieval was rather weak, probably resulting from the length
ERPs and task switching 591
Table 1. Proportion of Correct Responses and Mean Response
Time (in Milliseconds) for Experiment 1
Color Word
AccuracyPure trialsM .97 .97SE .01 .01
Cue repetitionsM .92 .92SE .01 .01
Task repetitionsM .92 .93SE .01 .01
Task alternationsM .91 .93SE .02 .01
Response timePure trialsM 841 795SE 29 29
Cue repetitionsM 1152 1179SE 41 42
Task repetitionsM 1174 1201SE 43 45
Task alternationsM 1136 1122SE 50 41
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of the CSI and the effect of task switching reflected faster
response time for task alternations than for task repetitions. The
reason for the facilitation observed for task alternations is not
clear, but could be related to methodological factors that are
considered more thoroughly in the discussion.
ERP Data
Task mixing. The effects of task mixing on the ERPs are
portrayed in Figures 1 and 2 and were analyzed in a series of
ANOVAs including data for pure trials and cue repetitions.
These data reveal an enhancement of the P3 and parietal slow
wave for cue repetitions relative to pure trials that was significant
between 200 and 600 ms after cue onset (Table 2). During this
epoch the Trial � Electrode interactionwas also significant: 200–
400 ms, F(2,42)5 12.43, Z2p 5 .37, e5 .97; 400–600 ms,
F(2,42)5 9.06, Z2p 5 .30, e5 1.00. This interaction appeared to
result from the greater amplitude of the P3 and parietal slow
wave at the midline electrode relative to the lateral electrodes. To
test this suggestion a post hoc analysis that compared mean
voltage between 200 and 600 ms at electrode Pz to mean voltage
collapsed across electrodes P3 and P4 was performed. In this
analysis the Trial � Electrode interaction was significant,
F(1,21)5 17.16, Z2p 5 .45. The increase in the amplitude of the
P3 and parietal slow wave is consistent with evidence from prior
studies examining the neural correlates of task mixing (Kieffaber
& Hetrick, 2005; Kray et al., 2005; West, 2004) and probably
reflects the need to encode the task cues in the mixed blocks.
Cue retrieval. The effects of cue retrieval on the ERPs are
portrayed in Figures 2 and 3 and were analyzed in a series of
ANOVAs that included data for cue repetitions and task
repetitions. These data reveal an enhancement of the parietal
slow wave for task repetitions relative to cue repetitions between
400 and 800 ms after cue onset (Table 2). During this epoch the
Dimension � Trial � Electrode interactionwas significant (400–
600 ms, F[2,42]5 4.83, Z2p 5 .19, e5 .88) or marginally signifi-
cant (600–800 ms, F[2,42]5 3.67, p5 .06, Z2p 5 .15, e5 1.00).
Post hoc analyses examining the nature of this interaction
592 S. Travers and R. West
Color cue repetition
Color pure trial
Word cue repetition
Word puretrial
P3 Pz P4
+6µV
–3µV
–200 1000 ms
Figure 1. Grand-averaged ERPs for three parietal electrodes demonstrating the influence of taskmixing on the P3 and parietal slow
wave that is marked by the arrows. The tall bar reflects stimulus onset, the short bars on the x-axis reflect 200-ms increments and the
short bars on the y-axis reflect 2-mV increments.
Color Task
Word Task
+
–
Task Mixing Cue Retrieval Task Switching
Figure 2. Scalp topography maps demonstrating the distribution of the P3 associated with task mixing (cue repetitions minus pure
trials, at 400ms after cue onset), the parietal slowwave associatedwith cue retrieval (task repetitionsminus cue repetitions, at 600ms
after cue onset), and the parietal and frontal-polar slow waves associated with task set reconfiguration and rule mapping (task
alternations minus task repetitions, at 800 ms after cue onset) for the color and word tasks. Note that the amplitude varies across
maps (task mixing � 3.5 mV, cue retrieval � 1.25 mV, and task mixing � 2.5 mV).
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revealed that the amplitude of the parietal slow wave was greater
for word cues than for color cues at electrode P3 between 400 and
600 ms, F(1,21)5 14.09, Z2p 5 .40, and was not significant
between 600 and 800 ms, F(1,21)5 5.41, p5 .03, Z2p 5 .21,
following the Bonferroni correction. Additionally, the amplitude
of the parietal slow wave did not differ between dimensions at
electrodes Pz (400–600 ms, F[1,21]5 3.73, p5 .06, Z2p 5 .15;
600–800 ms, Fo1.00, Z2p 5 .01) and P4 (400–600 ms,
F[1,21]5 3.13, p5 .09, Z2p 5 .13; 600–800 ms F[1,21]5 3.43,
p5 .07, Z2p 5 .14) following the Bonferroni correction. The
results of these analyses indicate that cue retrieval was associated
with an enhancement of the parietal slow wave, with this effect
being modulated by task to a greater extent over the left than the
right parietal region.
Task switching. The effects of task switching on the ERPs are
portrayed in Figures 2 and 4. These data reveal two modulations
of the ERPs that were sensitive to the influence of task switching.
First, the amplitude of the parietal slowwave was greater for task
alternations than for task repetitions (Nicholson et al., 2006).
Second, there was a negative slow wave beginning at roughly
500 ms after onset of the task cue over the frontal-polar region
that was greater in amplitude for task alternations than for task
repetitions. The time course and topography of the frontal-polar
slow wave appears to be similar to a modulation reported by
Rushworth et al. (2005); however, it has not been well
characterized in previous studies using ERPs to examine the
neural correlates of task switching. The effects of task switching
on the ERPswere examined in a series of ANOVAs that included
data for task repetitions and task alternations. The amplitude of
the parietal slow wave was greater for task alternations than for
task repetitions between 400 and 1000 ms after stimulus onset
(Table 2). Additionally, during this interval the Dimension �Trial � Electrode interaction was significant (400-600 ms,
F[2,42]5 5.01, Z2p 5 .19, e5 1.00; 600–800 ms, F[2,42]5 11.98,
Z2p 5 .36, e5 1.00; 800–1000 ms, F[2,42]5 3.96, Z2p 5 .16,
e5 .87). This interaction reflected a decrease in the amplitude
of the parietal slow wave for color cues from the left to the right
hemisphere and little effect of region on the amplitude of the
parietal slow wave for word cues (Figure 5). This suggestion was
supported by the results of a post hoc analysis that included
electrodes P3 and P4 andmean amplitude between 400 and 1000
ms where the Dimension � Trial � Electrode interaction was
significant, F(1,21)5 12.70, Z2p 5 .38. Differences in the ampli-
tude of the parietal slow wave between the color and word tasks
reveal that this modulation of the ERPs may be associated with
processes underlying task set reconfiguration.
The frontal-polar slow wave was present between 600 and
1000 ms after cue onset (Figures 2 and 4; Table 2). As can be seen
from the inferential statistics presented in Table 2, the frontal-
polar slow wave appears to be more closely associated with
processes underlying task switching than with processes asso-
ciated with task mixing or cue retrieval (i.e., the effect of trial did
not approach significance in the analyses of task mixing or cue
retrieval). In contrast to the parietal slow wave, the analyses of
the frontal-polar slowwave did not reveal significant interactions
involving the variable dimension (all Fso1.00). This finding
leads to the suggestion that the amplitude of the frontal-polar
slow wave is similar for color and word cues and may indicate
that the frontal-polar slowwave reflects a neural correlate of rule
mapping rather than task set reconfiguration.
In summary, the electrophysiological data revealed modula-
tions of the ERPs that were differentially sensitive to processes
associated with task mixing, cue retrieval, task set configuration,
and rule mapping. Task mixing was associated with an
ERPs and task switching 593
Table 2. Inferential Statistics for the Main Effect of Trial in the
ERP Data for Experiment 1
200–400 ms 400–600 ms 600–800 ms 800–1000 ms
ParietalTask mixing
F 47.70 48.89 2.81 3.69Z2p .69 .70 .12 .15
Cue retrievalF o1.00 5.35 7.07 o1.00Z2p .001 .20 .25 .02
Task switchingF 1.39 6.31 32.49 24.64Z2p .06 .23 .61 .52
Frontal-polarTask mixing
F F F o1.00 o1.00Z2p F F .02 .03
Cue retrievalF F F o1.00 o1.00Z2p F F .01 .04
Task switchingF F F 29.76 22.06Z2p F F .59 .51
Color task repetition
Color cue repetition
Word task repetition
Word cue repetition
P3 Pz P4
+6µV
–4µV
–200 1000 ms
Figure 3. Grand-averaged ERPs for three parietal electrodes demonstrating the influence of cue retrieval on the parietal slow wave
that ismarked by the arrows. The tall bar reflects stimulus onset, the short bars on the x-axis reflect 200-ms increments, and the short
bars on the y-axis reflect 2-mV increments.
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enhancement of the parietal P3 and parietal slow wave for cue
repetitions relative to pure trials that would logically result from
the need to encode the task cues on cue repetitions (Kieffaber &
Hetrick, 2005; Kray et al., 2005). Cue retrieval and task
switching were both associated with enhancement of the parietal
slowwave beginning at roughly 400 ms after onset of the task cue
that was sensitive to task demands. There were, however,
differences in the time course and topography of these effects.
The effect of cue retrieval on the parietal slow wave was resolved
by 800 ms after cue onset whereas the effect of task switching
remained significant until at least 1000 ms after cue onset. Also,
the effect of cue retrieval was stronger for the word task than for
the color task over the left, but not right, parietal region. In
contrast, the effect of task switching decreased from the left to the
right parietal region for the color task and was similar across
the parietal region for the word task. The influence of task on the
effects of task switching for the parietal slow wave may indicate
that this modulation of the ERPs is sensitive to processes
underlying task set reconfiguration. Task switching was also
associated with a slow wave over the frontal-polar region that
appeared to be similar in amplitude for the color and word tasks
(Rushworth et al., 2005). This pattern of data leads to the
suggestion that the frontal-polar slow wave is more likely
associated with processes underlying rule mapping than with
processes underlying task set reconfiguration (Mayr & Kliegl,
2003). However, some degree of caution is required in accepting
this conclusion as it is predicated on the observation of a null
effect (i.e., the lack of a Dimension � Trial interaction).
EXPERIMENT 2
We had two goals in Experiment 2. First, we sought to replicate
the novel findings of Experiment 1 related to the neural correlates
594 S. Travers and R. West
Color task repetitions
Color task alternations
Word task repetitions
Word task alternations
+6µV
–4µV
–200 1000 ms
P4PzP3
Fp2FpzFp1
Figure 4. Grand-averaged ERPs for three parietal and three frontal-polar electrodes demonstrating the influence of task set
reconfiguration on the parietal slowwave and rulemapping on the frontal-polar slowwave that ismarked by the arrows. The tall bar
reflects stimulus onset, the short bars on the x-axis reflect 200-ms increments, and the short bars on the y-axis reflect 2-mVincrements.
600–800 ms
Mic
rovo
lts
800–1000 ms
0
0.5
1
1.5
2
2.5
3
0
0.5
1
1.5
2
2.5
3
Color Word
Color Word
Mic
rovo
lts
P3
Pz
P4
P3
Pz
P4
Figure 5. Mean difference in ERP amplitude between 600–800 ms and
800–1000 ms for task alternations versus task repetitions at the parietal
electrodes revealing the differential effect of task on the parietal slow
wave. The bars reflect 1 standard error.
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of task switching. Second, we sought to determine whether the
parietal and frontal-polar slow waves were modulated by a
variable that should influence processes underlying cue retrieval
and rulemapping. Specifically, we included both transparent and
nontransparent cues in the experiment. Based on ideas related to
mediator retrieval in task switching (Logan & Schneider, 2006),
we expected that cue retrieval would be more effortful for
nontransparent cues than for transparent cues because non-
transparent cues do not possess an a priori association with the
task that is to be performed (i.e., the association of ‘‘%%%%’’
to the word task is weaker than the association of ‘‘WORD’’ to
the word task). The more effortful retrieval for nontransparent
cues relative to transparent cues was expected to lead to an
increase in the amplitude or duration of the parietal slow wave
differentiating cue repetitions from task repetitions. Further, we
expected that rule mapping would only be required for
nontransparent cues, given the direct mapping between the
transparent task cues and the tasks, resulting in the frontal-polar
slow wave being limited to nontransparent task alternations.
Method
Participants
Twenty-two individuals (12 men and 10 women) ranging in age
from 19 to 22 years (M5 20.77) participated in this study for
course credit or for a stipend of $20. Eighteen of the participants
were right-handed and 4 were left-handed. None of the
individuals had participated in Experiment 1. All participants
provided informed consent and the Human Subjects Institu-
tional Review Board of the university approved the study. A high
degree of movement artifact resulted in the exclusion of 1
participant’s data from the analyses.
Materials and Procedure
Experiment 2 consisted of three phases (key acquisition, cue
practice, and experimental). The key acquisition and cue practice
phases were identical to Experiment 1 with the exception that
transparent (WORD or COLOR) and nontransparent
(%%%% or $$$$) cues were included in the cue practice phase.
The experimental phase was identical to Experiment 1 with the
following exception. Transparent and nontransparent cues were
presented in each block and a single type of cue (transparent or
nontransparent) was associated with cue repetitions, task
repetitions, or task alternations within a given block. For
instance, for half of the blocks transparent cues preceded the
word and color alternation trials, and for the other half of the
blocks nontransparent cues preceded these trials. The presenta-
tion of these blocks alternated throughout the experiment. This
approach was adopted as we found it impossible to obtain a
balanced set of trials within a single block that also controlled for
repetition priming. Following Experiment 1, there were equal
numbers of switch (task repetitions and task alternations) and
nonswitch (cue repetitions) trials, resulting in 210 cue repetitions
being excluded from the analyses. As a result of the balancing
constraints the number of trials included in the analyses ranged
from 48 to 55 trials per condition. There were two pure blocks
that were identical to Experiment 1 with the exception that both
transparent and nontranparent cues were presented. As the cues
are irrelevant for pure blocks, the data for pure trials were
collapsed across transparent and nontransparent cues.
Electrophysiological Recording and Analysis
All aspects of the EEG recording and artifact correction
procedures were identical to Experiment 1. ERPs were averaged
for correct responses for pure trials, cue repetitions, task
repetitions, and task alternations for transparent and nontran-
sparent cues for the color and word tasks (Table 3). The ERP
averages included 200 ms of activity before and 1000 ms of
activity after cue onset. Differences inmean voltage across condi-
tions were examined in four intervals (200–400 ms, 400–600 ms,
600–800 ms, 800–1000 ms) in ANOVAs that were identical
to those conducted in Experiment 1 with the exception that they
included the additional factor of cue type (transparent or
nontransparent). The analyses for the P3 and parietal slow wave
included data for electrodes P3, Pz, and P4, and the analyses for
the frontal-polar slow wave included data for electrodes Fp1,
Fpz, Fp2, Af3, and Af4. Other aspects of the analyses were
identical to Experiment 1.
Results
Behavioral Data
The proportion of correct responses and mean response time for
Experiment 2 are presented in Table 4. The influence of task
mixing was examined in ANOVAs that included data for pure
trials, transparent cue repetitions, and nontransparent cue
repetitions; the influence of cue retrieval in ANOVAs that
included data for cue repetitions and task repetitions; and the
influence of task switching in ANOVAs that included data for
task repetitions and task alternations.
For the response accuracy data, the analysis for task mixing
revealed a main effect of trial, F(2,40)5 160.74, Z2p 5 .88, with
accuracy being higher for pure trials than for mixed trials. The
analysis of cue retrieval revealed a main effect of trial,
F(1,20)5 16.77, Z2p 5 .46, with accuracy being slightly lower for
cue repetitions than for task repetitions. Two of the two-way
interactions were also significant (Cue � Trial, F[1,20]5 26.52,
Z2p 5 .57; Dimension � Trial, F[1,20]5 18.85, Z2p 5 .49). The Cue
� Trial interaction reflected lower accuracy for nontransparent
cues than for transparent cues for cue repetitions,
F(1,20)5 43.59, Z2p 5 .69, and little effect of cue type on task
repetitions, Fo1.00, Z2p 5 .02; the Dimension � Trial interaction
ERPs and task switching 595
Table 3. Mean Number of Trials Contributing to Averaged ERPs
for Experiment 2
Accuracy
Transparent Nontransparent
Color Word Color Word
Pure trialsM 70.30 65.05SD 13.37 23.67
Cue repetitionsM 31.52 34.05 41.24 37.29SD 5.51 7.63 8.51 7.22
Task repetitionsM 38.48 35.52 35.48 39.62SD 8.27 7.32 6.27 7.83
Task alternationsM 31.76 36.10 39.00 37.29SD 5.72 8.34 6.27 8.23
Note: Data for pure trials are collapsed across transparent andnontransparent cues.
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reflected lower accuracy for cue repetitions than for task
repetitions for word trials, F(1,20)5 90.49, Z2p 5 .82, and little
difference between these conditions for color trials, Fo1.00,
Z2p 5 .04. The analysis of task switching revealed a main effect of
cue, F(1,20)5 52.77, Z2p 5 .73, and a Cue � Trial interaction,
F(1,20)5 88.16, Z2p 5 .82. The interaction reflected an effect of
cue type for task alternations, F(1,20)5 195.79, Z2p 5 .91, and
little effect of cue type for task repetitions, Fo1.00, Z2p 5 .02.
For the response time data, the analysis of mixing costs
revealed a main effect of trial, F(2,40)5 59.76, Z2p 5 .75,
reflecting slower response time for cue repetitions than for pure
trials. For the analysis of cue retrieval the main effect of trial was
significant, F(1,20)5 6.70, Z2p 5 .25, with response time for cue
repetitions being 25 ms slower than response time for task
repetitions. For the analysis of task switching the Cue � Trial
interaction was significant, F(1,20)5 8.67, Z2p 5 .30, and re-
flected slower response times for transparent than nontranspar-
ent cues for task repetitions, F(1,20)5 14.53, Z2p 5 .42, and little
effect of cue type for task alternations, Fo1.00, Z2p 5 .001. The
Cue � Dimension interaction was also significant,
F(1,20)5 9.89, Z2p 5 .33, and reflected somewhat slower response
times for transparent cues than nontransparent cues for the color
dimension, F(1,20)5 3.83, Z2p 5 .16, and little effect of cue for the
word dimension, Fo1.00, Z2p 5 .001.
In summary, task mixing resulted in robust effects in the
response time and accuracy data that were in the expected
direction. In contrast, the influence of cue retrieval and task
switching on the behavioral data was more variable. The
response accuracy data revealed little effect of cue retrieval on
task performance and robust task switching costs for nontran-
sparent cues. The response time data revealed that responses for
task repetitions were generally faster than responses for cue
repetitions and that responses for task alternations were
generally faster than responses for task repetitions. The latter
finding is consistent with the results of Experiment 1, but is
counter to the common finding of slower response time for task
alternations than for task repetitions.
ERP Data
Task mixing. The effects of task mixing on the ERPs are
portrayed in Figure 6. Consistent with the results of Experiment
1 these data reveal an enhancement of the P3 and parietal slow
wave for cue repetitions relative to pure trials, with the
enhancement of the parietal slow wave appearing to last longer
for nontransparent cues than for transparent cues. The main
effect of trial was significant between 200 and 600 ms after cue
onset (Table 5). Consistent with the results of Experiment 1, the
Trial � Electrode interaction was significant between 200 and
400 ms, F(4,80)5 2.77, Z2p 5 .12, e5 1.00. This interaction
reflected the tendency for the amplitude of the P3 to be greater
at electrode Pz than at electrodes P3-P4, which was confirmed in
a post hoc test collapsing across electrodes P3-P4, Trial �Electrode F(2,40)5 9.69, Z2p 5 .33, e5 .98.
Cue retrieval. The effects of cue retrieval on the ERPs are
portrayed in Figure 7. The amplitude of the parietal slow wave
was greater for task repetitions than for cue repetitions between
400 and 800 ms (Table 5). For transparent cues the parietal slow
wave was greater for task repetitions than for cue repetitions
between 400 and 600 ms, although this difference was only
marginally significant, F(1,20)5 3.41, p5 .08, Z2p 5 .15, and the
slow wave was not present between 600 and 800 ms, Fo1.00,
Z2p 5 .03. For nontransparent cues the amplitude of the parietal
slowwavewas greater for task repetitions than for cue repetitions
in both intervals (400–600ms, F[1,20]5 20.33, Z2p 5 .50; 600–800
ms, F[1,20]5 15.38, Z2p 5 .44). In an analysis considering the
400–800-ms interval the Cue � Trial � Electrode interaction
was significant, F(2,40)5 6.79, Z2p 5 .25, e5 1.00. Post hoc
analyses of this interaction revealed no significant differences
across electrodes for transparent cues, F(2,40)5 1.38, Z2p 5 .07,
e5 .73, and greater amplitude for task repetitions than cue
repetitions for nontransparent cues that decreased from electrode
P3 to electrode P4 that was marginally significant,
F(2,40)5 3.78, p5 .03, Z2p 5 .16, e5 .99. The results of these
analyses indicate that the effect of cue retrieval on the ERPs may
be stronger for nontransparent cues than for transparent cues.
Task switching. The effects of task switching on the ERPs are
portrayed in Figure 8. As was the case in Experiment 1, task
switching modulated the amplitude of the parietal and frontal-
polar slow waves. The amplitude of the parietal slow wave was
greater for task alternations than for task repetitions between 600
and 1000 ms after cue onset (Table 5). In an analysis including
data for this interval the Cue � Dimension � Trial interaction
was significant, F(1,20)5 7.69, Z2p 5 .28. Separate post hoc
analyses for transparent and nontransparent cues were per-
formed to explore the nature of this interaction. For transparent
cues the main effect of trial, F(1,20)5 6.63, Z2p 5 .25, was
significant, and the Epoch � Trial interaction, F(1,20)5 5.42,
p5 .03 Z2p 5 .21, was marginally significant. The interaction
reflected significant differences between task alternations and
task repetitions from 600 to 800ms, F(1,20)5 9.15, Z2p 5 .31, and
nonsignificant differences from 800 to 1000 ms, F(1,20)5 3.64,
596 S. Travers and R. West
Table 4. Proportion of Correct Responses and Mean Response
Time (in Milliseconds) for Experiment 2
Transparent Nontransparent
Color Word Color Word
AccuracyPure trials
M .94 .96 .01 .01SE
Cue repetitionsM .89 .88 .85 .85SE .018 .009 .012 .011
Task repetitionsM .86 .90 .86 .92SE .016 .01 .017 .013
Task alternationsM .91 .93 .77 .83SE .012 .012 .015 .015
Response timePure trials
M 811 800SE 30 41
Cue repetitionsM 1030 1011 994 989SE 49 41 40 46
Task repetitionsM 1032 991 954 957SE 44 41 38 47
Task alternationsM 979 955 939 998SE 48 43 44 52
Note: Response accuracy and response time for pure trials are collapsedacross transparent and nontransparent cues.
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p5 .07, Z2p 5 .15. For nontransparent cues the main effect of
trial, F(1,20)5 5.05, p5 .04, Z2p 5 .20, and the Trial � Epoch
interaction, Fo1.00, Z2p 5 .04, were not significant, and the
Dimension � Trial interaction was significant, F(1,20)5 10.89,
Z2p 5 .35. This interaction reflected significant differences be-
tween task alternations and task repetitions for the color task,
F(1,20)5 11.85, Z2p 5 .37, but not the word task, Fo1.00,
Z2p 5 .006. The results of these analyses reveal that the effect of
task switching on the parietal slow wave was present for
transparent and nontransparent cues. For transparent cues this
effect appeared to be similar for the color andword tasks, and for
nontransparent cues this effect was stronger for the color task
than for the word task. The interaction between task and cue type
observed for the parietal slow wave differentiating task repeti-
tions from task alternations may indicate that processes under-
lying task set reconfiguration are more strongly recruited when
nontransparent cues are utilized.
The amplitude of the frontal-polar slow wave was greater for
task alternations than for task repetitions between 600 and 1000
ms after cue onset (Table 5; Figure 8). In this interval the Cue �Trial interaction was significant, F(1,20)5 8.87, Z2p 5 .31. Post
hoc analyses revealed significant differences between task
repetitions, M5 .41 mV, and task alternations, M5 � .87 mV,for nontransparent cues, F(1,20)5 8.21, Z2p 5 .29, and nonsigni-
ficant differences between task repetitions,M5 .25 mV, and task
alternations, M5 � .01 mV, for transparent cues, Fo1.00,
Z2p 5 .01. These data support the hypothesis that the frontal-
polar slowwavemay be associatedwith processes underlying rule
mapping.
In summary, the findings of Experiment 2 generally replicate
and extend those of the first experiment. The P3 differentiated
mixed trials from pure trials and was not sensitive to the type of
cue. These findings are consistent with the idea that the P3
reflects processes associated with encoding the cue. Replicating
the results of Experiment 1, the duration of the parietal slow
wave increased from cue repetitions to task repetitions to task
alternations. Additionally, the parietal slowwave was temporally
extended for nontransparent cues relative to transparent cues.
Both of these findings are consistent with the idea that the
parietal slow wave is sensitive to processes underlying cue
retrieval. Additionally, in the analyses examining the influence of
task switching on the parietal slow wave there was an interaction
between cue type and dimension. This finding leads to the
suggestion that the parietal slow wave is sensitive to processes
associated with task set reconfiguration when nontransparent
cues are used. The frontal-polar slowwave appeared to be limited
to nontransparent cues and to be insensitive to the to-be-
performed task as was the case in Experiment 1. This finding
ERPs and task switching 597
Color
Word
Pure trials
Transparent cue repetition
Nontransparent cue repetition
P3 Pz P4
P3 Pz P4
+6µV
–4µV
–200 1000 ms
Figure 6. Grand-averaged ERPs at three parietal electrodes demonstrating the influence of task mixing and cue type on the P3 and
parietal slow wave that is marked by the arrows. The tall bar reflects stimulus onset, the short bars on the x-axis reflect 200-ms
increments, and the short bars on the y-axis reflect 2-mV increments.
Table 5. Inferential Statistics for the Main Effect of Trial for the
Parietal Region of the Scalp for Experiment 2
200–400 ms 400–600 ms 600–800 ms 800–1000 ms
Task mixingF 17.76 10.06 1.11 2.22Z2p .47 .34 .05 .14
Cue retrievalF 2.57 54.75 8.95 o1.00Z2p .11 .73 .31 .001
Task switchingF o1.00 o1.00 7.45 6.28Z2p .006 .02 .27 .24
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supports the hypothesis that the frontal-polar slow wave may be
related to rule mapping.
General Discussion
The present experiments were designed to examine the functional
characteristics of modulations of the ERPs elicited during task
switching. Specifically, we were interested in whether different
modulations of the ERPs could be associated with distinct
cognitive processes (i.e., cue retrieval, task set reconfiguration,
and rule mapping) that are thought to support the ability to
flexibly switch between two tasks (Logan & Bundesen, 2003;
Mayr &Kliegl, 2003;Monsell &Mizon, 2006). The results of the
two experiments for the ERP data were largely consistent with
the findings of previous research. Task switching modulated the
amplitude of slow wave activity over the parietal and frontal-
polar regions of the scalp and had little effect on the amplitude of
the P3. The parietal slow wave was sensitive to the influence of
processes underlying cue retrieval and task set reconfiguration
whereas the frontal-polar slow wave appeared to be sensitive to
processes underlying rule mapping.
Consistent with the findings of previous research, the
response accuracy and response time data revealed robust task
mixing costs reflecting a decrease in response accuracy and
increase in response time from pure trials to cue repetitions. The
expression of task switching costs in the behavioral data across
the two experiments was less consistent with the findings of
previous research. In the response accuracy data there were no
switch costs in Experiment 1, whereas in Experiment 2 there was
a modest effect for nontransparent color task alternations. In the
response time data, task alternations tended to be faster than task
repetitions or cue repetitions, revealing a reversal of the standard
task switch costs. Also, in Experiment 1 task repetitions were
slower than cue repetitions, whereas in Experiment 2 this pattern
was reversed. The reason for the atypical patterns observed in the
response time data is unclear and may result from the confluence
of three or more factors. First, our CSI and response-to-cue
interval were relatively long when compared to those used in
many behavioral studies of task switching, and there is clear
evidence that switch costs are diminished as these intervals
increase (Logan & Bundesen, 2003; Monsell & Mizon, 2006).
Second, the use of Stroop stimuli in combination with the long
CSI may have contributed to this effect. Consistent with this
idea, Monsell and Mizon found that switch costs were not
significant at a 1000-ms CSI when a stimulus–response compat-
ibility task was used (Experiment 1) andWest and Travers (2007)
found that switch costs were not significant for either younger or
older adults in a study using Stroop stimuli and a 1500-ms CSI.
In contrast, robust switch costs have been observed with a 1000-
ms CSI when perceptual or conceptual judgments were required
(Monsell & Mizon, 2006). Third, the stimulus lists were
constructed so as to reduce the influence of repetition priming.
Controlling for priming effects may have served to inflate
response time for cue repetitions and task repetitions that are
likely to be influenced by repetition priming (Schneider & Logan,
2005) and had less of an effect on task alternations.
As in previous research the amplitude of the P3 was sensitive
to processes influencing task mixing, and the parietal slow wave
was sensitive to processes influencing task switching (Kieffaber &
Hetrick, 2005; Kray et al., 2005; West, 2004; West & Moore,
2005). Furthermore, differences between cue repetitions, task
598 S. Travers and R. West
Word
Color
P4PzP3
P4PzP3
+4µV
–4µV
–200 1000 ms
Transparent cue repetitionsNontransparent cue repetitionsTransparent task repetitionsNontransparent task repetitions
Figure 7. Grand-averaged ERPs at three parietal electrodes demonstrating the influence of cue retrieval and cue type on the parietal
slow wave that is marked by the arrows. The tall bar reflects stimulus onset, the short bars on the x-axis reflect 200-ms increments,
and the short bars on the y-axis reflect 2-mV increments.
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repetitions, and task alternations revealed that the parietal slow
wave was sensitive to processes influencing both cue retrieval and
task set reconfiguration. These findings provide an extension of
previous work examining differences in the ERPs elicited by task
repetitions and task alternations where the influences of cue
retrieval and task set reconfiguration were confounded (e.g.,
Kieffaber & Hetrick, 2005; West &Moore, 2005). Differences in
the amplitude and time course of the parietal slow wave between
cue repetitions and task repetitions could be seen as arising from
variation in the time required to retrieve cues from working
memory (cue repetitions) or long-termmemory (task repetitions)
(Logan & Bundesen, 2003). This idea would be consistent with
the finding that the P3 was greater in amplitude over the midline
than lateral parietal regions, whereas the parietal slow wave for
nontransparent task cues was greater in amplitude over the left
than right parietal region. These findings may reflect the
manifestation of a modulation that is similar to the parietal
old–new effect that is associated with retrieval from long-term
memory in recognition paradigms (Rugg, 2004). The difference
in the duration of the parietal slowwave between task repetitions
and task alternations that interacted with task most likely arises
from the need to reconfigure task set on task alternations
(Nicholson et al., 2006).
There were also differences in the time course and topography
of the parietal slow wave that distinguished task repetitions from
task alternations that were sensitive to the task that was to be
performed and the nature of the cue. These findings indicate that
the parietal slowwave is sensitive to processes influencing task set
reconfiguration and are interesting in light of previous research
where effects of task have not been observed (Kieffaber &
Hetrick, 2005; Nicholson et al., 2006). Differences between the
current and prior findings may be related to the greater
attentional demands that are inherent in the Stroop task relative
to the perceptual or categorical judgments that were required in
prior research (Kieffaber & Hetrick, 2005; Nicholson et al.,
2006). In Experiment 1, the amplitude of the parietal slow wave
decreased from the left to right parietal regions for the color task
and was similar in amplitude across the parietal region for the
word task. In Experiment 2, the amplitude of the parietal slow
wave was similar for the color and word tasks for transparent
cues and was significant for the color task but not the word tasks
for nontransparent cues. The reason for these differences in the
ERPs and task switching 599
Transparent
Nontransparent
Color task repetitions
Word task repetitions
Color task alternations
Word task alternations
P3 Pz P4
Fp2FpzFp1
P3 Pz P4
Fp2FpzFp1
+4µV
–4µV
–200 1000 ms
Figure 8. Grand-averaged ERPs for three parietal and frontal-polar electrodes demonstrating the influence of task set
reconfiguration, rule mapping, and cue type on the parietal and frontal-polar slow waves that is marked by the arrows. The tall
bar reflects stimulus onset, the short bars on the x-axis reflect 200-ms increments, and the short bars on the y-axis reflect 2-mVincrements.
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effects of tasks and cues on the parietal slow wave across the two
experiments is not readily apparent and may be related to the
reduction in the number of trials per condition that was required
to implement the manipulation of cue type in Experiment 2.
Given this, further work seems warranted in order to more fully
understand the relationship between the processes underlying
task set reconfiguration and the parietal slow wave.
The frontal-polar slow wave differentiated task alternations
from the other three types of trials, appeared to be insensitive to
the task that was to be performed, and also appeared to be
limited to nontransparent cues. This latter finding is consistent
with a between experiment comparison of the results of
prior studies. For instance, Rushworth et al. (2005) observed a
frontal slow wave in a task with nontransparent cues. In
contrast, Nicholson et al. (2006) did not report frontal slow
wave activity in a study where subjects were given substantial
practice with the task switching paradigm before collection of the
ERP data.
The presence of a frontal-polar slow wave that differentiates
task alternations from the other three trial types is consistentwith
behavioral evidence indicating that processes other than those
associated with cue retrieval underlie task switching when
nontransparent task cues are used (Logan & Bundesen, 2004;
Mayr &Kliegl, 2003). For instance, several studies have revealed
slower response time for task alternations than for task
repetitions when nontransparent task cues were incorporated in
the design (Logan & Bundesen, 2004; Mayr & Kliegl, 2003;
Monsell &Mizon, 2006; Nicholson et al., 2006). Two accounts of
this effect have been offered. Given evidence from a study using
nontransparent task cues, Mayr and Kliegl argued that the effect
could be related to task set reconfiguration. In contrast, Logan
and Bundesen suggested that the difference between task
alternations and task repetitions could arise from the need to
map an arbitrary (nontransparent) task cue to a given task set.
Two pieces of evidence support the latter account. First,
differences in response time between task alternations and task
repetitions appear to be greatest in instances where nontran-
sparent task cues are used; second, the differences between
transparent and nontransparent task cues are greatly reduced
and possibly eliminated with practice (i.e., once the association
between the nontransparent task cues and the tasks becomes well
established) (Logan & Bundesen, 2004). Experiment 2 of the
current study was designed to examine these two alternatives in
accounting for the frontal-polar slow wave elicited by task
alternations. The data from Experiment 2 revealed that the
frontal-polar slow wave appeared to be limited to nontranspar-
ent cues, supporting the hypothesis that this modulation of the
ERPs is associated with rule mapping rather than with task set
reconfiguration.
Conclusions
The data from two experiments reveal modulations of the ERPs
that were differentially sensitive to processes underlying cue
retrieval (parietal slow wave), task set reconfiguration (parietal
slow wave), and rule mapping (frontal-polar slow wave). The
amplitude of the parietal slow wave was greater over the left than
right hemisphere in the contrast of cue repetitions and task
repetitions, possibly reflecting a neural correlate of retrieval from
long-term memory somewhat similar to the parietal old-new
recognition effect. The contrast of task repetitions and task
alternations revealed that the amplitude of the parietal slowwave
differed between the color andword tasks, revealing the influence
of processes associated with task set configuration. Together the
data from these experiments indicate that dissociable pro-
cesses associated with cue retrieval, task set reconfiguration,
and rulemapping underlie our ability to dynamically switch from
one task to another (Mayr & Kliegl, 2003; Monsell & Mizon,
2006).
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