Download - Neural correlates of cue retrieval, task set reconfiguration, and rule mapping in the explicit cue task switching paradigm

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

588

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

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

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


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

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


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).

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


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.

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


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.

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


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.

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,


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.

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


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

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


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.

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


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.

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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(Received December 15, 2006; Accepted November 19, 2007)
