Cerebral Cortex November 2009;19:2508--2521
Advance Access publication March 25, 2009
Priming and Backward Influences in the
Human Brain: Processing Interactions
during the Stroop Interference Effect
L. G. Appelbaum1, K. L. Meyerhoff1,2and M. G. Woldorff1,3
1Center for Cognitive Neuroscience, Duke University, Durham,
NC 27708,2School of Medicine, University of North Carolina,
Chapel Hill, NC 27514 and3Department of Psychiatry, Duke
University, Durham, NC 27708
This study investigated neural processing interactions during
Stroop interference by varying the temporal separation of relevant
and irrelevant features of congruent, neutral, and incongruent
colored-bar/color-word stimulus components. High-density event-
related potentials (ERPs) and behavioral performance were
measured as participants reported the bar color as quickly as
possible, while ignoring the color words. The task-irrelevant color
words could appear at 1 of 5 stimulus onset asynchronies (SOAs)
relative to the task-relevant bar-color occurrence: 2200 or 2100
ms before, 1100 or 1200 ms after, or simultaneously. Incongruent
relative to congruent presentations elicited slower reaction times
and higher error rates (with neutral in between), and ERP difference
waves containing both an early, negative-polarity, central-parietal
deflection, and a later, more left-sided, positive-polarity component.
These congruency-related differences interacted with SOA, show-
ing the greatest behavioral and electrophysiological effects when
irrelevant stimulus information preceded the task-relevant target
and reduced effects when the irrelevant information followed the
relevant target. We interpret these data as reflecting 2 separate
processes: 1) a ‘priming influence’ that enhances the magnitude of
conflict-related facilitation and conflict-related interference when
a task-relevant target is preceded by an irrelevant distractor; and 2)
a reduced ‘backward influence’ of stimulus conflict when the
irrelevant distractor information follows the task-relevant target.
Keywords: conflict processing, event-related potentials (ERPs),
incongruency, stimulus onset asynchrony (SOA), Stroop task
Models of forced-choice decision making rely heavily on the
notion that the brain accumulates information for one stimulus
versus others over some period of time, with the resulting choice
being determined by the relative weight of this information at
a decision stage (Gold and Shadlen 2000; Schall 2001; Platt
2002; Ratcliff et al. 2003; Reddi et al. 2003; Ratcliff and Smith
2004). Computational and neural models of information
processing assume that this accumulation is driven by both
systematic and random influences that alter the speed and
strength of representations in the brain, thereby determining
the relative strength of each choice when the response system
The classic Stroop interference task (Stroop 1935) has
provided a fruitful platform by which to test models of forced-
choice decision and response selection under situations where
compatible or incompatible components of the stimulus facil-
itate or impair task performance. In the typical Stroop task,
participants are instructed to report the physical color of
a written color word (e.g., ‘‘RED’’), while ignoring the semantic
meaning of the word. In cases where the physical color of the
presentation is congruent with the semantic meaning of the
word, participants are both faster and more accurate at
reporting the physical color. However, when the physical
color differs from the semantic meaning of the word (i.e., is
incongruent) participants are slower and more prone to error
(see MacLeod 1991 for a review).
Numerous theoretical accounts of Stroop interference have
been proposed over the more than 70-year history of this
phenomenon. Although early speed-of-processing (‘‘horse
race’’) models interpreted Stroop effects as resulting from the
faster, more ‘‘automatic’’ processing of word information (Dyer
1973; Posner and Snyder 1975; Dunbar and MacLeod 1984),
more recent theoretical and computational explanations of
Stroop-related interference have tended to model the effects as
arising from response competition occurring in a parallel and
hierarchical network (Cohen et al. 1990; Cohen et al. 1992;
Phaf et al. 1990; Stafford and Gurney 2007). Under such
‘connectionist’ frameworks, processing is determined by
activity spreading throughout pathways of differing strengths,
with the response decision ultimately occurring when the
output of these pathways crosses a certain threshold (Rumelhart
et al. 1986). According to these views, interference occurs
when 2 simultaneously activated pathways produce conflicting
activity at their processing intersection, whereas facilitation
occurs when the 2 paths produce compatible activation. The
intersection of conflicting activity can occur at any phase in the
processing hierarchy (e.g., semantic evaluation or response
selection) following sensory processing, where the pathways
rely upon a common set of processing resources, a notion that
has been called the ‘‘multiple-resource’’ view (Allport 1982;
Hirst and Kalmar 1987; Cohen et al. 1990).
One key piece of evidence that has argued against a simple
speed-of-processing account came from behavioral experi-
ments in which the color and word components of the Stroop
stimulus were presented with varying stimulus onset asyn-
chronies (SOAs) (Dyer 1971; Glaser and Glaser 1982; Glaser
and Dungelhoff 1984; Glaser and Glaser 1989; Sugg and
McDonald 1994). In these experiments, the task-relevant
stimulus component could be preceded or followed by
presentation of the task-irrelevant component with SOAs
typically ranging from –400 to +400 ms. If interference in the
Stroop task was due to word meaning being processed faster
than the physical color, then presenting the color information
earlier should give its processing a sufficient head start to
eliminate interference from the word-meaning information.
Similarly, if the participant’s task was to report the word name,
and the physical-color information was presented early enough,
it should be possible to elicit a robust ‘‘reverse Stroop’’ effect in
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which the processing of the color information would tempo-
rally coincide with the processing of the word, therefore
creating interference in the naming of the word. Neither of
these types of results are typically observed, however
(MacLeod 1991; MacLeod and MacDonald 2000). Thus,
although pre-exposure to a task-irrelevant color component
did not have an effect on naming the word, pre-exposure of the
task-irrelevant word did have a substantial effect on naming the
physical color. Moreover, such interference was observed even
if the word was presented up to 100 ms after the physical
color. These SOA manipulations, and resultant data patterns,
have called into question the idea that interference arises
strictly because words are processed faster than color,
suggesting rather that interference is due to interactions that
alter the strength of activation patterns in a distributed and
Temporal Relationships in the Stroop SOA Task—Priming
and Backward Influences
As illustrated by the Stroop SOA manipulations, successful goal-
oriented behavior involves the filtering of task-irrelevant
information, especially when it is conflicting or distracting in
some way. It is also well appreciated, however, that the temporal
relationship between the components of visual stimuli greatly
influences the processing and perception of those stimuli.
Priming reflects one such category of stimulus--stimulus
temporal interactions in which processing of a target stimulus
is altered when it is preceded by a meaningfully related ‘‘prime’’
stimulus. These automatic (or implicit) effects can occur either
on the basis of perceptual features of the stimulus, such as
color (Marcel 1983) or motion (Jiang et al. 2002), or on the
basis of semantic aspects of the stimuli (reviewed in Neely
(1991), even in the absence of conscious awareness (Marcel
1983). Although priming is most typically associated with
enhanced processing of a stimulus due to the occurrence of
a previous stimulus, it has also been shown that there are types
of priming that can exert negative, inhibitory influences
In contrast, when a target is followed in time by the
subsequent presentation of an irrelevant distractor, backward
influences may occur (reviewed in Enns and Di Lollo 2000).
Although these influences can also in theory act to facilitate or
inhibit target processing, they are most commonly demonstrated
as the relative reduction in perceptibility of a target when
information is lost because of interference by a subsequently
presented stimulus. Such ‘backward masking’ is generally
believed to be a precategorical process that depends entirely
on the sensory aspects of the 2 inputs and not on lexical or
semantic factors. Because Stroop SOA variants, such as the one
used in the present study, reflect processing interactions that
may be either facilitory or inhibitory in nature, we refer more
generally to instances in which the irrelevant stimulus compo-
nent is presented prior to the relevant target as ‘‘priming
influences’’ and instances when the irrelevant stimulus compo-
nent comes after the target as ‘‘backward influences.’’
ERPs as a Measure of Stimulus Conflict and Semantic
Event-related potentials (ERPs) provide a measure of brain
dynamics with high temporal resolution, allowing researchers to
characterize the cascade of processes that behavioral measures
such as reaction time cannot offer. ERPs therefore constitute
a quantitative measure optimally suited for delineating the
nature of cognitive interference effects, such as those elicited
by the Stroop task.
Previous applications of Stroop-related ERPs have described 2
principle interference-related response components (Rebai et al.
1997; West and Alain 1999; Liotti et al. 2000; Atkinson et al. 2003;
Hesse et al. 2003; West 2003; Markela-Lerenc et al. 2004; West
et al. 2005; Hanslmayr et al. 2008). The first is a central-medial
component extending from roughly 350- to 500-ms poststimulus
that is more negative for incongruent relative to congruent trials.
This component has generally been viewed as reflecting the
detection and/or resolution of response conflict and is believed
to arise, at least partially, from generators in the anterior
cingulate cortex (ACC). A second ERP response component,
observed between 500 and 900 ms, is more positive for
incongruent relative to congruent trials. This late positive
complex (LPC) has tended to be maximal over the left parietal
cortex and has been related to the processing of semantic
meaning of words (West and Alain 1999; Liotti et al. 2000).
Taken together,these findings,alongwith thelackofcongruency
effects on sensory ERP components (Duncan-Johnson and Kopell
1981; Ilan and Polich 1999; Rosenfeld and Skogsberg 2006) have
suggested that Stroop interference does not influence sensory
processing, but rather occurs later at stages of response selection
(Hanslmayr et al. 2008).
Stroop-like and priming influences share similarities in that
both relate to biasing in perceptual systems; therefore, they
have sometimes been described in similar cognitive and
mechanistic terms (MacLeod 1991; MacLeod and MacDonald
2000). For example, the N400 ERP, a broad negative ERP wave
over central-parietal scalp locations, has been shown to be
sensitive to semantic priming effects and accordingly has been
often used as a marker of semantic processing (Kutas and
Hillyard 1980; Kutas and Federmeier 2000). This component is
larger for words that are semantically incongruent versus
semantically congruent with a preceding priming word or
sentence. Because the N400 depends substantially on the
temporal separation of the prime and the target (Kiefer and
Spitzer 2000; Kiefer and Brendel 2006), it is thought to reflect
effects on the processing of the target word resulting from the
preactivation of semantic representations of words associated
with the prime. Although functional similarities between the
semantic N400 component and the Stroop-evoked negativity
have been noted, it is thought that the Stroop response reflects
interference interactions amongst more general central-
executive control processes rather than more specifically
semantic incongruency effects (West 2003; West et al. 2004;
Hanslmayr et al. 2008). Nonetheless, the observation that the
N400 is sensitive to the temporal relationship between stimulus
components suggests the utility of similar SOAmanipulations on
the Stroop interference ERP effect.
The goal of the present study was to investigate the temporal
sensitivity of brain processes that detect and resolve stimulus
conflict using modified versions of the classic Stroop paradigm.
In separate experimental sessions, reaction times and error
rates were collected with and without concurrently recorded
ERPs as subjects reported the physical color of the stimulus. In
these tasks, stimuli were presented with 5 levels of SOA, in
which the relative timing of the physical-color and color-word
Cerebral Cortex November 2009, V 19 N 11 2509
components of the stimuli were varied from trial-to-trial. This
approach of presenting the task-relevant stimulus component
first (‘‘relevant-first’’) or the task-irrelevant component first
(‘‘irrelevant-first’’) allowed us to examine the influence of pre-
and postexposure of congruent versus incongruent informa-
tion on both behavior and brain activity.
In our main experimental session we assess the behavioral and
neural responses elicited by stimulus incongruency by consider-
ing the ERP difference waves produced by subtracting congruent
from incongruent trials, and we then relate these ‘‘incongruency
difference waves’’ at the different SOAs to behavioral perfor-
mance on this task. We explicitly focus our ERP analyses here on
the incongruency difference waves, because the SOA manipula-
of overlap in the ERP record depending on the temporal
separation between stimulus components (Woldorff 1993). As
this overlap is equivalent for the congruent and incongruent
stimuli within each SOA condition, the difference wave isolates
SOA and the neural processing related to the conflict processing
interactions. In an additional behavioral control study, we
evaluate the role of both facilitation and inhibition by comparing
reaction times and error rates for compatible and incompatible
In theory, these SOA manipulations could have resulted in
several outcomes relating to behavioral performance and/or the
amplitude or latency of the Stroop ERP effects. For example,
based on the common observation that mainly the amplitude,
and not the latency, of the language-related N400 component is
modulated by the strength of the prime-target semantic
relationship (Kutas and Federmeier 2000), our SOA manipula-
tion might only manifest as amplitude changes in the ERP
incongruency effects. Alternatively, the pretarget stimulus may
serve to alter the temporal characteristics of the processing of
the upcoming target, in which case the response latency of the
ERP incongruency effects may also be influenced. Nonetheless,
in line with the priming and backwards influences discussed
above, we would expect that pretarget exposure of the irrel-
evant stimulus is likely to result in the largest and earliest
incongruency effects in relation to simultaneous presentation,
and that the effects of post-target exposure to the irrelevant
stimulus is likely to be relatively diminished and delayed.
Forty young adults with normal or corrected-to-normal visual acuity
participated in these experiments. Twenty-five participants (19--37
years, 12 females) served as subjects in the ‘‘Main Experiment’’ and 15
participants (18--35 years, 7 females) served as subjects in the additional
‘Behavioral Control’ task carried out in separate sessions. Four
participants participated in both experimental sessions. All participants
were screened for colorblindness, and informed consent was obtained
prior to experimentation under a protocol approved by the Duke
University Institutional Review Board. Participants were instructed on
the task and given practice experimental runs prior to the start of the
experiment. All participants were paid $10/h for their participation.
Separate experimental sessions were conducted in which subjects
performed modified versions of the classic Stroop paradigm (see
Supplementary Materials for stimulus movies). In the main experimen-
tal session, reaction times and error rates were monitored as whole-
head 64-channel electroencephalography (EEG) was recorded. In the
separate, additional, behavioral control session, reaction times and error
rates were monitored as participants viewed an extended set of
stimulus conditions that included a neutral distractor condition, but
with no EEG recorded.
In both experimental variants of the task, the physical ‘‘bar-color’’ and
semantic ‘‘color-word’’ components of the stimulus were presented
with 5 levels of temporal asynchrony. As depicted in Figure 1, the bar
color (always presented at time 0) could co-occur with a simultaneously
presented color-word (no-delay), or be either preceded or followed by
the presentation of the color-word, by either 100 or 200 ms. In all cases
the participants’ task was to report the color of the bar as quickly as
possible by pressing 1 of 4 keys on the keyboard corresponding to the 4
possible colors, while ignoring the task-irrelevant color-word. We
reference each SOA condition to the no-delay (0 ms) condition, and
therefore refer to those trials in which the color-word component
came first as the ‘‘irrelevant-first’’ (–200 irrelevant-first and –100
irrelevant-first) conditions, and those trials in which the colored bar
appeared first as the ‘‘relevant-first’’ (+100 relevant-first and +200
relevant-first) conditions. For short hand, these SOA conditions may be
referred to by their relative timing; –200, –100, 0, +100, +200, or more
generally as being negative and positive SOAs.
In the main experimental session, the colored bars were red, green,
blue, or yellow rectangular patches, whereas the color words were the
text strings ‘‘RED,’’ ‘‘GREEN,’’ ‘‘BLUE,’’ or ‘‘YELLOW,’’ written in white
font with black borders. Red and green responses were mapped to the
‘‘D’’ and ‘‘F’’ keys on the left hand, and blue and yellow were mapped to
the ‘‘J’’ and ‘‘K’’ keys on the right hand. Stimuli were presented on a gray
screen (luminance value: 40 cd/m2) with a white fixation cross at the
center. Colored bars subtended 5? 3 16? of visual angle and were
presented 3.75? below fixation. Participants were positioned 60 cm
away from the computer screen.
In this task variant, only congruent and incongruent trials were
presented and these occurred in equal numbers for all the SOA delays
(Fig. 1B). On half the trials, the color-bar and color-word combinations
matched (congruent, e.g., red--red), whereas the other half of the trials
were split evenly between the 3 possible noncorresponding mappings
(incongruent, e.g., red--yellow, red--green, and red--blue). On every trial,
the bar and the word remained on the screen together for 1000 ms
after the onset of the later stimulus component. Each run consisted of
48 trials randomized across conditions and word/color combinations,
with equal numbers of trials occurring for each SOA condition. A run
lasted approximately 3 min.
The behavioral control variant of this task was identical in form to the
main experiment described above, with the addition of 3 types of
neutral stimulus trials. On these trials ‘‘PINK,’’ ‘‘ORANGE,’’ or ‘‘BROWN’’
text strings could appear at any of the SOA conditions. In that pink,
orange, and brown were not mapped to any of the target responses,
they therefore served as neutral, task-irrelevant controls. Congruent,
neutral, and incongruent trials were presented in equal numbers (33%
each), and subjects were again instructed to response as quickly
possible by pressing 1 of 4 keys on the keyboard corresponding to the 4
possible bar colors, while ignoring the task-irrelevant color words.
For both tasks, participants were instructed to maintain central
fixation and encouraged to minimize eye blinks during the experimen-
tal run. Before recording began, participants were given 1 or 2 training
runs, each consisting of 48 trials, in order to facilitate their learning of
the mapping of the 4 color response buttons. Data from twenty runs
were collected for each participant in the main experiment, and from
24 runs in the behavioral control session. Participants were given the
opportunity to rest between runs.
Data Acquisition and Analysis
Behavioral responses were monitored and recorded as participants
performed the color-discrimination task and were later analyzed for
significant differences. Trials were counted as correct if the subject’s
response occurred 100--1000 ms following the bar presentation and
Processing Interactions during the Stroop Task
Appelbaum et al.
corresponded correctly to the physical bar color. In that no systematic
differences were observed for responses to the different target colors,
data were collapsed over the corresponding color-bar/word combina-
tions to arrive at within-participant mean response times (RTs) and
error rates for all condition categories: congruent, neutral, and
incongruent instances of the 5 SOA conditions (no-delay, –100 ms
irrelevant-first, –200 ms irrelevant-first, +100 ms relevant-first, and +200
ms relevant-first). RTs (excluding erroneous responses) and error rate
means for these categories were then computed along with the
standard error. t-tests were performed on the congruent versus
incongruent RTs and error rates, separately at each SOA, to establish
the presence of significant behavioral congruency effects. SOA by
congruency, 2-way analysis of variance (ANOVA) were performed on
the RTs and error rates to determine significant main effects and
interactions of experimental conditions on behavioral performance for
the main experiment (5 3 2) and behavioral control (5 3 3) sessions.
Post hoc single factor ANOVAs were also performed over SOA for the
individual condition types in each session. In addition, separate 3 by 2
ANOVAs were performed on the irrelevant-first (–200, –100, and 0) and
relevant-first (0, +100, and +200) conditions, to establish the presence
of independent pre-exposure and postexposure congruency effects on
behavioral performance collected during the EEG sessions. The
significance threshold for the behavioral analyses was set to a P value
of 0.05 and reported using the Greenhouse-Geisser correction for
sphericity. The Bonferroni correction was also applied to post hoc
EEG Recording and Analysis
The EEG was recorded continuously from 64 channels mounted in a
customized elastic cap (Electro-Cap International, https://www.electro-
cap.com) using a bandpass filter of 0.01--100 Hz, gain of 1000, and
sampling rate of 500 Hz (SynAmps, Neuroscan, Charlotte, NC). All
channels were referenced to the right mastoid during recording. The
positions of all 64 channels were equally spaced across the customized
cap and covered the whole head from slightly above the eyebrows to
below the inion posteriorly (Woldorff et al. 2002). Impedances of all
channels were maintained to be below 5 kX, and fixation and eye
movements were monitored with both electro-oculogram recordings
and a zoom-lens camera. Recordings took place in an electrically
shielded, sound-attenuated, dimly lit, experimental chamber.
For each participant, ERPs to the onset of the bar color were
selectively averaged for each condition and SOA. ERP processing
included the re-referencing of all channels to the algebraic mean of the
2 mastoid electrodes and application of a digital, noncausal, 9-point
running-average filter. This filter greatly reduces frequencies of 56 Hz
and above at our sampling frequency of 500 Hz. Artifact rejection was
performed off-line before averaging by using a computer algorithm that
discarded epochs of the EEG that exceeded a prespecified threshold in
the window from –200 to 900 ms around the presentation of a bar-color
stimulus. The artifact rejection thresholds were set individually for each
subject, resulting in an average of ~15% of trials being rejected. Five
experimental participants were excluded from the analysis due to
either electrical noise problems (N = 2) or high trial-rejection rates
caused by eye blinks (N = 3).
Separate ERPs were computed for correctly reported congruent and
incongruent presentations for each of the 5 SOA conditions (–200,
–100, 0, +100, +200) by time-locking to the onset of the bar stimulus.
Because no differences were observed in the ERP responses for the
different target colors, responses were collapsed over all corresponding
color-bar/word combinations to arrive at 10 (5 SOAs 3 2 congruency)
evoked response types. To isolate brain potentials related to the Stroop
interference effect, difference waves were computed separately for
each SOA by subtracting the ERPs for congruent trials from the ERPs for
incongruent trials. Because we were interested primarily in the
relatively slow activity associated with the cognitive resolution of
Stroop interference, we applied an additional 51-point running-average
Figure 1. (A) Schematic illustration of the experimental design for a congruent (red--red) Stroop stimulus presented at each of the 5 SOAs. Each temporal separation (?200,
?100, 0, þ100, and þ200 ms) is shown in a separate row with vertical dotted lines indicating times at which stimuli components were presented. Once both stimulus
components were presented, they remained on the screen for an additional 1000 ms for all SOA conditions. The participant’s task was always to report the color of the bar, which
is defined as 0 ms in this schematic. (B) Trials proportions and exemplar stimuli for the main experiment and behavioral control variants of the task. See the Supplementary
Materials for movies of the stimuli used in the 2 tasks.
Cerebral Cortex November 2009, V 19 N 11 2511
filter to attenuate high-frequency activity occurring at, or above, 10 Hz.
Spherical-spline--interpolated topographic voltage maps of the 20
subject grand-averaged ERP differences were derived for a series of
consecutive 50-ms windows spanning from 100- to 900-ms post-color-
bar to visualize how the scalp distribution changed over time.
To test for significant differences between the congruent and
incongruent waveforms within SOA conditions, 2-way repeated-
measures ANOVAs were performed using a set of left- and right-sided
regions of interest, each consisting of 2 posterior-parietal channels
roughly corresponding to the peak of the incongruency-effect
distribution (these channels are indicated in orange in the bottom
panel of Fig. 3). For each SOA condition, 2-way ANOVAs with factors
Trial Type (congruent vs. incongruent) and Laterality (left vs. right)
were computed in successive 20-ms windows, with 10-ms overlap,
spanning from the onset of the second stimulus component to 900 ms
after the onset of the relevant target. Each time window was compared
with the prestimulus baseline, defined as the 200 ms preceding the
presentation of the initial stimulus component for each SOA. Latency
ranges with greater than 3 consecutive windows exceeding the P <
0.05 level were determined to be significant, and 2-way interactions
between hemisphere and trial type were only considered over those
latency ranges that showed a main effect of trial type.
In order to statistically assess the pattern of ERP latency and
amplitude effects between SOA conditions, we submitted the
individual subjects’ peak-latency and peak-amplitude values to re-
peated-measures ANOVAs. For each participant, and at each SOA, the
peak-latency and peak-amplitude within the significant latency
ranges defined by the within-SOA analyses were extracted from
the incongruency difference waves and averaged across the 4
channels of interest. The means of these individual subject peak-
latency and peak-amplitude measures were then submitted to a
within-subject, 1-factor ANOVA with SOA (–200, –100, 0, 100, 200) as
the single factor.
Robust and statistically significant behavioral effects of stimulus
compatibility were observed in both the main experiment and
in the behavioral control variants of these tasks. For both task
variants, RTs were faster and error rates lower for congruent
trials than for incongruent trials. Mean reaction times and error
rates for the 2 sessions are shown graphically in Figure 2 and
presented along with paired t-test results in Table 1.
Analysis of the behavioral data collected during the main
experimental session indicated that RTs for congruent trials
were faster than for incongruent trials for each of the SOA
conditions. Error rates for congruent trials were also lower
than for incongruent trials for all SOAs, with the exception of
the +200 SOA conditions, which did not reach significance at
the P < 0.05 level. For general statistical evaluation of these
data, 2 3 5 (congruency by SOA) repeated-measures ANOVAs
were performed separately on the RT and percent-error data.
The ANOVA for reaction times demonstrated a significant main
effect of congruency (F1,19= 204.9, P < 0.001) and of SOA
(F4,76= 46.2, P < 0.001), and a significant congruency by SOA
interaction (F4,76= 16.8, P < 0.001). For the error rates, the 2-
way ANOVA showed only a significant main effect of con-
gruency (F1,19= 16.0, P = 0.001). To further probe the driving
influences in the congruency by SOA interaction, 1-way
Figure 2. Behavioral performance for data collected during the main experiment (A) and the behavioral control experiment (B) are shown as a function of SOA. Data in the top
panels show reaction times for Incongruent (red), Neutral (green), and Congruent (blue) trials. Congruency differences are shown as gray bars for the Incongruent minus
Congruent reaction times in the main experiment, and separated into RT Facilitation (white: Congruent minus Neutral) and Interference (black: Incongruent minus Neutral) in the
behavioral control experiment. Mean error rates are shown in the bottom panels for each condition using the same color convention as in above.
Processing Interactions during the Stroop Task
Appelbaum et al.
ANOVAs were performed on the reaction time data separately
for the congruent and the incongruent trials. Between-
condition comparisons revealed a main effect of SOA for the
congruent (F4,95= 4.31, P = 0.003), but not incongruent (F4,95=
0.530, P = 0.714) trials. Subsequent planned comparisons of the
congruent SOA conditions revealed only differences between
the –200 SOA and the +100 and +200 SOA conditions.
Two, 2 3 3 ANOVAs done separately on the RTs for pre-
exposure (–200, –100, 0) and postexposure (0, 100, 200)
SOAs each showed main effects of congruency (pre-exposure:
[F1,19 = 69.5, P < 0.001]; postexposure: [F1,19 = 285.8, P <
0.001]), SOA (pre-exposure: [F2,38 = 7.13, P = 0.002]; post-
exposure: [F2,38= 45.3, P < 0.001]) and SOA by congruency
interactions (pre-exposure: [F2,38 = 9.8, P
exposure: [F2,38= 12.3., P < 0.001]) on RT, supporting the view
that pre-exposure and postexposure can each separately
produce interference effects that vary as a function of the
distractor-target relative timing.
< 0.001]; post-
Behavioral Control Experiment
As shown in Figure 2B for responses collected during the
behavioral control session, reaction times were fastest for
congruent, intermediate for neutral, and slowest for incongru-
ent trials. Statistical evaluation of the reaction times and
performance errors was done by way of separate 3 3 5
(congruency by SOA) repeated-measures ANOVAs. As observed
in the main experiment, a significant main effects of con-
gruency (F2,28= 50.26, P < 0.001), of SOA (F4,56= 78.4, P <
0.001), and a congruency by SOA interaction (F8,112= 13.15, P <
0.001) were all present. Separate 1-way ANOVAs, performed on
the reaction time data, demonstrate a main effect of SOA for
the congruent (F4,70= 4.69, P = 0.002) and neutral (F4,70= 2.56,
P = 0.046) trials, but not for the incongruent (F4,70= 0.44, P =
0.78) trials. Subsequent planned comparisons of the congruent,
neutral, and incongruent trial types revealed significant differ-
ences between the –200 SOA and the +100 and +200 SOA
conditions for congruent trials, and between the –200 and +200
SOA conditions for the neutral trials. Repeated-measures
ANOVA computed on the performance errors showed a signif-
icant main effect of congruency (F2,28= 5.98, P = 0.007) and
SOA by congruency interaction (F8,112 = 2.76, P = 0.008),
though the main effect of SOA (F4,56= 1.59, P = 0.19) did not
reach statistical significance. See Table 1 for specific within-
SOA contrasts of congruent, neutral, and incongruent RTs and
As done with the main experiment, separate ANOVAs were
also performed on the RTs for pre-exposure (–200, –100, 0) and
postexposure (0, 100, 200) SOAs. Each showed main effects of
congruency, SOA, and an SOA by congruency interaction, again
supporting the view that pre-exposure and postexposure can
each separately produce interference effects that vary as
a function of the distractor-target relative timing.
Collectively, data from these 2 tasks emphasize the relation-
ship between the temporal separation of the Stroop compo-
nents and the stimulus congruency. Specifically, we observed
that, for both tasks, pre-exposure of a task-irrelevant color-
word (negative SOAs) enhances the magnitude of the
behavioral incongruency effect on the subsequent target
relative to when they were presented simultaneously. Post-
target exposure of an irrelevant distractor, on the other hand,
reduced the overall magnitude of this effect relative to the no-
delay condition, while still producing statistically significant
interference. Importantly, data from the behavioral control task
demonstrate a main effect of SOA on the RTs of the neutral
trials, strongly suggesting that pre-exposure of the distractor
stimulus influences performance irrespective of its compatibil-
ity with the upcoming target.
ERPs for the No-Delay Condition
Grand average (left) and difference wave (right) ERPs for the
no-delay condition are shown in Figure 3 for 4 mid-line
channels, FCz, Cz, CPz, and Pz. As observed in previous studies
Summary of behavioral performance data
SOART differencetSignificanceError ratetSignificance
Main experiment (incongruent minus congruent):
Behavioral control (incongruent minus neutral):
Behavioral control (neutral minus congruent):
Behavioral control (incongruent minus congruent):
t(19) 5 ?12.47
t(19) 5 ?10.83
t(19) 5 ?7.82
t(19) 5 ?10.25
t(19) 5 ?3.17
P \ 0.001
P \ 0.001
P \ 0.001
P \ 0.001
P 5 0.002
t(19) 5 3.33
t(19) 5 2.62
t(19) 5 1.95
t(19) 5 2.23
t(19) 5 0.9
P 5 0.001
P 5 0.008
P 5 0.035
P 5 0.017
P 5 0.19
t(14) 5 ?7.37
t(14) 5 ?4.55
t(14) 5 ?4.44
t(14) 5 ?1.86
t(14) 5 ?0.7
P \ 0.001
P \ 0.001
P \ 0.001
P 5 0.08
P 5 0.5
t(14) 5 ?4.04
t(14) 5 ?1.1
t(14) 5 ?2.55
t(14) 5 ?2.50
t(14) 5 0.01
P 5 0.001
P 5 0.29
P 5 0.023
P 5 0.025
P 5 0.99
t(14) 5 ?10.3
t(14) 5 ?4.75
t(14) 5 ?4.1
t(14) 5 ?3.46
t(14) 5 ?2.12
P \ 0.001
P \ 0.001
P \ 0.001
P \ 0.003
P 5 0.05
t(14) 5 ?2.04
t(14) 5 ?0.45
t(14) 5 1.90
t(14) 5 0.47
t(14) 5 0.45
P 5 0.03
P 5 0.32
P 5 0.038
P 5 0.32
P 5 0.33
t(14) 5 ?15.22
t(14) 5 ?5.75
t(14) 5 ?6.66
t(14) 5 ?3.85
t(14) 5 ?2.65
P \ 0.001
P \ 0.001
P \ 0.001
P \ 0.001
P 5 0.01
t(14) 5 ?4.17
t(14) 5 ?1.33
t(14) 5 ?1.78
t(14) 5 ?1.35
t(14) 5 0.59
P \ 0.001
P 5 0.20
P 5 0.09
P 5 0.19
P 5 0.55
Note: Group mean RT (left) and percent error (right) differences and paired t-test results for all within-SOA contrasts of congruent, neutral, and incongruent trials.
Cerebral Cortex November 2009, V 19 N 11 2513
(Hanslmayr et al. 2008; Liotti et al. 2000; West 2003; West and
Alain 1999), ERP waveforms for congruent (blue) and in-
congruent (red) color-word pairs diverge between 300 and 500
ms. This congruency effect is globally reflected as increased
negative-polarity electrical brain activity over central-parietal
regions for the incongruent trials as compared with the con-
gruent trials. In addition, a second, later difference is observed
in the latency window between 550 and 900 ms in which
incongruent trials elicit a more positive deflection over parieto-
occipital sites as compared with congruent trials. The
spatiotemporal distribution of this effect closely resembles
that of the LPC reported by other investigators (West and Alain
1999; Liotti et al. 2000), and we have adopted this nomencla-
ture here. The spatial distribution of the negative (top) and
positive (bottom) components for the no-delay condition can
be seen in Figure 4. These maps are averaged over the 50-ms
interval spanning the peak of the amplitude differences and are
shown as spline-interpolated flat maps on posterior and lateral
views of the head.
Congruency Effects as a Function of SOA
Varying the SOA of the presentation of the colored-bar and
color-word components of the stimulus modulates the timing
of the arrival of conflicting versus congruent information to the
brain areas that detect and resolve conflict. The difference
between the brain responses to congruent and incongruent
stimuli is believed to index this conflict-related activity and
therefore provides a principled marker by which to compare
the influence of SOA on the neural processes underlying
Stroop-related conflict resolution. Here we begin by separately
considering difference-wave activity for the irrelevant-first and
relevant-first SOA conditions.
Incongruency difference waves, computed as the incongru-
ent minus congruent ERPs, are shown on separate plots for the
irrelevant-first (left) and relevant-first (right) SOA conditions
over 4 midline channels in Figure 5. The difference waves for
the no-delay condition (also seen in the right panel of Fig. 3)
are shown in both of these plots (black traces). We present the
irrelevant and relevant-first waveforms on separate plots here
both for clarity of presentation and to illustrate the differential
influence of pre- and post-target distractor presentations on
the Stroop incongruency difference potential.
Irrelevant-First Difference Waves
For the irrelevant-first conditions, the difference waves show
a prominent negative deflection followed by a positive de-
flection at all SOAs. This pattern is globally similar to previous
reports of simultaneous-presentation Stroop tasks (Rebai et al.
1997; West and Alain 1999; Liotti et al. 2000; Atkinson et al.
2003; West 2003; Hesse et al. 2003; Markela-Lerenc et al. 2004;
West R et al. 2005; Hanslmayr et al. 2008), but the current data
now include a manipulation of the relative timing of the
Figure 3. Grand average ERPs (left) and incongruent minus congruent difference
waves (right) are shown for the no-delay condition of the Stroop color-discrimination
task. ERPs are shown for congruent (blue) and incongruent (red) trials at 4 midline
channels (FCz, Cz, CPz, and Pz). The location of these channels are indicated in green
in the key at the bottom. Channels marked in orange around the peak of the effect
were subjected to repeated-measures ANOVAs.
Figure 4. Spatial distribution of the negative-polarity (top) and later positive-polarity
(bottom) incongruency ERP effects for the no-delay SOA condition. Note that these
differences maps are also indicated with asterisks ‘‘*’’ in Figure 6.
Processing Interactions during the Stroop Task
Appelbaum et al.
irrelevant and relevant stimulus components. The largest and
earliest incongruent-versus-congruent negative-wave deflec-
tions were observed for the –200 ms irrelevant-first condition
(Fig. 5, purple), consistent with the pattern of reaction time
differences present in the behavioral data (see Fig. 2 and Table 1).
Difference-wave activity shows a significant monotonic shift
in onset and offset latency for the negative deflection across
the irrelevant-first conditions, as indicated by within-SOA-
condition ANOVA test results (see Methods). Those time points
that reached statistical significance at the P < 0.05 level are
shown by the colored bars presented below the difference
waves in Figure 4 and are included in Table 2.
In addition to the negative-polarity congruency ERP effects,
statistically significant time points are also present at later
latencies for the positive-polarity deflection. This positive
deflection shows a similar monotonic shift with SOA as seen
in the earlier negative deflection and resembles the LPC
observed in other Stroop ERP task variants (West and Alain
1999; Liotti et al. 2000). Trial-by-hemisphere interactions are
present in the LPC response for the –200 and –100 irrelevant-
first conditions. The spatial distribution of these effects can be
seen in Figure 6 (rows 1 and 2) as having a left-sided parietal
Relevant-First Difference Waves
Difference waves as computed here index the neural activity
relating to the incongruency versus the congruency of the task-
relevant and task-irrelevant stimulus components. Because the
word element would theoretically be able to cause interfer-
ence if it appears at any point before the completion of the
color processing, positive-SOA ERP differences should reflect
the influence of postexposure of the irrelevant stimulus feature
on the processing of the relevant target, an effect we are
referring to here as ‘‘backward influence.’’
Relevant-first difference waves and ANOVA test results are
shown on the right side of Figure 5. Analogous to the latency
shifts seen in the irrelevant-first conditions, the +100 SOA
relevant-first ERP difference wave (orange) shows a similar
100-ms latency shift when compared with the no-delay
condition (black). Delaying the irrelevant input an additional
100 ms (to +200 ms), however, had relatively little influence on
the onset latency of the congruency difference wave. This can
be seen both in the overlapping onset of the difference
response for the +100 (orange) and +200 (red) SOA conditions,
and in the ANOVA test results depicted graphically at the
bottom of Figure 5 and entered into Table 2. Interestingly, the
offset of this negative deflection for the +200 SOA condition
does show a consistent, monotonic shift relative to the +100
SOA, suggesting that the duration of the processes generating
the difference wave is not fixed, but rather depends on the
temporal arrangement of the inputs. Lastly, a late positive
difference is present for both the no-delay and +100-ms SOAs
that initiates at roughly the same latency for these 2 conditions.
However, no LPC is seen for the +200 ms SOA, the condition
that also shows the smallest behavioral effects.
Spatiotemporal Distribution of Stroop Incongruency as
a Function of SOA
To portray the temporal evolution of the Stroop effects more
intuitively for the different SOA conditions, it is useful to
visualize the full extent of the ERP difference distribution as it
evolves in time for each of these conditions. This spatiotem-
poral distribution of Stroop interference is shown in Figure 6 as
left and right views of the 2-D spline-interpolated topographic
maps of the difference-wave activity. These maps are computed
as the average activity in 50-ms windows from 0 to 900 ms
following the onset of the task-relevant color-bar stimulus. This
figure is arranged with each SOA condition presented on
Figure 5. Group average difference waves (incongruent minus congruent) are shown
separately for irrelevant-first (left) and relevant-first (right) conditions, with the no-
delay difference wave (black traces) present in both sets of plots. Irrelevant-first
difference waves shifted monotonically as a function of SOA, with the ?200 ms
condition showing the largest and temporally sharpest amplitude difference (purple
traces). Relevant-first difference waves did not show a strictly monotonic shift, with
the þ100 and þ200 SOA difference waves initiating at nearly the same increased
latency relative to the no-delay condition effect, but with the þ200 condition effect
offsetting later. Horizontal bars below the difference waves correspond to the time
points that showed a main effect of congruency according to ANOVAs performed on
the 4 channels surrounding Pz (highlighted in orange in Figure 3 inset). These bars are
color coded with the same condition convention as for the difference waves.
Summary of ANOVA results
SOA condition ANOVA effectNegativityPositivity
?200 Trial type
Trial 3 Hemi
Trial 3 Hemi
Trial 3 Hemi
Trial 3 Hemi
Trial 3 Hemi
Note: Significant latency ranges for trial type (congruent vs. incongruent) and trial type by
hemisphere interactions are indicated for each SOA condition. Both earlier negative and later
positive differences show a monotonic shift with SOA, with the exception of the þ200 (relevant-
first) condition. Main effects of trial type are shown visually in Figure 4.
Cerebral Cortex November 2009, V 19 N 11 2515
a separate column with the map latency indicated to the left
and the voltage color scale shown below. Time points
corresponding to the maps portrayed in Figure 4 are indicated
with an asterisk (‘‘*’’).
Figure 6 clearly shows the temporal shift in the incongruency
effect resulting from the SOA timing manipulation. Here,
a central-parietal negative deflection is present (blue and purple
scale colors) that shifts in a largely monotonic and linear manner
with stimulus SOA, with the exception of the +200 relevant-first
A later, parietal positivity is also present (orange and yellow)
that reaches significance in all but the +200 ms relevant-first
condition. Consistent with the trial type by hemisphere
ANOVA results (Table 2) some hemispheric laterality is
present in the spatial distribution of these effects. In
particular, the LPC appears to be more left-side dominant.
SOA Influences on Peak-Amplitude and -Latency as
a Function of SOA
Results from the within-condition ANOVA tests, and from the
visual display of the difference distributions presented in Figure 6,
+200 +1000 -100 -200
-2.75 0.00 2.75
Figure 6. Spatiotemporal distributions of the congruency-related difference potentials as a function of SOA. The temporal shift due to SOA is evident in these distributions for
both the earlier negative-polarity effect (blue/purple) and the later positive-polarity effect (yellow/orange). As seen in the difference waves in Figure 5, these maps also show that
the negative-polarity waves for the þ100 and þ200 ms SOA conditions onset at roughly the same latency.
Processing Interactions during the Stroop Task
Appelbaum et al.
present a striking qualitative depiction that neural interactions
resulting from stimulus incongruency shift monotonically with
SOA. This observation is substantiated quantitatively by re-
peated-measures ANOVAs performed on the ERP difference-
wave peak-latency values between the SOA conditions (see
main effect of SOA on the peak-latency of the negative-going
ERP deflection (F4,95= 103.5, P < 0.001). Subsequent post hoc
comparisons revealed significant differences between all the
individual SOA conditions except for between +100 and
+200 (P = 0.13).
Lastly, as noted above, the largest incongruency difference-
wave deflections and reaction-time differences were observed
for the –200 ms irrelevant-first condition (see Figs 2 and 5).
Repeated-measures ANOVAs performed on the ERP peak-
amplitudes confirmed a main effect of SOA on the difference-
wave amplitudes (F4,95 = 2.85, P = 0.028), with post hoc
comparisons revealing significant differences between the +200
SOA condition and all other conditions (P < 0.05). Comparable
peak-latency and peak-amplitude analyses were not done on the
LPC as not all SOAs had a significant LPC component.
Stroop interference is a widely used marker of cognitive
function that has been successfully employed to study the
psychological and neural processes of executive attention. In the
present study, Stroop incongruency effects were observed in
both behavioral and electrophysiological measures across a range
of temporal offsets introduced between the physical color and
color-word stimulus components. In addition to replicating the
well-established behavioral and ERP patterns reported when
Stroop stimulus components are presented simultaneously, we
observed substantial interactions of SOA with both the reaction
times and the ERP congruency-related difference waves. These
interactions were manifest as both amplitudes and latency
changes with differential effects due to pretarget and post-target
SOAs. Our results demonstrated the greatest incongruency
effects when an irrelevant stimulus preceded a relevant target
(e.g., –200 ms SOA) and reduced effects when an irrelevant
stimulus followed a relevant target (e.g., +200 ms SOA).
We interpret this pattern of results as reflecting 2 distinct
processes. When the target color-bar is preceded by an irrele-
vant word stimulus, the increased RT differences and ERP
difference-wave amplitudes can be viewed as reflecting a
priming mechanism. More specifically, in line with classic
theories of perceptual priming (Posner and Snyder 1975;
MacLeod 1991), the earlier presentation of an irrelevant word
stimulus gives the brain a ‘‘head start’’ in its processing,
including that of its semantic characteristics. This head start
therefore primes the response selection and results in a greater
competitive advantage for when the bar colors match the word
meaning, and an increase in interference when they do not
match. The present findings further indicate that presenting
the irrelevant stimulus prior to the target also appears to
serve a general cueing or alerting function, resulting in
enhanced processing for all target types that follow, regardless
of their congruency relationship to the priming stimulus.
When the to-be-reported, color-bar stimulus is followed by
an irrelevant color-word stimulus, a reduction in the Stroop
incongruency effect is observed for both RTs and ERP
differences, reflecting a diminishing influence of the distractor.
This backward influence can be explained by considering
classic models of forced-choice decision making (Ratcliff 1978;
Logan 1980; Luce 1986; Rumelhart et al. 1986; Cohen et al.
1990; Cohen et al. 1992; Ratcliff and Smith 2004; Voss et al.
2004) in which evidence accumulates over time until a re-
sponse threshold is reached (although see Stafford and Gurney
2004, 2007 for discussion of other computational models of
Stroop effects). When the color-bar component is presented
first (positive SOAs), processing of this task-relevant stimulus
proceeds unimpeded for some period of time, allowing more
evidence to accumulate in favor of the appropriate response
prior to the introduction of the irrelevant stimulus. Under
these circumstances, the irrelevant stimulus is in a position of
having to catch up and therefore elicits smaller behavioral
effects and smaller and later neural effects when presented
after a temporal delay.
SOA and ERP Incongruency Effects
The ERP is a measure of the brain’s electrical activity elicited by
specific sensory stimuli and cognitive processes. Voltage
deflections in the ERP that occur within the first ~200 ms show
a characteristic pattern that varies with the sensory character-
istics of the evoking stimulus. Deflections occurring later, how-
ever, vary more with the cognitive characteristics of processing
brought about by the task. ERP components, such as the
incongruency difference effect elicited in these tasks, are
defined by their relative onset latency, voltage amplitude, scalp
distribution, and sensitivity to experimental manipulation, and
thus provide a useful measure of the cognitive processes
In the present experimental design, the SOAs of the task-
relevant target and task-irrelevant distractor stimulus compo-
nents were varied in 100-ms increments, thereby altering the
temporal dynamics of the sensory processing of the component
parts of the stimuli, as well as the intersection of the processing
of the congruent and incongruent components in the brain. By
presenting these stimuli at relatively short SOAs, the ERPs to
successive stimuli overlap in time with differing amounts of
distortion depending on the length of the temporal separation.
Although effective methods exist for deconvolving such
differential overlap in the ERP waveforms with certain
manipulations or control conditions (Woldorff 1993), a partic-
ularly pragmatic approach in the current design is to restrict
direct comparisons between SOAs to the incongruency (in-
congruent minus congruent) difference wave. As noted in the
introduction, an equivalent amount of overlap is present for the
incongruent and congruent trials within a given SOA, and
therefore evaluating the difference wave is an effective means
to isolate how processes related to the cognitive resolution of
stimulus incongruency are influenced by the temporal separa-
tion of the stimulus components.
The influence of this temporal manipulation could in
principle take many forms in the ERP responses as determined
by interactions between the stimulus processing, response
selection, and the temporal arrangement of the inputs. As
alluded to above (see Introduction), pre-exposure and post-
exposure of task-irrelevant information could have affected
either the amplitude or latency of the ERP incongruency
difference wave, or both. We observed that the SOA manipu-
lation resulted in different modulations to the ERP effect for
negative and positive SOAs. First, nearly twice as many
Cerebral Cortex November 2009, V 19 N 11 2517
significant time points (as computed by the ANOVA) were
present in the negative versus positive SOAs, presumably
reflecting the greater neural activity elicited by incompatible
information when it arrives earlier to induce perceptual
priming. Beyond this, negative-SOA conditions elicited ampli-
tude changes and linear shifts in response latency that
corresponded closely to the 100-ms temporal offsets in-
troduced between the stimulus components. Positive SOAs,
however, produced amplitude changes and latency shifts that
did not shift linearly with the temporal separation introduced
between the stimulus components. Specifically, the +200 SOA
ERP effect did not adhere to the monotonic shift in response
latency nor did it contain a LPC, although it did demonstrate
a longer lasting negativity. In addition, this stimulus SOA
corresponded to only marginal behavioral effects. Although the
functional significance of these observations for the +200 SOA
condition is not clear, one possible interpretation is that
conflict influence in this case did not ramify into an LPC
response due to its late arrival. The interaction with semantic
processes—a reported functional correlate of the LPC compo-
nent (West and Alain 1999; Liotti et al. 2000)—may therefore
not have been activated, resulting in relatively weak behavioral
Spatiotemporal Distribution of Stroop Incongruency
Since the earliest application of ERPs in studying the Stroop
effect (Scott et al. 1967), dozens of researchers have utilized
this technique. Although several groups have reported some
small differences in the early sensory components (e.g., Ilan and
Polich 1999; Hanslmayr et al. 2008) most have focused on the
later cognitive processes related to the incongruency versus
congruency of the stimulus components. Though far from
exclusive, the majority of ERP results have claimed that the left
hemisphere generally shows more electrophysiological in-
terference effects than the right, an observation that appears
to also be present in the current results.
Stroop-related incongruency, and stimulus incompatibility
more generally, has been associated with function in the ACC,
dorsal lateral prefrontal cortex, and the parietal lobe (see
reviews by Roberts and Hall 2008; Mansouri et al. 2009).
Numerous ERP (Rebai et al. 1997; West and Alain 1999; Liotti
et al. 2000; Atkinson et al. 2003; Hesse et al. 2003; West 2003;
Markela-Lerenc et al. 2004; West et al. 2005; Hanslmayr et al.
2008) and functional magnetic resonance imaging (fMRI)
(Botvinick et al. 1999; Peterson et al. 1999; MacDonald et al.
2000; Botvinick et al. 2004; Kerns et al. 2004; Egner and Hirsch
2005; Polk et al. 2008) studies have indicated that these areas
are actively involved in the monitoring for, and adjustment in
control due to, stimulus conflict. However, as addressed in a
recent review by Mansouri et al. (2009), the relative in-
volvement of these areas in distinct functional operations is still
Although the negative ERP Stroop difference component has
typically been modeled as arising from generators in the ACC
(Liotti et al. 2000; Hanslmayr et al. 2008), the particular
distribution and waveform morphology elicited by the incon-
gruency subtraction has varied considerably with the specifics
of the experimental manipulation and response mode. For
example, Liotti et al. (2000) observed substantial differences in
scalp distributions for verbal-response versus manual-response
variants of the task, with a more anterior-medial focus for
verbal responses (both overt and covert) and a broader more
centro-parietal distribution for manual ones. Although some
other researchers have also reported relatively posterior
distributions for Stroop incongruency effects with manual
responses (Rebai et al. 1997; West and Alain 1999; Liotti et al.
2000), some others have reported fairly anterior distributions
with manual responses (e.g., Markela-Lerenc et al. 2004;
Hanslmayr et al. 2008). Regardless, this leaves open the
possibility that different sets of neural generators are involved
in the selection of competing responses when different output
effectors are employed. Beyond this, lesion data have indicated
that different portions of the ACC are involved in manual versus
verbal responses in the Stroop task (Swick and Turken 2002).
In the present study, the response distribution of the
incongruency negativity (see Figs 4 and 6), for all the SOAs, is
more posterior and slightly left-sided, consistent with that
reported by Liotti et al. (2000) and West and Alain (1999) for
a manual-response Stroop task, and potentially consistent with
a source in the more posterior regions of the ACC (Liotti et al.
2000). Considering the posterior distribution of this effect,
however, another possible explanation is that it derives from
a set of parietal generators that are relatively left dominant,
perhaps along with contribution from more posterior or medial
regions of the cingulate. This interpretation is consistent with
numerous reports from neurophysiology (Goodale and Milner
1992; Snyder et al. 2000) and fMRI (Bunge et al. 2002) that the
left parietal cortex is involved in maintaining and activating
motor responses on the basis of stimulus--response associations
during task performance. Given the potential cognitive demands
inherent in maintaining the mapping between 4 stimulus
types and 4 responses, this interpretation seems a reasonable
It should be noted that the ERP results of the present paper
are reported using a voltage referencing scheme of the
algebraically averaged mastoids. Although this referencing
scheme is fairly common, it does differ from the also commonly
used average reference (i.e., where the reference is the average
voltage of all the electrodes). Accordingly, we have also exam-
ined the present data using the average reference scheme, and
a comparison of the 2 approaches is included in the sup-
plementary materials (Supplementary Materials 2). The choice
of the referencing scheme had little effect on the topographic
distribution of the Stroop incongruency effects (although using
the average reference scheme did somewhat reduce the
amplitude of the effects). The close similarity in topography
suggests that the relatively posterior distribution of the effects
observed here likely relate to paradigmatic aspects of the
design and task (including possibly the use of a manual
response—cf. Liotti et al. 2000), rather than the choice of
Priming and Backwards Interference versus Facilitation,
Inhibition, and General Alerting Mechanisms
In the present study our experimental focus concerned the
effects of temporal separation on the processing of compatible
versus incompatible stimulus components presented at different
temporal delays. As already discussed, the pattern of results
elicited in this design demonstrate clear interactions between
SOA and stimulus incongruency, that manifest as ‘‘priming
influences’’ in instances where the irrelevant stimulus precedes
the target and ‘‘backward influences’’ when the irrelevant
stimulus component comes later. By definition, however, those
Processing Interactions during the Stroop Task
Appelbaum et al.
trials that included a pretarget distractor stimulus (the task-
irrelevant word) differed in form from the other SOA conditions,
where the target occurred simultaneously or first. The pretarget
stimulus in these conditions could have had certain consequen-
ces that complicate the interpretation of the priming influences
that stem from the negative-SOA conditions. In particular, it is
possible that the pretarget stimulus could have acted as an
exogenous cue to alert the participant as to an impending target
presentation (i.e., the target color-bar will occur within 200 ms),
regardless of whether it was congruent or incongruent in
meaning. This could therefore have acted to enhance processing
(e.g., reduce RT values) for all the negative-SOA conditions,
diluting any interference effects for the incongruent RTs and
increasing the facilitation on the congruent RT values. Our
results from the main experiment are, in fact, consistent with
this possibility. As seen graphically in Figure 2A, a main effect of
SOA was present for the congruent but not incongruent trials,
with the slope of this function demonstrating a strong facilita-
tion (lower RTs) with greater negative SOAs. Therefore,
although the absolute magnitude of interference increased with
earlier SOA presentations, it is unclear from these data from the
main experiment alone whether these effects were driven by
facilitation or interference.
Existing accounts of Stroop-task effects generally make
a distinction between facilitation resulting from stimulus
congruency and interference due to incongruency by con-
trasting performance to a semantically neutral control condi-
tion (Glaser and Glaser 1982; Dunbar and MacLeod 1984;
MacLeod 1991, 1998; Tzelgov et al. 1992; MacLeod and
MacDonald 2000). Due to practical signal-to-noise constraints
inherent to the ERP analyses, and the large number of trial
types imposed by the 5 levels of SOA in our design, we were
not able to include a neutral control condition in the main
experiment. However, because the distinction between stim-
ulus compatibility and behavioral facilitation or inhibition
constitutes an important processing distinction, we included
a full behavioral replication of the SOA design that included
a neutral reference condition. This allowed us to assess the
possibility that pre-exposure of the distractor may be serving as
a general exogenous alerting cue, and in turn altering the
apparent contributions of facilitation and inhibition to the
observed results in the main experiment.
Results from the behavioral control experiment indeed
support this interpretation. The results replicate the common
observation that neutral trial performance is intermediate
between congruent and incongruent trial RTs. Most impor-
tantly, however, these data demonstrate that there is a main
effect of SOA on the RT of the neutral trials, with the earlier
SOAs facilitating the performance for the neutral trials in the
same direction as the facilitation observed with the congruent
trials (although not as strongly). These results therefore
provide important evidence that pre-exposure of task-irrele-
vant stimuli were indeed serving to exert a general alerting
influencing that affects performance on all negative-SOA trials.
Because the slope of the neutral versus SOA data is in-
termediate between congruent and incongruent trials, it is
reasonable to interpret the SOA effects as reflecting both
facilitation and inhibitory influences. To help visualize this, we
presented the separate contributions of facilitation (white
bars) and interference (black bars) in relation to the neutral
RTs in Figure 2B. Although these behavioral results help
disentangle the contribution of general alerting influences from
facilitation and interference, a net increase in the magnitude of
the RT difference for earlier SOAs is still present, suggesting the
presence of priming due to an exogenously cued, alerting
effect, as noted above.
Decision processes, such as those employed in the Stroop
color-naming task, involve a cascade of operations including
the sensory processing and discrimination of stimulus in-
formation, response selection, and the implementation of a final
motor action plan. The present findings broaden our un-
derstanding of the temporal dynamics of neural processes
resulting from stimulus incompatibility in the Stroop task.
Specifically, we show that Stroop incongruency produces
different functional characteristics due to pre-exposure and
postexposure of task-irrelevant stimulus components. We
observe that pre-exposure of an irrelevant word stimulus
elicits greater RT differences and larger ERP effects, which we
interpret as reflecting a form of conflict-related priming.
Postexposure of the irrelevant word stimulus results in
reduced RT and ERP differences, suggesting that task-irrelevant
stimuli have a diminishing influence with greater delays relative
to the task-relevant target. The SOA manipulation also induced
corresponding changes in the onset latencies of the ERP
incongruency effects presumably reflecting the time range at
which the processing of the relevant and irrelevant stimulus
components intersect and therefore elicit interference.
materialcanbe foundat: http://www.cercor.
National Institute of Heath grants (numbers R01-MH60415,
R01-NS051048) and National Science Foundation grant (num-
ber NSF-BCS-0524031) to M.G.W.
We wish to thank William Wojtach, Wen Chen, and Tineke Grent-t’-Jong
for their helpful comments on this manuscript. We would also like to
thank Lauren Davis and Robert Won for their help with data collection.
Conflict of Interest Statement: None declared.
Allport DA. 1982. Attention and performance. In: Claxton GI, editor.
New directions in cognitive psychology. London: Routledge &
Kegan Paul. p. 112--153.
Atkinson CM, Drysdale KA, Fulham WR. 2003. Event-related potentials
to Stroop and reverse Stroop stimuli. Int J Psychophysiol. 47:1--21.
Botvinick M, Nystrom LE, Fissell K, Carter CS, Cohen JD. 1999. Conflict
monitoring versus selection-for-action in anterior cingulate cortex.
Botvinick MM, Cohen JD, Carter CS. 2004. Conflict monitoring and
anterior cingulate cortex: an update. Trends Cogn Sci. 8:539--546.
Bunge SA, Hazeltine E, Scanlon MD, Rosen AC, Gabrieli JD. 2002.
Dissociable contributions of prefrontal and parietal cortices to
response selection. Neuroimage. 17:1562--1571.
Cohen JD, Dunbar K, McClelland JL. 1990. On the control of automatic
processes: a parallel distributed processing account of the Stroop
effect. Psychol Rev. 97:332--361.
Cerebral Cortex November 2009, V 19 N 11 2519
Cohen JD, Servan-Schreiber D, McClelland JL. 1992. A parallel
distributed processing approach to automaticity. Am J Psychol.
Dunbar K, MacLeod CM. 1984. A horse race of a different color: Stroop
interference patterns with transformed words. J Exp Psychol Hum
Percept Perform. 10:622--639.
Duncan-Johnson CC, Kopell BS. 1981. The Stroop effect: brain
potentials localize the source of interference. Science. 214:938--940.
Dyer FN. 1971. The effect of word meaning response: Stroop
interference for different preexposures of the word. Psychon Sci.
Dyer FN. 1973. The Stroop phenomenon and its use in the study of
perceptual, cognitive and response processes. Mem Cogn. 1:106--120.
Egner T, Hirsch J. 2005. Cognitive control mechanisms resolve conflict
through cortical amplification of task-relevant information. Nat
Enns JT, Di Lollo V. 2000. What’s new in visual masking? Trends Cogn
Glaser MO, Glaser WR. 1982. Time course analysis of the Stroop
phenomenon. J Exp Psychol Hum Percept Perform. 8:875--894.
Glaser WR, Dungelhoff FJ. 1984. The time course of picture-word
interference. J Exp Psychol Hum Percept Perform. 10:640--654.
Glaser WR, Glaser MO. 1989. Context effects in Stroop-like word and
picture processing. J Exp Psychol Gen. 118:13--42.
Gold JI, Shadlen MN. 2000. Representation of a perceptual decision in
developing oculomotor commands. Nature. 404:390--394.
Goodale MA, Milner AD. 1992. Separate visual pathways for perception
and action. Trends Neurosci. 15:20--25.
Hanslmayr S, Pastotter B, Bauml KH, Gruber S, Wimber M, Klimesch W.
2008. The electrophysiological dynamics of interference during the
Stroop task. J Cogn Neurosci. 20:215--225.
Hesse W, Moller E, Arnold M, Schack B. 2003. The use of time-variant
EEG Granger causality for inspecting directed interdependencies of
neural assemblies. J Neurosci Methods. 124:27--44.
Hirst W, Kalmar D. 1987. Characterizing attentional resources. J Exp
Psychol Gen. 116:68--81.
Ilan AB, Polich J. 1999. P300 and response time from a manual Stroop
task. Clin Neurophysiol. 110:367--373.
Jiang Y, Luo YJ, Parasuraman R. 2002. Neural correlates of perceptual
priming of visual motion. Brain Res Bull. 57:211--219.
Kerns JG, Cohen JD, MacDonald AW, 3rd, Cho RY, Stenger VA,
Carter CS. 2004. Anterior cingulate conflict monitoring and adjust-
ments in control. Science. 303:1023--1026.
Kiefer M, Brendel D. 2006. Attentional modulation of unconscious
‘‘automatic’’ processes:evidence from event-related potentials in
a masked priming paradigm. J Cogn Neurosci. 18:184--198.
Kiefer M, Spitzer M. 2000. Time course of conscious and unconscious
semantic brain activation. Neuroreport. 11:2401--2407.
Kutas M, Federmeier KD. 2000. Electrophysiology reveals semantic
memory use in language comprehension. Trends Cogn Sci.
Kutas M, Hillyard SA. 1980. Reading senseless sentences: brain
potentials reflect semantic incongruity. Science. 207:203--205.
Liotti M, Woldorff MG, Perez R, Mayberg HS. 2000. An ERP study of the
temporal course of the Stroop color-word interference effect.
Logan GD. 1980. Attention and automaticity in Stroop and priming
tasks: theory and data. Cognit Psychol. 12:523--553.
Luce R. 1986. Response times: their role in inferring elementary mental
organization. New York (NY): Clarendon Press.
MacDonald AW, 3rd, Cohen JD, Stenger VA, Carter CS. 2000.
Dissociating the role of the dorsolateral prefrontal and anterior
cingulate cortex in cognitive control. Science. 288:1835--1838.
MacLeod CM. 1991. Half a century of research on the Stroop effect: an
integrative review. Psychol Bull. 109:163--203.
MacLeod CM. 1998. Training on integrated versus separated Stroop
tasks: the progression of interference and facilitation. Mem Cognit.
MacLeod CM, MacDonald PA. 2000. Interdimensional interference in
the Stroop effect: uncovering the cognitive and neural anatomy of
attention. Trends Cogn Sci. 4:383--391.
Mansouri FA, Tanaka K, Buckley MJ. 2009. Conflict-induced behavioural
adjustment: a clue to the executive functions of the prefrontal
cortex. Nat Rev Neurosci. 10:141--152.
Marcel AJ. 1983. Conscious and unconscious perception: experiments
Markela-Lerenc J, Ille N, Kaiser S, Fiedler P, Mundt C, Weisbrod M. 2004.
Prefrontal-cingulate activation during executive control: which
comes first? Brain Res Cogn Brain Res. 18:278--287.
Neely JH. 1991. Semantic priming effects in visual word recognition:
a selected review of current findings and theories. In: Bensner D,
Humphreys GW, editors. Basic processing in reading—visual word
recognition. Hillsdale (NJ): Erlbaum. p. 264--333.
Peterson BS, Skudlarski P, Gatenby JC, Zhang H, Anderson AW, Gore JC.
1999. An fMRI study of Stroop word-color interference: evidence for
cingulate subregions subserving multiple distributed attentional
systems. Biol Psychiatry. 45:1237--1258.
Phaf RH, Van der Heijden AH, Hudson PT. 1990. SLAM: a connectionist
model for attention in visual selection tasks. Cognit Psychol.
Platt ML. 2002. Neural correlates of decisions. Curr Opin Neurobiol.
Polk TA, Drake RM, Jonides JJ, Smith MR, Smith EE. 2008. Attention
enhances the neural processing of relevant features and suppresses
the processing of irrelevant features in humans: a functional
magnetic resonance imaging study of the Stroop task. J Neurosci.
Posner M, Snyder C. 1975. Attention and cognitive control. In: Solso R,
editor. Information processing and cognition. Hillsdale (NJ):
Ratcliff R. 1978. A theory of memory retrieval. Psychol Rev. 85:59--108.
Ratcliff R, Cherian A, Segraves M. 2003. A comparison of macaque
behavior and superior colliculus neuronal activity to predictions
from modelsof two-choice
Ratcliff R, Smith PL. 2004. A comparison of sequential sampling models
for two-choice reaction time. Psychol Rev. 111:333--367.
Rebai M, Bernard C, Lannou J. 1997. The Stroop’s test evokes a negative
brain potential, the N400. Int J Neurosci. 91:85--94.
Reddi BA, Asrress KN, Carpenter RH. 2003. Accuracy, information, and
response time in a saccadic decision task. J Neurophysiol.
Roberts KL, Hall DA. 2008. Examining a supramodal network for
conflict processing: a systematic review and novel functional
magnetic resonance imaging data for related visual and auditory
stroop tasks. J Cogn Neurosci. 20:1063--1078.
Rosenfeld JP, Skogsberg KR. 2006. P300-based Stroop study with low
probability and target Stroop oddballs: the evidence still favors the
response selection hypothesis. Int J Psychophysiol. 60:240--250.
Rumelhart DE, Hinton GE, McClelland JL. 1986. A general framework
for parallel distributed processing. In: Rumelhart DE, McClelland JL,
Group tPR, editors. Parallel distributed processing: explorations in
the microstructure of cognition. Cambridge (MA): MIT Press.
Schall JD. 2001. Neural basis of deciding, choosing and acting. Nat Rev
Scott DF, Hoffmann HJ, Bickford RG. 1967. Changes in summated visual
potentials. Lambda waves during mental tasks using the Stroop test.
Percept Mot Skills. 25:993--996.
Snyder LH, Batista AP, Andersen RA. 2000. Intention-related activity in
the posterior parietal cortex: a review. Vision Res. 40:1433--1441.
Stafford T, Gurney KN. 2004. The role of response mechanisms in
determining reaction time performance: Pieron’s law revisited.
Psychon Bull Rev. 11:975--987.
Stafford T, Gurney KN. 2007. Biologically constrained action selection
improves cognitive control in a model of the Stroop task. Philos
Trans R Soc Lond B Biol Sci. 362:1671--1684.
Stroop JR. 1935. Studies of interference in serial verbal reactions. J Exp
Sugg MJ, McDonald JE. 1994. Time course of inhibition in color-
response and word-response versions of the Stroop task. J Exp
Psychol Hum Percept Perform. 20:647--675.
Processing Interactions during the Stroop Task
Appelbaum et al.
Swick D, Turken AU. 2002. Dissociation between conflict detection and Download full-text
error monitoring in the human anterior cingulate cortex. Proc Natl
Acad Sci USA. 99:16354--16359.
Tipper SP. 2001. Does negative priming reflect inhibitory mechanisms?
A review and integration of conflicting views. Q J Exp Psychol A.
Tzelgov J, Henik A, Berger J. 1992. Controlling Stroop effects by
manipulating expectations for color words. Mem Cognit. 20:727--735.
Voss A, Rothermund K, Voss J. 2004. Interpreting the parameters of the
diffusion model: an empirical validation. Mem Cognit. 32:1206--1220.
West R. 2003. Neural correlates of cognitive control and conflict
detection in the Stroop and digit-location tasks. Neuropsychologia.
West R, Alain C. 1999. Event-related neural activity associated with the
Stroop task. Brain Res Cogn Brain Res. 8:157--164.
West R, Bowry R, McConville C. 2004. Sensitivity of medial frontal
cortex to response and nonresponse conflict. Psychophysiology.
West R, Jakubek K, Wymbs N, Perry M, Moore K. 2005. Neural
correlates of conflict processing. Exp Brain Res. 167:38--48.
Woldorff MG. 1993. Distortion of ERP averages due to overlap from
temporally adjacent ERPs: analysis and correction. Psychophysiology.
Woldorff MG, Liotti M, Seabolt M, Busse L, Lancaster JL, Fox PT. 2002.
The temporal dynamics of the effects in occipital cortex of visual-
spatial selective attention. Brain Res Cogn Brain Res. 15:1--15.
Cerebral Cortex November 2009, V 19 N 11 2521