Journal of the Institute for Psychological and Physical Science, Vol. 1, No. 1, 63–69, 2009

Perceptual Similarity between Pictures Modulates ERPs during a Stop/NoStop Task
Aki AKAMINE＊1) and Mitsuro KIDA＊2)   Similarities between stimuli affect performance on reaction time (RT) tasks. This study examined whether
similarities between pictures modulate stimulus-elicited event-related brain potentials (ERPs) during a Stop/
NoStop task, in which participants had to withhold motor responses. The Stop/NoStop task is a relatively novel
method of assessing discriminative RTs, in which participants are asked to withhold a motor response to aparticular stimulus (Stop trials), but to respond to all other stimuli (NoStop trials). Stimulus similarity was
manipulated by varying the perceptual similarity between the Stop stimuli and the NoStop stimuli. ERPs for
Stop stimuli were recorded during both low- and high-similarity conditions. These new data were analyzed
along with data previously collected during a medium-similarity experiment (Akamine & Kida, 2006). The Stop
stimuli elicited a large central-parietal dominant positive wave (late P3), with a peak latency of about
400–550 ms. Late P3 latency significantly increased as a function of stimulus similarity, but amplitude did notchange. This component closely resembles the NoGo P3, which is related to response inhibition. Difficulties indiscriminating between the stimuli would cause a delay in the inhibition of responses to the Stop stimuli. In
addition, RTs for NoStop stimuli increased as a function of stimulus similarity. These results suggest that thestimulus processing that is required if a motor response is to be withheld might have a reciprocal relationshipwith response execution in a discriminative RT task.
Keywords: event-related brain potentials, P2, N2, P3, Stop/NoStop task, response inhibition

In various cognitive tasks, participants’ performance (e.g.,reaction times (RTs), error rates) vary according to thenature of the experimental manipulation, including physicalstimulus properties, the probability of stimulus occurrence,and the degree of similarity across stimulus categories. In
order to perform a task successfully, it is important toaccurately process not only the target stimuli (i.e., aparticipant is required to pay attention and usually to
execute a motor response), but also any non-target stimuli(i.e., a participant is required to withhold a motor response
to such stimuli). However, there are very few investigationsof the relationship between cognitive processing of target
and non-target stimuli. Moreover, how the two types ofprocessing influence each other remains unclear. We
recorded event-related brain potentials (ERPs) during a
discriminative reaction time task in the present study, toexamine the cognitive processing of a stimulus for which a
motor response is withheld.
ERPs have served as a valuable tool for investigating thebrain activity that underlies information processing inhumans. One particularly useful aspect of the ERP
technique is that it enables processing activities to bestudied even when the individual does not perform an overt
response. ERPs thus overcome a limitation of behavioral
measures such as RTs, the recording of which necessitatesobservable responses.
NoGo P3
The Go/NoGo task is a familiar cognitive task in ERP
research. In this task, participants are required to identify
Go (target) stimuli and respond (e.g., pressing a button),whereas they are not required to detect NoGo stimuli and to
make a motor response. The classic P3 (P3b) elicited by Go
stimuli has had its maximum amplitude at the moreposterior scalp sites. In contrast, the NoGo response has asomewhat longer latency and a more frontal-central
distribution than the target-related P3, and this component
is often referred to as the NoGo P3, to distinguish it fromthe classic P3 (Eimer, 1993; Fallgatter & Strik, 1999; Jodo
& Inoue, 1990; Strik, Fallgatter, Brandeis, & Pascual-* 1) Department of Child Care Studies, School of Human Care Studies, Nagoya University of Arts and Sciences* 2) Department of Psychology, Faculty of Psychological and Physical Sciences, Aichi Gakuin University
Requests for reprints should be sent to: E-mail: akamine@nuas.ac.jp

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Aki AKAMINE and Mitsuro KIDA

Marqui, 1998). Because these topographies remain constantacross visual and auditory modalities, both the Go P3 andNoGo P3 have been described as having a modality
independent nature (Tekok-Kilic, Shucard, & Shucard,
2001). Topographical differences between Go and NoGo
conditions suggest that these ERPs do constitute two
separate components: Each corresponds to a distinct neuralgenerator, and these components appear to be produced byfunctionally distinct brain systems (Pfefferbaum & Ford,
1988). Indeed, the Go P3 has been related to target
detection or response production (Eimer, 1993;
Pfefferbaum, Ford, Weller & Kopell, 1985), whereas the
NoGo P3 has been associated with response inhibition(Schupp, Lutzenberger, Rau, & Birbaumer, 1994; Strik etal., 1998). NoGo P3 is a slow positive variation without aclear peak. Although many researchers have described P3(P3b) latencies, we could not find a study that had examined
NoGo P3 latencies.
Using Go/NoGo and Stop/NoStop tasks, we examinedthe effects of negative emotions on RTs and ERPs
(Akamine & Kida, 2005) . We have also investigated ERPs
associated with stimulus presentations when participants
withheld motor responses in the experiment (Akamine &Kida, 2006). The Stop/NoStop task is a discriminative
reaction time task in which participants are required towithhold a motor response to a particular stimulus (Stoptrials), but to respond to all other stimuli (NoStop trials).
Both NoGo and Stop stimuli elicit two large positive
components, termed early P3 and late P3. These areobserved around 300 ms and 500 ms after stimulus onset,
respectively. The amplitude of the early P3 increases from
Fz to Pz, and does not appear to differ across NoGo andStop stimuli. On the other hand, the late P3 has a centralparietal distribution and is notably larger for Stop stimuli
than for NoGo stimuli. The late P3 elicited by Stop stimuli
exhibits a clear peak. However, such a clear peak has notbeen observed during processing of NoGo stimuli. It has
been suggested that the early P3 should be equivalent to theP3b, and that the late P3 should be equivalent to theso-called NoGo P3 (e.g. Jodo & Inoue, 1990). Thus, earlyP3 appears to be related to stimulus evaluation, whereas
late P3 seems to reflect aspects of response inhibition(Schupp et al., 1994; Strik et al., 1998).
As briefly mentioned above, in the Stop/NoStop task it is
crucial that participants judge whether an incoming
stimulus is a Stop stimulus or not. It is expected that the
Stop stimulus would capture participants’ attention andwould activate various cognitive processes, including both
perceptual and response processes. However, participants
are required to withhold a motor response to the Stop

stimulus. To prevent the implementation of a motor
response, the participants would need to resolve thecognitive conflict between perceptual and response
processes that is produced by the task instructions. Thus, it
has been suggested that the large late P3 elicited by Stop
stimuli reflects effortful inhibition of activated response
processes (Akamine & Kida, 2004, 2006). One would
expect that investigating the late P3 elicited by Stop stimuli
would provide somewhat different findings for response
inhibition.
Purpose of the Present Study
It was assumed that degree of similarity between picture
stimuli would cause difficulty in stimulus discrimination.
The present study was designed to examine the effects ofdifficulties in stimulus discrimination on cognitive
processes activated by a stimulus that requires a motor
response to be withheld, i.e., a Stop/NoStop task. ERPs for
Stop stimuli were recorded during two experimental
conditions, employing the same methodology as used in ourprevious study (Akamine & Kida, 2006). In this previous
study, five categories of pictures (cars, people, flowers,
electronics, and landscapes, with probability of 0.4, 0.3, 0.1,
0.1 and 0.1) were used, and the car stimuli were assigned tobe the Stop stimuli. Here, the car stimuli were replaced withsimple geometric shapes in Experiment 1, and with animals
in Experiment 2. Experiment 1 served as the low-similarity
condition and Experiment 2 as the high-similarity condition.
The previous experiment in which the car stimuli were usedas the Stop stimuli was defined as the medium-similarity
condition for present purposes. Degree of similarity
between picture stimuli was manipulated based on the
degree of perceptual similarity between Stop and NoStop“people” stimuli, which were presented most frequent in
the NoStop stimuli. ERPs elicited by the Stop stimuli acrossthese three conditions were analyzed here.1)

Experiment 1 2)
MethodWe used a similar method to that of Akamine and Kida
(2006).
Participants
Twenty-one students at Aichi Gakuin University (15women and 6 men, M age = 22.2 years) participated in the
study for payment. None of them had participated in ourprevious study (Akamine & Kida, 2006).

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Perceptual Similarity between Pictures Modulates ERPs during a Stop/NoStop Task

Experiment 2

Procedure
Stimuli. Five groups of color pictures were used in thisstudy: Simple geometric shapes, people, flowers,
electronics, and landscapes. Except for the simple
geometric shapes, these pictures were the same as thoseused by Akamine and Kida (2006). The simple geometricshapes category consisted of 20 different images (e.g.,
circle, triangle, square). The people category included 10
different ordinary faces (neutral stimuli) and 10 different
faces that featured some type of skin disease or external
injury (negative stimuli). The remaining three categories(flowers, electronics, and landscapes) consisted of 5
pictures each.
Stimuli were presented one at a time on a computer
screen that was positioned approximately 1 m in front of
the participants. Each picture subtended a visual angle of
14.0° horizontally and 10.0° vertically, and was presented
with a fixed stimulus onset asynchrony of 3,000 ms (500 ms
on and 2,500 ms off).
Reaction time task. Participants performed a Stop/NoStop
task. The five categories of pictures, simple geometricshapes, people, flowers, electronics, and landscapes were
presented randomly with probabilities of 0.40, 0.30, 0.10,
0.10, and 0.10, respectively. The participants were required
to respond to all pictures except for geometric shapes bypressing a button with the index finger of their right hand,as quickly and accurately as possible. Following 50 practice
trials, all participants performed 300 experimental trials,
which consisted of six blocks with 50 trials each.3)

MethodWe used the same method as in Experiment 1. The
differences between Experiments 1 and 2 were as follows:
Participants
Thirteen students at Aichi Gakuin University (10 womenand 3 men, M age = 21.4 years) participated in theexperiment for payment. They had not participated inExperiment 1 or Akamine and Kida (2006).
Procedure
Stimuli. Animal pictures, 20 different images ofmonkeys’, dogs’ and cats’ faces, were used instead ofsimple geometric shapes. The other pictures were the sameas those used in our previous experiments.
Reaction time task. The participants’ task was to press abutton in response to all pictures except the animals (i.e.,
people, flowers, electronics, and landscapes) with the index
finger of their right hand, as quickly and accurately as
possible.
ERP Recording and Data Collection
ERP waveforms were obtained for each participant andsite, in response to the Stop animal stimuli.

Results

ERP Recording and Data Collection
Electrophysiological data were collected during thediscriminative reaction time task. Electroencephalograms(EEG) were recorded from four midline sites, Fz, Cz, Pz,
and Oz, referenced to linked earlobes. An electrooculogram(EOG) was recorded from an electrode located below theright eye. Electrode impedances did not exceed 10 kOhms.
EEG and EOG signals were amplified using the San-ei 360
system (filter bandpass: 0.05 (time constant 3 s) –30 Hz).
The data, together with trial information, were stored on amagnetic tape and processed offline. All recordings weredigitized at 500 Hz. ERP waveforms were computed foreach participant by averaging readings for the epoch from
200 ms before stimulus onset to 1,000 ms after stimulus
onset. Averaged ERPs were obtained for the Stop geometricshape stimuli at each electrode. The trials on which eye
movements or blinks occurred and those with an incorrect
or no response were excluded from the ERP averages. The
averaged ERPs were aligned to a 200-ms pre-stimulus
baseline.

The purpose of the present study was to examine whether
stimulus similarities modulate ERPs for Stop stimuli. To
this end, the data collected in our previous study (Akamine& Kida, 20064)) were newly analyzed and compared withthe data obtained in the present Experiments 1 and 2.
Behavioral Data
Mean error rates and RTs for each task condition are
shown in Table 1. Although the Stop stimuli induced moreerrors than did the NoStop stimuli, participants made very
few errors overall.
RTs for the 5 categories of NoStop stimulus were averaged
for each participant and submitted to a one-way analysis ofvariance (ANOVA), with Stop stimulus similarity level as theindependent variable (low-, medium-, and high-similarity). A
significant effect of similarity was obtained, F (2, 62) =11.90, p<.01. A Tukey’s HSD test revealed that RTs wereshortest in the low-similarity condition, followed by themedium-similarity condition and then the high-similarity
condition, HSD (3, 62) = 31.68, p<.001.
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Aki AKAMINE and Mitsuro KIDA

Table 1: Mean Error Rates (%) and Reaction Times (ms)Stop stimuli

NoStop stimuli
NeutralpeopleNegative
Electronics
peopleFlowers

Landscapes

M

Error rate
Low-similarity condition(Geometric shapes)
3.37
2.60
Medium-similarity condition(Cars)
M
5.27
SD
3.70
High-similarity condition(Animals)
M
3.08
SD
2.18
Reaction time
Low-similarity condition
M—
SD—
Medium-similarity condition
M—
SD—
High-similarity condition
M
—
SD
—
M
SD

0.20
0.72

0.12
0.39

0.04
0.18

0.08
0.35

0.20
0.51

0.13
0.34

0.19
0.89

0.13
0.48

0.13
0.60

0.08
0.32

0.13
0.48

0.13
0.51

0.13
0.44

0.13
0.30

0.13
0.30

0.13
0.30

0.06
0.22

0.12
0.21

362.2
48.7

363.8
48.1

389.9
54.3

370.5
53.2

376.8
50.7

372.6
49.7

384.9
36.2

406.5
38.6

452.0
33.2

390.7
41.8

406.1
41.1

408.0
35.1

469.0
102.3

467.7
95.7

473.3
94.5

466.8
89.3

487.6
107.3

472.9
96.2

ERP Data
P3. Figure 1 shows grand-mean waveforms for the Stop
stimuli. The early components (N1, P2 and N2) show afront-central distribution. These were followed by anextremely large positive deflection (P3) that appeared after
300 ms, with a central-parietal distribution. The P3component was designated as the largest positive deflection,
peaking between 300 and 630 ms after the N1–P2–N2
complex. The peak latency and baseline-to-peak amplitudeof P3 were measured for each averaged ERP. The data at
Oz had to be excluded from analysis due to the indistinct
waveforms obtained from many of the participants;
analyses were performed only on data collected from Fz,
Cz, and Pz. These data are shown in Table 2.
P3 peak latency data were submitted to a two-way
ANOVA, with Stop stimulus similarity (low-, medium-, andhigh-similarity) and site (Fz, Cz, and Pz) as independent
variables. Both main effects of Stop stimulus and site weresignificant, F (2, 62) = 29.17, p<.001; F (2, 124) = 4.48,
p<.05, respectively. The two-way interaction was not
significant. A Tukey’s HSD test revealed that P3 latencies
were significantly different across all conditions, HSD (3,62) = 30.25, p<.05. Latencies were shortest in the
low-similarity condition, followed by the middle-similarity
condition and then finally the high-similarity condition. In
addition, P3 latencies at Fz were significantly longer thanFigure 1: Grand mean ERPs elicited by Stop stimuli

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Perceptual Similarity between Pictures Modulates ERPs during a Stop/NoStop Task

Table 2: Mean latencies and amplitudes of late P3 for the Stop stimuli
Amplitude (μV)

Latency (ms)
Fz

Cz

Pz

Fz

Cz

Pz

M
SD

434.1
47.9

420.9
39.6

421.3
40.4

12.72
4.60

17.54
6.66

16.16
6.24

M
SD

485.9
45.5

463.8
40.0

458.8
49.9

9.78
5.43

16.89
8.13

16.11
6.46

M
SD

532.0
40.9

527.8
41.0

530.6
46.2

14.31
7.34

17.91
8.18

16.38
6.63

Low-similarity condition

Medium-similarity condition

High-similarity condition

they were at Cz and Pz, HSD (3, 62) = 12.49, p<.05. There
was no latency difference between Cz and Pz.
The same two-way ANOVA was also performed on theP3 peak amplitude data. The main effect of site wassignificant, F (2,124) = 53.38, p<.001, whereas the main
effect of Stop stimulus similarity was not significant. A
significant Stop stimulus similarity x Site interaction was
obtained, F (4, 124) = 3.66, p<.01. However, while thesimple main effects of Stop stimulus similarity were notsignificant at each electrode site, the simple main effects ofsite were significant at each level of Stop stimulus
similarity. A Tukey’s HSD test revealed that P3 amplitudes
were significantly larger at Fz than at Cz and Pz, HSD (3,124) = 2.15, p<.05; however, in the high-similarity
condition, Fz < Pz, p<.10. No significant amplitudedifferences between Cz and Pz were found.
P2 and N2. The baseline-to-peak amplitudes of the P2
and N2 components were measured at Cz, within ranges of120–220 and 180–300 ms, respectively. Participants’ data
were removed from further analysis if no clear P2 and/or
N2 peaks could be observed on their ERP waveforms. The
following analyses were performed on the data of 56
participants: 17 in the low-similarity condition, 26 in themedium- similarity condition, and 13 participants in thehigh-similarity condition. Table 3 presents the amplitudesof the P2 and N2 components at the Cz site. These were
submitted separately to one-way ANOVAs with Stop
stimulus similarity as the independent variable.
The analysis of the P2 amplitude data showed asignificant effect of Stop stimulus similarity, F (2, 53) =3.41, p<.05. A Tukey’s HSD test showed that P2 amplitudes
were significantly larger in the high-similarity condition
than in both the low- and medium-similarity conditions.
There were no differences between the low-similarity andmedium-similarity conditions, HSD (3, 53) = 1.88, p<.05.
Finally, the N2 amplitude data also showed a significant
effect of Stop stimulus similarity, F (2, 53) = 4.55, p<.05.
N2 amplitudes were significantly larger in thehigh-similarity condition than in the low- and medium
similarity conditions, but there were no significant
differences between the low- and medium similarity
conditions, HSD (3, 53) = 2.49, p<.01.

Discussion
In the present study, the largest positive peaks elicited by
the Stop stimuli, with a latency range of 300–600 ms after
stimulus onset, were examined. The components were
distributed at the central-parietal site. Akamine and Kida
(2006) demonstrated that this positive deflection isequivalent to late P3. The late P3 is also similar to the
NoGo P3 that is associated with response inhibition (e.g.,
Jodo & Inoue, 1990). A terraced positive wave was seen in
the medium and high-similarity conditions studied here,around 300 ms after stimulus onset at the parietal site.
These components would be equivalent to P3b (or early
P3). P3 yielded by Stop stimuli would consist of at least
two distinct components. In contrast, a remarkably large
single positive peak could be seen in the low-similarity
condition. It is possible that Stop stimuli in the
low-similarity condition would also elicit the two types of
positive components with a latency range of 300–600 ms

Table 3: Mean amplitudes of P2 and N2 at Cz for the Stop stimuli
P2

N2

M
SD

0.96
4.31

–3.59
4.27

M
SD

2.43
4.20

–3.51
3.19

M
SD

4.78
2.93

–7.50
5.53

Low-similarity condition

Medium-similarity condition

High-similarity condition

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Aki AKAMINE and Mitsuro KIDA

after stimulus onset. The two components occurred very
closely together in temporal space. As a result, they might
have overlapped strongly and ultimately merged into asingle large compound component (Falkenstein,
Koshlykova, Kiroj, Hoormann & Hohnbain, 1995).
RTs for NoStop stimuli increased as a function of
stimulus similarity. In addition, the latency of the late P3
significantly increased along with stimulus similarity, but
amplitude did not change in a similar fashion. Thus,
difficulty in discriminating between stimuli would cause
not only a delay in reaction times to the NoStop stimuli, butalso a slowdown in the process of response inhibition to the
Stop stimuli. Although the putative connection betweenchanges in late P3 latency for Stop stimuli and RTs for
NoStop stimuli needs further examination, it is suggested
that processing of the stimuli to which a motor responsemust be withheld might have a reciprocal relationship to
response execution in a discriminative reaction time task.
Hasher and Zacks (1988) proposed an inhibition deficit
hypothesis, such that age-related impairments result from aweakening of inhibitory processes. Studies focused on these
inhibitory processes would be valuable for investigating
human information processing activities.
Both P2 and N2 were considerably larger in thehigh-similarity condition than in the low- and mediumsimilarity conditions. In the high-similarity condition, thepictures of animals’ faces were used as Stop stimuli, withcars and simple shapes serving as medium and low
similarity stimuli, respectively. Rockstroh, Elbert,
Birbaumer, & Lutzenberger (1982) reported that the
N100–P200 complex showed large amplitudes whenparticipants’ attention was shifted to the evoking stimulus.
It is assumed that the N100, and possibly the P200, reflect
the initial selection of an information source for further
processing. The present study suggests that facial images
are more likely to capture participants’ attention at an earlystage after stimulus onset.
Several studies have suggested that N2 for NoGo stimuli
is related to response inhibition (Eimer, 1993; Jodo &Kayama, 1992; Kok, 1986; Pffeerbaum et al., 1985). Other
studies have demonstrated that the negative deflection
around 250 ms after stimulus onset is enhanced in response
to pictures of persons’ faces (Akamine & Kida, 1998;
Watanabe, Okita, Konishi, & Imashioya, 1998). Pictures ofpeople yield larger N2 than pictures of cars, on both Go and
NoGo trials (Akamine & Kida, 2000). Thus, theenhancement of N2 in the high-similarity condition might
be closely related to the detection of faces (human or
animal), rather than response inhibition.

Notes１）We presented this study at the 72nd Annual Convention of
the Japanese Psychological Association in September 2008,
at Hokkaido University.
２）We thank Keita Kogura, a graduate of Aichi Gakukin
University, for his help with Experiments 1 and 2.
３）We presented the study, which examined the differences in
RTs and ERPs between NoStop negative and neutral
stimuli, at the 25th Annual Convention of the JapaneseSociety for Physiological Psychology and Psychophysiology
in July 2007, at Sapporo Medical University.
４）Thirty-one students at Aichi Gakuin University (22 womenand 9 men, M age = 21.8 years) participated in the study for
payment.
	  Akamine and Kida (2006) examined two subcomponentsof P3: Early P3 and late P3. The early P3 amplitude wasdesigned as the mean waveform amplitude during the
50–ms period between 290 and 340 ms. Late P3 amplitude
was designed as the mean waveform amplitude during the
50–ms period between 460 and 510 ms. In the present
study, ERP data obtained by Akamine and Kida (2006)
were re-analyzed using the same procedure used inExperiments 1 and 2.

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Final version received, January 15, 2009