Effects of Visual Working Memory on Brain Information
Processing of Irrelevant Auditory Stimuli
Jiagui Qu1,2, Joshua D. Rizak2,3, Lun Zhao4, Minghong Li2*, Yuanye Ma2,5*
1 University of Science and Technology of China, Hefei, Anhui, P. R. China, 2 State Key Laboratory of Brain and Cognitive Science, Kunming Institute of Zoology, Chinese
Academy of Sciences, Kunming, Yunnan, P. R. China, 3 University of the Chinese Academy of Science, Beijing, P. R. China, 4 Psychological Research Center, Beijing Yiran
Sunny Technology Co. Lt, Beijing, P. R. China, 5 State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, P. R.
China
Abstract
Selective attention has traditionally been viewed as a sensory processing modulator that promotes cognitive processing
efficiency by favoring relevant stimuli while inhibiting irrelevant stimuli. However, the cross-modal processing of irrelevant
information during working memory (WM) has been rarely investigated. In this study, the modulation of irrelevant auditory
information by the brain during a visual WM task was investigated. The N100 auditory evoked potential (N100-AEP)
following an auditory click was used to evaluate the selective attention to auditory stimulus during WM processing and at
rest. N100-AEP amplitudes were found to be significantly affected in the left-prefrontal, mid-prefrontal, right-prefrontal, leftfrontal, and mid-frontal regions while performing a high WM load task. In contrast, no significant differences were found
between N100-AEP amplitudes in WM states and rest states under a low WM load task in all recorded brain regions.
Furthermore, no differences were found between the time latencies of N100-AEP troughs in WM states and rest states while
performing either the high or low WM load task. These findings suggested that the prefrontal cortex (PFC) may integrate
information from different sensory channels to protect perceptual integrity during cognitive processing.
Citation: Qu J, Rizak JD, Zhao L, Li M, Ma Y (2014) Effects of Visual Working Memory on Brain Information Processing of Irrelevant Auditory Stimuli. PLoS ONE 9(2):
e89989. doi:10.1371/journal.pone.0089989
Editor: Jan de Fockert, Goldsmiths, University of London, UK, United Kingdom
Received March 4, 2013; Accepted January 28, 2014; Published February 26, 2014
Copyright: ß 2014 Qu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was supported by 973 program (2012CB825500, 2011CB707800), NSFC (31271168, 91132307/H09, 31070965) and NSFC Finnish-Chinese
joint project 813111172. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: yuanma0716@vip.sina.com (YM); liminghong_jacky@sina.com (ML)
[11,12,13,14]. The activity of the PFC has been found to be
significantly increased during WM tasks [15]. Although much has
been learned from these studies, the majority of these studies were
concerned with the relationship of stimuli received within the same
sensory channel, and little is known about how or if the brain can
modulate irrelevant stimuli from different sensory sources, i.e.,
visual versus auditory systems, in a cross-modal manner. To
evaluate whether the PFC and/or other brain regions are able to
modulate irrelevant stimuli from different sensory channels in a
cross-modal manner, a delayed-response task (DRT) that involved
visual WM was employed along with an irrelevant auditory
stimulus. In this task, the auditory stimulus was applied to
determine whether the brain could maintain attention toward the
visual WM task while dampening and/or inhibiting the response
to the auditory stimulus. Electroencephalography (EEG) was used
to monitor brain activity during the visual WM task. In the EEG,
the amplitudes of auditory evoked potentials (AEP) are positively
related to the cognitive activities of brain regions [16,17,18]. The
AEP is composed of three main components (P50, N100, and
P200), which are known as the middle latency AEP. The N100AEP has been related to the trigger of attention [19,20] and was
used in the present study as an indicator of brain activity following
irrelevant auditory stimuli in a cross-modal system.
In this cognitive experiment, human subjects were asked to
perform a visual object WM task with either a low or high WM
load. An irrelevant auditory stimulus was presented in each
Introduction
Working memory (WM) and selective attention (SA) are two key
components of cognitive processing that are intimately related
[1,2,3]. WM is a specific type of short-term memory that enables
the brain to temporarily maintain specific information as well as
process this information to direct future behaviors [2]. Therefore,
WM is considered the basic neural mechanism required to
accomplish executive functions [1]. SA is a cognitive process that
filters incoming information to maintain ongoing cognition [3]. By
filtering incoming information, SA allows only relevant information into the short-term processing stores of WM [4,5]. This
important cognitive relationship allows an organism to focus
attention on external stimuli, tasks and challenges, maintain
necessary information temporarily and to make appropriate
behaviors according to the purpose or challenge. WM also has a
regulatory function on selective attention processes [5]. It has been
shown that a higher WM load in a visual WM task results in
greater interference from distractor faces on behavioral performance [6]. Likewise, distractor interference in an auditory task has
been found to increase significantly under high (vs. low) loads in a
concurrent WM task compared with that in an inconcurrent WM
task [7]. These results suggested that the regulation of selective
attention by WM depended on the level and type of the WM load.
The prefrontal cortex (PFC) is directly involved in the
modulation of irrelevant stimuli [8,9,10] and is the key brain
region utilized in WM and selective attention processes
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Visual WM on Processing of Irrelevant Stimuli
Materials and Methods
Table 1. The percentage of correct responses in the visual
WM tasks.
Ethics Statement
The research protocol of the study entitled ‘‘Effects of Visual
working memory load on brain information processing of
irrelevant auditory stimuli’’ has been reviewed and approved by
the internal review board of Kunming Institute of Zoology,
Chinese Academy of Sciences. Written informed consent has been
obtained from the participants and the data was analyzed
anonymously.
The percentage of correct responses (%)
Low WM load
97.33 (2.85)
High WM load
94.17 (7.62)
The percentage of correct responses is greater than 85% in both the low and
high WM load tasks. Data is shown as mean (SD).
doi:10.1371/journal.pone.0089989.t001
Participants
Participants were undergraduate and graduate students randomly selected from colleges and universities in Kunming, China.
The participants were between 19 and 27 years of age and the sex
ratio was 1 to 1. Participants were divided into 2 groups in order to
assess the effect of different WM loads. A total of 12 participants
were assigned to the low WM load task (6 men, 6 women, mean
age = 23); however, data from only 11 participants were analyzed
delayed phase between object presentation and object recognition
and in each inter-trial interval (ITI) phase. The N100-AEP was
recorded to monitor brain activity associated with the irrelevant
auditory stimulus in the following regions of interest (ROI): the
prefrontal, frontal, and temporal regions.
Figure 1. Mean N100-AEP amplitudes in rest states (white bars) and WM states (gray bars) following an irrelevant auditory
stimulus. A: N100-AEP amplitudes in low WM load task; B: N100-AEP amplitudes in High WM load task. L-PF: left-prefrontal; M-PF: mid-prefrontal; RPF: right-prefrontal; L-F: left-frontal; M-F: mid-frontal; R-F: right-frontal; L-T: left-temporal; R-T: right-temporal. Results are expressed as mean6SEM;
*P,0.05.
doi:10.1371/journal.pone.0089989.g001
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Visual WM on Processing of Irrelevant Stimuli
percentage of correct responses in the visual WM task was
required to be higher than 85%. No subjects were removed from
the study due to failure to meet this requirement.
Memory Task Description
The delayed-response task (DRT) is a classic paradigm used to
research the mechanisms of information maintenance and
processing in the brain [21]. The DRT is composed of four
phases: (1) target phase, in which target stimuli are presented to
the participants; (2) delayed phase, in which the target stimuli are
removed for delayed intervals of 3000–5000 ms; (3) probe phase,
in which probe stimuli are presented to the participants and the
participants are asked to identify whether the probe stimuli are the
same as the target stimuli; and (4) inter-trial interval (ITI) phase, in
which the participants are given a rest period of 5000–7000 ms
prior to being presented with a new four phase trial. This
paradigm is designed to evaluate information encoding, preservation, extraction, and recall.
Experiment Design
Experiments were conducted with two WM loads (low and high
visual WM load) because the accuracy of WM tasks with higher
loads was found to be lower than 85% in preliminary tests.
1. Low visual WM load task. At the beginning of each trial,
a rectangle and a fixation point were presented for 500 ms to alert
the participant to the task. Then, a black and white image of one
Caucasian face was presented as the target stimulus for 1500 ms
(target phase) with a visual angle of 3.5u horizontally and 5.5u
vertically. After that, a delayed phase was randomly selected with a
time interval between 3000,5000 ms. Then another face was
presented for 1000 ms and the participant was given 1000 ms
(probe phase) to make a judgment whether the face was the same
as the face presented in target phase. The image presented in the
probe phase was the same image presented in the target phase in
50% of the trials. The order of correct and incorrect image
pairings was randomized. After the judgment, there was a random
time interval of 5000,7000 ms (ITI phase) before the next trial
began. Each task contained 80 trials.
2. High visual WM load task. The high visual WM load
task was performed with the same procedure as the low visual WM
load task except that the visual object stimuli was a black and
white image that contained two parallel Caucasian faces. The
participant was asked to identify whether both of the faces
presented in probe phase were the same as the faces presented in
the target phase. Each task also contained 80 trials.
Figure 2. Overall average N100-AEP waveforms of the midfrontal region. A: Waveforms of the low WM load task; B: Waveforms
of the high WM load task. Solid lines represent the average N100-AEP
waveform in the WM state; dotted lines represent the average N100AEP waveform in the rest state.
doi:10.1371/journal.pone.0089989.g002
due to technical problems with the EEG apparatus during the
collection of 1 dataset. A total of 14 participants were assigned to
the high WM load task (7 men, 7 women, mean age = 24). All
participants were right-handed and had normal audition, normal
vision, no history of neurological disease or drug addiction. The
participants were asked to refrain from smoking and drinking tea,
coffee, or alcohol for 8 hours prior to the memory test.
First, the participants were requested to read the experimental
instructions and perform 5 test trials to become familiar with the
task. In the formal experiments, the participants were asked to
focus on a fixation rectangle and to ignore the sound clicks. The
Table 2. Time Latencies of the N100-AEP trough in each brain region in WM states and rest states in the low WM load tasks.
Brain Region
P values of Wilicoxon test
WM states (ms)
Rest states (ms)
L-PF
166.5(17.66)
163.37(20.96)
0.128
M-PF
165.09(18.35)
163.18(21.28)
1.000
R-PF
167.14(19.49)
163.23(21.63)
0.192
L-F
163.7(17.41)
160.42(20.14)
0.798
M-F
162.32(17.21)
162.18(20.34)
0.760
R-F
165.04(17.59)
163.57(21.35)
0.790
L-T
160.76(21.76)
157(22.03)
0.534
R-T
163.85(21.07)
156.64(25.61)
0.683
There were no statistically significant differences (P.0.05) in the N100-AEP latencies between WM states and rest states in the low load tasks. L-PF: left-prefrontal; M-PF:
mid-prefrontal; R-PF: right-prefrontal; L-F: left-frontal; M-F: mid-frontal; R-F: right-frontal; L-T: left-temporal; R-T: right-temporal. Data is shown as mean (SD).
doi:10.1371/journal.pone.0089989.t002
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Table 3. Time Latencies of the N100-AEP trough in each brain region in WM states and rest states in the high WM load tasks.
WM states/high WM load (ms)
Rest states/high WM load (ms)
P values of Wilicoxon test
150.93(14.97)
144.54(15.94)
0.090
150.93(16.18)
144.64(16.33)
0.100
150.82(14.92)
146.64(11.69)
0.073
149.31(11.65)
144.52(11.3)
0.100
149.25(13.76)
146.43(11.73)
0.126
150.93(14.79)
148.22(10.14)
0.100
149.55(11.39)
148.81(11.05)
0.109
152.29(14.86)
153.55(13.48)
0.109
There were no statistically significant differences (P.0.05) in the N100-AEP latencies between WM states and rest states in the high load tasks. L-PF: left-prefrontal; M-PF:
mid-prefrontal; R-PF: right-prefrontal; L-F: left-frontal; M-F: mid-frontal; R-F: right-frontal; L-T: left-temporal; R-T: right-temporal. Data is shown as mean (SD).
doi:10.1371/journal.pone.0089989.t003
In both memory tasks, an external loudspeaker presented one
irrelevant auditory stimulus at the midpoint of the delayed phase
(WM state) and ITI phase (rest state) of each trial. The auditory
stimuli were clicks compiled by Matlab from a series of sine waves
generated for 10 ms. The click frequency was 1000 Hz and the
click intensity was 85 dB.
Visual WM tasks were presented on a 17-inch computer screen
with a pure grey background, a resolution of 1024-by-768 pixels
and a refresh rate of 75 Hz. The distance between the eyes of the
participants and the screen was 57 cm. The test was performed in
a dark, sound-dampened room to eliminate any uncontrolled
external stimuli. The visual objects presented as stimuli (for both
the low and high WM load tasks) consisted of 150 black-and-white
photos of young Caucasian male and female faces and the sex ratio
of the faces was 1:1. The brightness and contrast of the photos
were constant with the background.
region (FT7, T7 and TP7), and right-temporal region (FT8, T8
and TP8), respectively. Each ROI consisted of the averaged value
of the pooled electrodes.
All data were then processed with the SPSS 17.0 software
package for statistical analysis. A repeated measures two-way
ANOVA for state (WM vs rest) and load (low vs high) was
performed for each ROI. The WM state and rest state N100-AEP
amplitudes for each region were then set as two levels of the
within-subject factor for the repeated measures one-way ANOVA.
Each WM group (low or high) were treated separately. The
latency data of the N100-AEP failed to meet the qualification
standards of a repeated measures one-way ANOVA. Therefore,
nonparametric statistics (Wilcoxon paired test) were applied to
identify within-group relationships for the latencies between the
WM state and the rest state. A statistically significant standard was
set at P,0.05 with a 95% confidence interval.
Data Recording and Analysis
Results
Raw EEG data were recorded and collected by a 64-leads
Neuroscan EEG workstation. The AC filter was set at
0.1,100 Hz and the data sampling rate was 1000 Hz. The
reference electrode was positioned on the apex of the nose and the
electric resistances of all electrodes were lower than 5 kV. Off-line
data were analyzed with the data analysis software ‘‘Scan 4.3’’ to
remove refused blocks and to reduce vertical ocular artifacts. The
epoch data consisted of data segments from 100 ms before the
triggers to 500 ms after the triggers. The data recorded at 100 ms
before the trigger was applied as a baseline to normalize the data.
The data was averaged by applying a low-pass filtering at 30 Hz
(12 db). Following this step, N100-AEP troughs were automatically detected by the Neuroscan software. The identification
standard of the N100-AEP was designated as the most significant
trough between 75 ms,175 ms and the latency of N100-AEP
components were defined by the trough apex. The amplitudes of
the N100-AEP were measured using the mean amplitudes from
10 ms before the trough to 10 ms after the trough according to the
overall average troughs [22]. This study focused on both the
changes of mean amplitudes and latencies of the N100-AEP.
According to the nearby electrode similarity principle, we
combined several ROIs into one ROI by pooling nearby
electrodes together. These pooled ROIs include the left-prefrontal
region (FP1 and AF3), mid-prefrontal region (FPZ), rightprefrontal region (FP2 and AF4), left-frontal region (F1, F3, F5,
F7, FC1, FC3 and FC5), mid- frontal region (FZ and FCZ), rightfrontal region (F2, F4, F6, F8, FC2, FC4 and FC6), left-temporal
Participants were evaluated with an EEG to measure the
amplitudes of the N100-AEP following an auditory click during
visual WM task. All participants complied with an accuracy
requirement to complete each task with a correct response rate
greater than 85% in both the low (97.33%) and high (94.17%) load
WM tasks (Table 1).
A repeated measures two-way ANOVA for state (WM vs rest)
and load (low vs high) revealed no interaction between state and
load in all ROIs [L-PF, M-PF, R-PF, L-F, M-F, R-F, L-T and R-T
(F(1, 23) = 0.008, 1.168, 0.250, 0.000, 0.002, 0.086, 0.083, 0.040),
P.0.05]. Whereas there was significant differences for N100-AEP
amplitudes between WM states and rest states in six ROIs [L-PF,
M-PF, R-PF, L-F, M-F and R-F (F(1, 23) = 6.846, 4.389, 10.544,
5.991, 6.505 and 5.599), P,0.05]. In the low WM load task
paradigm, a one-way ANOVA comparison of N100-AEP amplitudes in WM states (Delay Phase) and rest states (ITI Phase)
revealed no statistically significant differences in all ROIs [leftprefrontal, mid-prefrontal, right-prefrontal, left-frontal, mid-frontal, right-frontal, left-temporal and right-temporal (F(1, 10) = 1.557,
0.339, 4.025, 1.676, 1.808, 2.176, 0.617 and 0.035, P.0.05),
Figure 1A]. However, the one-way ANOVA comparisons of
N100-AEP amplitudes in the high WM load task were found to be
significantly affected during WM processing in 5 ROIs: the leftprefrontal, mid-prefrontal, right-prefrontal, left-frontal, and midfrontal [(F(1,13) = 11.563, 7.885, 7.505, 6.248 and 6.650, P,0.05,
Figure 1B]. It is noteworthy that the N100-AEP amplitudes in
WM states were higher (although not statistically significant) than
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Visual WM on Processing of Irrelevant Stimuli
study. Further research will be needed to clarify the role of WM
load on cross-modal sensory processing.
The PFC has been regarded as an integrator of information
from multiple sources. Pyramidal neurons in the PFC have the
largest number of dendritic spines [25], which suggests that
neurons in the PFC have the ability to integrate a large number of
excitatory inputs. The ability to integrate a large number of
excitatory inputs is very important for information integrating and
processing. Our results showing that the N100-AEP amplitudes
were affected in the visual WM tasks reflected integrated
information processing of both visual and auditory channels by
the PFC. This information processing mechanism might play an
important role for humans to adapt to new environments and
provide for better implementation of executive functions.
It is also noteworthy that the five brain regions (left-prefrontal,
mid-prefrontal, right-prefrontal, left-frontal, and mid-frontal) with
significant differences in the N100-AEP amplitudes overlap with
regions that are closely related to object recognition and WM
[12,26,27]. This suggested that the visual WM might participate in
the modulation of irrelevant auditory stimuli.
Taken together, our results suggest that the PFC may integrate
information from both visual and auditory channels and modulate
WM and selective attention in a cross-modal manner. Our
findings also indicated that the PFC might have to integrate as
much information as possible from all sensory channels prior to
performing executive functions in order to adapt to complex and
changing environments.
that in rest states in both low and high WM load tasks and that this
trend was witnessed in all recorded brain regions. The overall
average N100-AEP waveforms of the mid-frontal brain region for
both the low and high WM load tasks are displayed in Figure 2.
The time latency of the largest trough of the N100-AEP
following the auditory click was also evaluated. Application of
Wilcoxon paired test to the N100-AEP latencies of WM states and
rest states did not reveal any statistically significant difference (P.
0.05) in all ROIs in either the low or high WM load tasks (Table 2
and 3).
Discussion
Previous research has suggested that selective attention
processes in the PFC are able to inhibit irrelevant stimuli signals
during WM tasks [23,24]. However, these studies were performed
within the same sensory channel. In the present study, a delayedresponse task that involved visual WM and an irrelevant auditory
stimulus was employed to study the role of the PFC in processing
irrelevant stimuli from different sensory channels. Our results
suggested that the processing of irrelevant auditory stimuli was
affected during the visual WM task as the N100-AEP amplitudes
induced by the irrelevant stimulus were larger in WM states than
that in rest states. Furthermore, there were no differences in the
N100-AEP latencies in the WM and rest states, which suggested
that the visual and auditory stimuli might be processed in a parallel
manner. It seems that the load of the WM task might also play a
role in this process as comparison of N100-AEP amplitudes
between WM states and rest states found significant differences
only in the high load WM task, but not in the low load WM task.
However, there was no interaction between state and load found
in a two-way ANOVA, which makes the role of WM load
uncertain. As two different groups of participants were used in this
study to avoid a learning effect, the absence of an interaction
might be related to an uneven baseline between two separate
groups of participants. It is also possible that there was no
interaction between state and load under the conditions of our
Acknowledgments
The authors would like to thank Professor Min He for her technical
expertise regarding auditory evoked potentials, and Dr Jianhong Wang for
her valuable comments on the manuscript.
Author Contributions
Conceived and designed the experiments: YM ML JQ. Performed the
experiments: JQ ML. Analyzed the data: ML JQ LZ. Contributed
reagents/materials/analysis tools: YM. Wrote the paper: JQ ML JDR.
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