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International Journal of Affective Engineering Vol.15 No.3 pp.213-222 (2016)
doi: 10. 5057/ijae.I JAE-D-15-0 0014
213
J-STAGE Advance Published Date: 2016.02.26
1. INTRODUCTION
The recent development of video game devices and
portable electronic devices (including mobile phones and
tablet devices) enables us to play video games at any time
and place. As a result, video game playing has become
one of the most popular entertainment activities in today’s
society. Although early studies have reported potential
negative effects associating with the abusive use of video
games [1-3], recent studies suggest that video game
playing may enhance perceptual and cognitive processes,
such as attention [4-9], memory [10-12], and speed of
information processing [13, 14] (see for reviews [15, 16]).
For example, Green and Bavelier [4] reported enhance-
ment of various aspects of visual attention by action-video
game playing. In their experiments, attentional capacity
and its spatial distribution and temporal resolution were
compared between habitual action video game players
(AVGPs) and non-video game players (NVGPs). They
found that the attentional capacity was larger, its distribu-
tion wider, and its temporal resolution higher in the
AVGPs than in the NVGPs. Green and Bavelier also
examined how training on an action-video game affected
attention in NVGPs. They found that the training (i.e., 1 hr
per day for 10 days) significantly enhanced all aspects of
the attention abilities mentioned above (see also [5, 6]).
Colzato et al. [10] extended the findings of Green
and Bavelier [4] and subsequent studies (e.g., [5-9]) by
examining the effects of action video game experience
on working memory. In their study, AVGPs and NVGPs
performed an n-back task in which they were required to
indicate whether each stimulus (i.e., letter) presented
sequentially matched the one that was presented n items
ago. Colzato et al. found that the AVGPs determined the
target more quickly and accurately than the NVGPs did,
suggesting that the capacity of working memory is larger
in AVGPs than in NVGPs. Blacker and Curby [11]
reported a higher capacity of working memory in the
AVGPs than in the NVGPs by using a visual working
memory task [17] in which multiple colored squares are
briefly presented and participants have to memorize them
and report the color for one of the squares.
Although many studies have reported the enhancement
of cognitive abilities by experience and/or training of
action video games, other investigators have reported
inconsistent findings [18-20] (see also [15]). For example,
Boot et al. [18] measured a wide range of cognitive
abilities, including attention, memory, and executive
control, for AVGPs and NVGPs. They also measured
those cognitive abilities for NVGPs with training on
an action-video game, a puzzle game, or a real-time
strategy game (for 20 hrs). Although they found higher
performance in cognitive tasks, such as visual working
memory and multiple object tracking tasks in the AVGPs
compared to the NVGPs, attentional capacity and its
spatial distribution and temporal resolution did not
differ between the two groups (see also [19]). There
was no difference in n-back task performance between
the two groups.
Received: 2015.02.19 / Accepted: 2016.01.28
ORIGINAL ARTICLE
Experience and Training of a First Person Shooter (FPS) Game Can
Enhance Useful Field of View, Working Memory, and Reaction Time
Yasuhiro SEYA and Hiroyuki SHINODA
Ritsumeikan University, 1-1-1, Noji-higashi, Kusatsu, Shiga 525-8577, Japan
Abstract: To examine the effects of experience and training of a first person shooter (FPS) game on cognitive abilities, we conducted
three experiments in which participants performed useful field of view (UFOV), visual working memory (VWM), and reaction time
(RT) tasks. In Experiment 1, we compared performance on the three cognitive tasks between FPS players and non-FPS players. In
Experiments 2 and 3, changes in task performance after 10-hr training or no training on the FPS game were examined. Experiment 1
showed that FPS players performed better than did non-FPS players on all cognitive tasks. Experiment 2 showed higher performance
on all cognitive tasks after the training compared with those before it. Experiment 3 showed no enhancement of performance on all
tasks. These results indicate that FPS game experience and/or training can enhance cognitive abilities at least for UFOV, VMW, and RT.
Keywords: Action video game, cognitive abilities, training effect
International Journal of Affective Engineering Vol.15 No.3
214
The reason for the discrepant findings is not clear.
Strobach et al. [21] speculated that the findings in Boot
et al. [18] may have been confounded by fatigue and/or
other carryover effects, because in Boot et al.’s study,
participants performed 12 tasks (see also [15]).
The present study was designed to obtain a better
understanding of the effects of action video game on
cognitive abilities, such as attention and working memory.
In the present study, we used a first person shooter (FPS)
game, a genre of action video game, which has been used
in many previous studies. A FPS is a gun shooting game
undertaken through a first-person perspective. Therefore,
through the limited visual field of the character being
manipulated, players must quickly and accurately search
visual information and select appropriate behaviors in
response to visual objects (e.g., enemies and items) and
events (e.g., attacks from enemies).
We focused on three cognitive tasks to measure the
spatial range of attention (i.e., useful field of view; UFOV),
visual working memory (VWM), and reaction time (RT).
As mentioned above, because of the limited visual field
and nature of the task required in FPS games, players
must search visual objects quickly and accurately, not
only in the central visual field, but also in the peripheral
field. In addition, players must frequently update
information in their working memory and, according
to that information, msut select appropriate behaviors
quickly and accurately. In the present study, we also
measured the game scores after the cognitive tasks.
In the present study, we conducted three experiments.
In Experiment 1, we examined the effects of the FPS
game experience by comparing the performance in the
cognitive tasks between habitual FPS game players and
non-FPS game players. In Experiment 2, we examined
the effects of FPS game training on the task performance.
In Experiment 3, we also conducted a control condition
in which non-FPS game players were asked to perform
the cognitive tasks without game training.
2. MXPERIMENT 1
2.1 Method
2.1.1 Participants
Twenty-nine individuals participated, 14 FPS players
(all males with a mean age of 21.5 in the range of 18-24)
and 15 non-FPS players (twelve males and three females
with a mean age of 22.0 in the range of 18-25). FPS
players reported playing FPS games such as Call of Duty,
Hallo, and Battle Field series, more than 4 hrs/week
(mean of 6.4 hrs/week in the range of 4-16 hrs/week), and
non-FPS players reported no experience with FPS games
or had not played for over a year. Note that all of the FPS
players also reported playing various genres of action
video games, including sports, car racing, fighting,
and shooting games (third-person perspective). All the
participants gave informed consent to participate in the
experiment. They had normal or corrected-to-normal
vision.
2.1.2 Apparatus
In the cognitive tasks, a personal computer (Apple Mac
Pro Early 2009) was used to control the experiment
and generate stimuli used. All stimuli were presented on
a 22-inch color CRT monitor (refresh rate at 100 Hz) at
a viewing distance of 57 cm. The experimental program
was written with MATLAB with Psychophysics Toolbox
extensions [22, 23]. In the game task, the video game was
played on the Playstation 3 (Sony Computer Entertainment
Inc., Japan) with the accompanying controller, connected
to a 20-inch color LCD monitor (refresh rate at 60 Hz).
We used the commercially available FPS game “Call of
Duty: Modern Warfare 3” (ActiVision Inc., U.S.A.).
2.1.3 Stimuli
Figure 1 is an illustration of the tasks used in the present
study. A UFOV task used in the present study was quite
similar to that used in previous UFOV studies [24-26]
(see Figure 1A). In the display subtending 40º (W) × 30º (H),
a fixation stimulus, circular frames, a central target, a
peripheral target, and masks were presented in white on
a grey background (luminance 29.6 cd/m2). The fixation
stimulus (figure 8) subtended 0.8° × 1.0° and was presented
in the center of the display. Each frame (luminance
54.5 cd/m2) subtended 1.2° in diameter. The frames were
aligned at 4º, 12º, and 20º in the periphery from the center
of the display along four imaginary radial spokes. The
central target was a single letter (luminance 54.5 cd/m2)
subtending 0.8º × 1.0º. The central target was one of
four characters (E, F, H, or L) presented at the center
of the display. The peripheral target was a single
spot subtending 1.0° in diameter. The peripheral target
(luminance 33.2 cd/m2) was presented inside one of the
frames. The masks were filled circles (luminance 54.5 cd/m2)
with a 4 × 4 diagonal cross line pattern, subtending 1.2º in
diameter. They were presented at all frame locations as
well as the central target location.
A modified version of the VWM task described by Luck
and Vogel [17] (see also [11, 12]) was used (Figure 1B).
In the display, a fixation cross, a sample array, and a test
stimulus were presented on a grey region (luminance
42.2 cd/m2) subtending 9.88º × 7.38º, outside of this was
black (luminance 0.56 cd/m2). The fixation cross was
Experience and Training of a First Person Shooter (FPS) Game Ca n Enhance Useful Field of View, Working Memory, and Reaction Time
International Journal of Affective Engineering Vol.15 No.3
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black and subtended 2º × 2º. The fixation cross appeared
in the center of the display through a trial. The sample
array contained 2, 4, 6, or 8 colored squares (1.6º × 1.6º).
The color of each square was randomly chosen from a set
of nine clearly discriminable colors, i.e., red (luminance
15.2 cd/m2), brown (luminance 4.52 cd/m2), blue (luminance
7.24 cd/m2), cyan (luminance 55.2 cd/m2), violet (luminance
6.46 cd/m2), green (luminance 48.4 cd/m2), yellow (luminance
63.1 cd/m2), black (luminance 0.56 cd/m2), and white
(luminance 69.9 cd/m2), and each color appeared only
once in an array. The positions of the squares were
randomized for each trial, and the samples in a given array
were separated by at least 2.0º (center to center). The test
stimulus was presented at one of the square positions
presented on the sample array. The test stimulus was
divided into two colored rectangles; one rectangle was
the same color as the sample square that had been
presented at that position, and the other was a color that
was different.
In the RT task (Figure 1C), a white fixation cross and
a target (luminance 69.6 cd/m2) were presented in the
center of the gray background (luminance 42.2 cd/m2).
The fixation cross subtended 2º × 2º. The target was filled
circle subtending 2° in diameter.
2.1.4 Procedure
In the experiment, there were two sessions; one was a
cognitive task session, and the other one was a game task
session. We conducted the cognitive task session first,
followed by the game task session. In the cognitive task
session, the three tasks were conducted in a dark booth.
Each participant sat on a chair with his or her head fixed by
a chin rest while viewing the display binocularly. The order
of the three cognitive tasks was randomized across the
participants. Before the main experiment, the participants
practiced the tasks until they were familiar with them, after
which the main session began. The duration of the three
cognitive tasks was less than 1 hour. In all tasks, participants
could take rest periods whenever they felt fatigued.
In the UFOV task, at the beginning of each trial, the word
“Ready” was presented in the upper middle of the display
until the participant pressed the space key to begin a trial.
After pressing the key, the central fixation stimulus and the
circular frames were presented for 1 s. The display was
then replaced by the central and peripheral target display
for 100 ms and the masks were then presented for 1 s.
Following the offset of the masks, four possible central
targets and frames were presented until the participants
responded by pressing one of four labeled keys on a
Figure 1: Examples of (A) UFOV task, (B) VWM task, and (C) RT task used in the present study
International Journal of Affective Engineering Vol.15 No.3
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keyboard. The frames for the four possible locations were
then presented with each radial spoke labeled “1,” “2,” “3,”
or “4” until the participants responded by pressing one of
four labeled keys on the keyboard. The participant’s task
was to identify the central target (central task) while local-
izing the peripheral target (peripheral task). After each trial,
auditory feedback for the central task alone was provided.
There were two blocks of 72 trials. The central target and
frame at which the peripheral target was presented were
chosen randomly across trials with an equal number of
occurrences. The proportion correct responses (PCRs) for
each central and peripheral task were calculated.
In the VWM task, at the beginning of each trial, the word
“Ready” was presented in the upper middle of the display
until participants pressed the space key to begin a trial.
After the key press, the central fixation cross was presented
for 1 s. The display was then replaced by the sample array
for 100 ms and a blank display was then presented. Two
seconds after the onset of blank display, the test stimulus
was presented. The test stimulus disappeared if one of the
two labeled keys on the keyboard was pressed or 2 seconds
elapsed. The participant’s task was to memory the colors
and positions of the squares and to report which color from
the test stimulus was the same as the square that had been
presented in that position. There were 200 trials. The item
set size (2, 4, 6, or 8) was chosen randomly across trials
with an equal number of occurrences. Again, the propor-
tion correct response (PCR) was calculated.
In the RT task, at the beginning of each trial, the word
“Ready” was presented in the upper middle of the display
until participants pressed the space key to begin a trial.
After the key press, the central fixation cross was presented
for 1 s and the cross was replaced by the target to be
responded until a labeled key was pressed or 1 s elapsed.
The participant’s task was to respond to the onset of the
target, as soon as possible. There were 100 trials. In 20%
of the total trial, no target was presented (i.e., catch trial)
for participants to prevent an anticipatory response.
The man RT and false alarm rate were calculated.
In the game task session, the task was conducted under
a standard illumination. Participants sat on a chair and no
apparatus was used to fix their head position relative to the
video game monitor. The participant’s task was to play the
FPS game. Because most FPS players reported that they
could play the game for 30 min or longer per play, the
participants were asked not to buy weapons or armors
during the game and each trial was terminated when the
“GAME OVER” message was displayed or 10 min after
the start of the game. There were three trials. The mean
game score was calculated.
2.2 Results
Figure 2 shows the results of Experiment 1. As seen in
the figure, for all cognitive tasks and game task, the
performances were higher for the FPS players than for the
non-FPS players. Figure 2A shows the mean PCRs in the
peripheral tasks. As seen in the figure, PCRs were clearly
higher in the FPS players than in the non-FPS players in
the peripheral task. In both groups, PCRs decreased with
increasing eccentricity. The peripheral task performance
data were entered into a 2 (group) × 3 (eccentricity)
Figure 2: Results of Experiment 1. (A) PCRs in the peripheral
task of UFOV task, (B) PCRs in the VWM task,
(C) RTs in the RT task, and (D) game score in
the game task. Vertical bars indicate SE.
Experience and Training of a First Person Shooter (FPS) Game Ca n Enhance Useful Field of View, Working Memory, and Reaction Time
International Journal of Affective Engineering Vol.15 No.3
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ANOVA, which showed significant main effects of
both group, F (1, 27) = 6.28, p < .05, and eccentricity,
F (2, 54) = 70.12, p < .01. An interaction between group
and eccentricity was just above the significance, F (2, 54)
= 2.94, p = .062. A post-hoc comparison by Tukey’s HSD
method showed significantly lower PCRs at the 20-deg
eccentricity compared to the other eccentricities (both
ps < .05). Concerning the central task performance, a t test
revealed no significant difference between the FPS players
(mean = 97.12) and the non-FPS players (mean = 95.14).
Figure 2B shows the mean PCRs in the VWM task. As
seen in the figure, PCRs were higher in the FPS players
than in the non-FPS players. A 2 (group) × 4 (set size)
ANOVA showed significant main effects of both group,
F (1, 27) = 5.15, p < .05, and set size, F (3, 81) = 149.18, p < .01.
There was no interaction between them. A post-hoc
comparison showed significant differences in PCRs
between any pair of set size conditions (all ps < .05).
Figure 2C shows the mean RTs. The RT was shorter in
the FPS players than in the non-FPS players. The t test
result showed that the RT difference between the two
groups was just above the significance, t (27) = 2.05, p = .0504.
Concerning the error rate (i.e., false alarm rate), there
was no significant difference between the FPS players
(mean = 0.03) and non-FPS players (mean = 0.04).
Figure 2D shows the mean game scores in the FPS and
non-FPS players. A t test revealed significantly higher
scores in the FPS players compared to the non-FPS
players, t (27) = 11.37, p < .01. We also conducted addi-
tional analyses of the correlations between the game score
and each of the three cognitive task performances. Note
that the PCRs to the peripheral target of the UFOV task
and those in the VWM task were averaged across the
conditions of eccentricity and set size, respectively; the
averaged data were used for the correlational analyses.
Results showed significantly positive correlations with
performance in UFOV, r (27) = 0.53, p < .05, and VWM
tasks, r (27) = 0.38, p < .05, while the correlation was not
significant with performance in the RT task.
2.3 Discussion
In this experiment, we measured performance in the
UFOV, VWM, and RT tasks for FPS players and non-FPS
players; we found that FPS players had higher performance
in all tasks compared to the non-FPS players. This finding
is consistent with the findings of previous studies that
examined attentional abilities [4-6], working memory
[10-12], and speed of information processing [13, 14]. As
mentioned in the Introduction, there are discrepant findings
from studies examining the effects of action video game on
attention and memory [18-20]. The present study provides
positive evidence for the literature.
As argued by Strobach et al. [21], the studies reporting
negative findings [18-20] might have been confounded by
fatigue and other carryover effects. The present study
minimized these possibilities (short task duration and
only a few tasks were required). Therefore, the present
study would have revealed the clear differences between
the groups.
It should be noted that in the present study’s UFOV
task, the PCR to the central target in the FPS players was
not different from those in the non-FPS players. This is
inconsistent with the findings of Green and Bavelier’s [5]
findings which showed that FPS players had significantly
higher performance for the central target of the UFOV
task than did the non-FPS players. One possible reason for
this discrepancy is the methodological differences between
the present experiment and Green and Bavelier’s experi-
ment. In their experiment, to equalize the non-purposeful
effect (i.e., eccentricity) the stimulus presentation duration
was varied depending on the eccentricities. Consequently,
the higher central task performance may have reflected
not only the accuracy of information processing, but also
its speed, resulting in the differences between the two
groups. The present study used a UFOV task with no
manipulation of the presentation duration (e.g., [26]).
Therefore, the central task performance may have been
independent for the speed of information processing.
Note that in the present study’s RT task, the target was
presented in the center of the display and RT to it were
faster in the FPS players than in the non-FPS players. This
result may partially support the findings of the higher
central task performance in Green and Bavelier.
The results of the correlation analyses showed that the
performance in the UFOV and VWM task were signifi-
cantly related to the game score. This result strengthens
the view that the experience of the FPS game can enhance
cognitive abilities such as attention [4-6] and working
memory [10-12].
3. EXPERIMENT 2
3.1 Method
The apparatus and stimuli used in Experiment 2 were
identical to those used in Experiment 1. Participants were
8 individuals who had participated in Experiment 1 as
non-FPS players. In the experiment, they received 10-h
training (e.g., [4, 8]) on the FPS game used in Experiment 1
(i.e., Call of Duty). During the training period, participants
were asked to play the game in our laboratory for 1-3 hr
International Journal of Affective Engineering Vol.15 No.3
218
per day. The 10-hr training was completed over 4 or 5
days in 2 weeks (after participating in Experiment 1).
After the training period, they performed the cognitive
tasks and game task mentioned in Experiment 1.
3.2 Results and Discussion
Figure 3 shows the performance of the cognitive tasks
and game task in Experiment 2, as well as Experiment 1
(pre-training). As seen in the figure, performance in all
the cognitive tasks and game task became higher after
the 10-hr training. In the UFOV task (Figure 3A), the
peripheral task performance data were entered into a
2 (training period) × 3 (eccentricity) two-way ANOVA,
which showed significant main effects of both training
period, F (1, 7) = 6.36, p < .05, and eccentricity, F (2, 14) =
28.86, p < .01. An interaction between training period
and eccentricity was significant, F (2, 14) = 8.42, p < .01.
A post-hoc comparison showed significantly lower PCRs at
the 20-deg eccentricity compared to the other eccentricities
(both ps < .05). Subsequent analyses of the interaction
showed a significant simple main effect of training period at
the 12-, F (1, 21) = 7.37, p < .05, and 20-deg eccentricities,
F (1, 21) = 11.51, p < .01. On the central task performance,
there was no significant difference in the central task
performance between the two periods (the mean PCR was
93.48 and 93.58 in the pre and post periods, respectively).
In the VWM task (Figure 3B), a 2 (training period) ×
4 (set size) two-way ANOVA showed significant main
effects of both training period, F (1, 7) = 19.88, p < .01,
and set size, F (3, 21) = 89.74, p < .01. There was no inter-
action. A post-hoc comparison showed significant
differences in PCRs between any pair of set size condi-
tions (all ps < .05).
In the RT task (Figure 3C), the t test results showed a
significant difference between the two periods, t (7) = 2.85,
p < .05. However, the difference in the error rate was not
significant (the mean error rate was 0.03 and 0.04 in the
pre and post periods respectively). In the game score
(Figure 3D), the result of the t test showed a significantly
higher game score in the post training, t (7) = 7.31, p < .01.
The results of Experiment 2 are consistent with those
of Experiment 1 and previous studies examining effects of
game training on attention [4-6], working memory [10-12],
and speed of information processing [13, 14]. This suggests
that the FPS game training, as well as the FPS game expe-
rience, can enhance the spatial distribution of attention.
This experiment also showed no difference in the PCRs
to the central target in the UFOV task between the training
periods, which is consistent with the results in Experiment
1 but not with the findings of Green and Bavelier [5].
As mentioned in Experiment 1, this discrepancy can be
explained by the methodological differences between the
present experiments and their experiment.
4. EXPERIMENT 3
4.1 Method
The apparatus and stimuli used in Experiment 3 were
identical to those used in Experiment 1. Participants were
7 individuals who had participated in Experiment 1 as
non-FPS players, but who had not participated in
Figure 3: Results of Experiment 2. (A) PCRs in the peripheral
task of UFOV task, (B) PCRs in the VWM task,
(C) RTs in the RT task, and (D) game score in
the game task. Vertical bars indicate SE.
Experience and Training of a First Person Shooter (FPS) Game Ca n Enhance Useful Field of View, Working Memory, and Reaction Time
International Journal of Affective Engineering Vol.15 No.3
219
Experiment 2. In the experiment, they received no training
on the FPS game. Two weeks after Experiment 1, they
came to our laboratory and performed the cognitive tasks
and game task.
4.2 Results and Discussion
Figure 4 shows the performance of the cognitive tasks
and game task in Experiment 3, as well as Experiment 1
(pre-test). As seen in the figure, no enhancement of
performance in any of the cognitive tasks or game task
was found. In the UFOV task (Figure 4A), a two-way
(task repetition × eccentricity) ANOVA showed only a
significant main effect of eccentricity, F (2, 12) = 15.41,
p < .01, but the main effect of repetition and interaction
were not significant. A post-hoc comparison showed
significantly lower PCRs at the 20-deg eccentricity than
at the other eccentricities (both ps < .05). Note that the
difference in the central task performance between the
2 periods was not significant (the mean PCR was 97.22
and 96.53 in the pre and post periods, respectively).
In the VWM task (Figure 4B), a two-way (task repetition
× set size) ANOVA showed only a significant main effect
of set size, F (3, 18) = 82.47, p < .01, but the main effect
of task repetition and interaction were not significant.
A post-hoc comparison showed significant differences in
PCRs between any pair of set sizes (all ps < .05) except
between the 6 and 8 set sizes.
In the RT task (Figure 4C), the t test showed no signifi-
cant difference in the RT between the two periods. There
was no significant difference between the two in the error
rate (the mean error rate was 0.04 and 0.00 in the pre and
post periods, respectively). In the game score (Figure 4D),
the result of the t test showed no significant difference
between the two periods.
The results of Experiment 3 showed no enhancement
in the performance of the cognitive tasks, suggesting
that the repetition of the cognitive tasks cannot account
for the enhancement of the cognitive tasks reported
in Experiment 2. Because the patterns of the results
(i.e., the dependency of the PCRs on the eccentricity
in the UFOV and on the set size in the VWM task)
was quite similar between Experiments 2 and 3, it is
unlikely that the participants in this experiment adopted
different strategies from those used by the participants in
Experiment 2.
5. GENERAL DISCUSSION
The present study examined the effects of FPS game
experience (Experiment 1) and training (Experiments 2
and 3) on cognitive abilities using UFOV, VWM, and RT
tasks. The results of Experiment 1 clearly showed higher
performance on the cognitive tasks in the FPS game players
than in the non-FPS game players. This suggests that the
FPS game experience enhances the spatial distribution of
attention, capacity of working memory, and information
processing speed. Experiment 2 showed that the 10-hr
training of the game in the non-FPS game players
enhanced performance of the cognitive tasks, while
Experiment 3 showed that the repetition of the cognitive
tasks did not enhance performance of the tasks. These
Figure 4: Results of Experiment 3. (A) PCRs in the peripheral
task of UFOV task, (B) PCRs in the VWM task,
(C) RTs in the RT task, and (D) game score in
the game task. Vertical bars indicate SE.
International Journal of Affective Engineering Vol.15 No.3
220
results suggest that the FPS game training can enhance
cognitive abilities. Taken together, the present results of
the three experiments clearly indicate that the experience
and the training (at least for 10 hrs) of FPS game can
enhance attention [4-9], working memory [10-12], and
information processing [13, 14]. Considering that work-
ing memory is well known to be related to attention [27],
the FPS game would be useful, at least some degrees, for
enhancing attention-related cognitive abilities.
As discussed in the Introduction, several studies have
reported mixed results for the effects of video game
experience or training on cognitive abilities [18-20].
This is inconsistent with the present results of
Experiments 1 and 2. This discrepancy could be due to
carryover effects, namely, experience with and repetitions
of cognitive tasks. As we mentioned earlier, Boot et al. [18]
used 12 cognitive tasks. In Ravenzwaaij et al. [20],
participants played video games on five separate days.
Before each game session and following the last session,
they performed a visual discrimination task. It is, therefore,
possible that experience with various cognitive tasks and
repetitions of a task enhanced cognitive task performance
and concealed the effects of video games on cognitive
abilities. Indeed, these studies showed that task perfor-
mance was enhanced in the no-training group, unlike in
the case of Experiment 3 of the present study. In order to
reveal the effects of video games on cognitive abilities,
it would be necessary to limit the number of tasks and
the repetitions of the tasks.
One may argue that the difference in the cognitive tasks
would reflect the changes in cognitive strategies, not the
enhancement of cognitive abilities. For example, Nelson
and Strachan [28] reported that 1 hr playing for the video
game affected speed-accuracy tradeoff of players to both
localization and shape-matching tasks, depending on
game genres used. In their study, participants performed
the two cognitive tasks before and after the 1 hr video
game playing. Two types of video games were used:
a FPS and a puzzle game. Their results showed that
participants’ responses became faster but less accurate in
both tasks after the FPS game playing than before the
playing. After the puzzle game playing, participants’
responses became slower but more accurate than before
the playing. According to the explanation by the influence
of game play on a tradeoff strategy, it would be expected
that the FPS players and the non-FPS players after the
FPS game training traded off their response accuracy for
faster responses. However, the results of RT task in
Experiments 1 and 2 showed faster RT in the FPS players
than in the non-FPS players (Experiment 1) and after the
training period than before the period (Experiment 2) with
no change in error rate (false alarm rate). In addition, the
results of UFOV and VWM tasks in Experiments 1 and 2
also showed higher accuracy of responses (i.e. PCRs)
in those tasks in the FPS players than in the non-FPS
players (Experiment 1) and after the training than before
the training (Experiment 2). Taken together, it is unlikely
that the present findings can be accounted by the speed-
accuracy tradeoff. Note that in the UFOV task, we found
no change in the PCR to the central target between the
FPS and non-FPS players (Experiment 1) and between the
training periods (Experiment 2). Therefore, it is unlikely
that the peripheral task performance was traded off with
central task performance.
The present study did not examine the effects of other
types of video games such as puzzle games. Therefore, it
is not clear whether the effects of video games observed
here are specific to FPS games. We speculate that other
types of video games would be able to enhance the cogni-
tive abilities measured in the present study if the games
require players to quickly and accurately perceive relevant
information, as in a FPS game. Seya and Watanabe [29]
measured UFOV in game playing situations. In their
study, the peripheral visual field was restricted to an area
around the gaze by a window mask, while participants
played one of three video games, namely, car racing,
falling puzzle, and word puzzle games. They found that in
the word puzzle game, game score did not change with the
mask; however, in the other games, game score decreased
as the mask size increased. This suggests that UFOV is
essential for playing video games wherein the opponents
impose severe spatial and temporal constrains on players
(see also [30]). Boot et al. [18] and Ravenzwaaij et al. [20]
reported that players’ cognitive abilities were enhanced
irrespective of the type of game used for training.
However, their findings may have been confounded by
other factors as we discussed above.
It should be noted that our findings do not imply that
FPS game playing results in the enhancement of general
cognitive abilities required for various situations such as
driving and sports. Sports vision research has provided
evidence supporting this view. Mori et al. [31] measured
simple and choice RTs in karate athletes and novices.
They reported faster RTs in the athletes than in the
novices when the tasks consisted of videotaped scenes
of the opponent’s attack; however, when simple stimuli
were used, the difference was slight. This suggests that
training in a specific sport enhances the cognitive abilities
required for that sport or for tasks closely related to it
(see also [32]). A similar argument may be applicable to
Experience and Training of a First Person Shooter (FPS) Game Ca n Enhance Useful Field of View, Working Memory, and Reaction Time
International Journal of Affective Engineering Vol.15 No.3
221
the effects of FPS game experience and training. Further
investigation is needed to explore this point.
In conclusion, the present study provides positive
evidence regarding the effects of FPS game experience
and training on UFOV, VWM, and RT. The results suggest
that the number of tasks employed and the repetitions of
the tasks should be limited in order to eliminate potential
carryover effects. However, we believe that the effects of
video game should be examined by using multiple tasks,
in order to examine whether the enhancement of task
performance reflects cognitive strategies, such as a speed-
accuracy tradeoff.
ACKNOWLEDGEMENTS
This work was supported by a Grant-in-Aid for Young
Scientists (B) 25870916 to Y. S. We would like to thank
Junya Tagawa for his assistance of conducting the experi-
ments.
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Yasuhiro SEYA (Member)
Yasuhiro Seya is Assistant Professor of Department of Human and
Computer Intelligence, Ritsumeikan University, Japan. He received his
PhD in Kinesiology from Tokyo Metropolitan University in 2007. His
research interests are visual attention, eye movements, and self-motion
perception.
Hiroyuki SHINODA (Member)
Hiroyuki Shinoda is Professor of Department of Human and Computer
Intelligence, Ritsumeikan University, Japan. He received his PhD in
Architecture from Kyoto University in 1995. His interests are color
vision, elderly vision, and applications of visual science.
