Go/No-Go Saccadic Reaction Times Towards
Visual Field Targets differ between athletes
and nonathletes
Nayla Sokhn, Antoine Wuilleret, Roberto Caldara
Eye and Brain Mapping Laboratory (iBMLab), Department of Psychology, University of Fribourg, Switzerland.
nayla.sokhn@unifr.ch

the visual reaction time and saccades [4]. Ando et al.
(2001) showed that athletes tend to answer faster to astimulus displayed in central as well as in peripheral
positions compared to nonathletes [5]. Similarly,
Muiños et al. (2014) showed that elites were faster
when stimuli were shown at the peripheral visual field[6]. Other studies have also reported differences
between elites and novice groups. A recent study
conducted by Wimshurst et al. (2016), revealed theexistence of dissimilarities in brain function activationof hockey players between an expert and a novice
group [7]. Similarly, Williams et al. (2008) showedthat elite athletes always perform better than novices
in their domain of expertise [8]. Altogether, thesestudies show the importance of vision in athlete sports
and that athletes outperforms nonathletes.

Abstract—We studied whether performance (CorrectHits, Correct Rejections) on saccadic reaction timediffers between ten professional hockey players and acontrol group of non-sportive young adults. We
implemented a task during which observers were asked
to make a movement towards a green dot with different
eccentricities (Go trial) or to inhibit when a red dot ispresented with same eccentricity (NoGo trial). First, ourdata showed no differences in the reaction time between
both groups. However, within the group of hockey
players, observers were faster for low eccentricity.
Second, while the control group achieved better
performance in the Correct Hit, Hockey players
performed significantly better in the Correct Rejections(CR), with both groups were below chance level for theCR rates.
Keywords- eye-movements;Correct Rejections;CorrectHits;reaction time;Go/NoGo task.

I.

Besides these differences between athletes andnonathletes, other studies have explored whether
vision can be trained and improved [9-10]. Appelbaum
et al. (2018) reviews the training techniques in sports
vision [11]. Wimshurst et al. (2012) showed thattwenty-one Olympic hockey players who were testedbefore and after a ten-week visual training program
presented significant improvements [12]. Alison et al.
(2015) explored whether a preseason vision training
program would improve visual skills and season
success in an ice hockey team [13]. Their results
indicate a positive influence of the training program on
the players’ visual skill. Similarly, Schwab et al.
(2012) aimed at investigating if a vision training
program would improve the performance’s vision ofyoung hockey players compared to a control groupwith no training. Results demonstrated significant
differences between both groups [14]. These findings
clearly show that vision can be trained and improved.

INTRODUCTION

Visual perception and attention are essential skills
for athletes. They are both influenced and affected byeach other. Athletes require excellent vision to
anticipate opponents’ movements [1] and to optimally
perform in their sports. Using a meta-analysis on
perceptual and visual aspects in different sports, Mannet al. (2007) found that these aspects are essential forperformance [2].
Vision in athletes’ sports has been excessively
explored in the literature. Williams et al. (1975)
investigated the differences between the vertical andhorizontal fields of vision between athletes andnonathletes. They found that both fields of vision are
higher for elites compared to the other group [3].
Another study explored the peripheral perception anddemonstrated that athletes were significantly faster to
respond compared to nonathletes when the target
appears in the peripheral field [1]. Using a clinicalbattery of vision tests Christenson et al. (1988)
revealed that athletes outperformed control groups in

One of the reliable tools to enhance vision andattention is the D2 Visuomotor Training Device (D2).
This tool is a light-training visuo-motor reaction timetraining device for high-performance athletics. It
consists of a board with sixty-four buttons organized978-1-5386-7512-0/19/$31.00 @2019 IEEE222

in 5 concentrical circles enclosing the center of thescreen. These buttons can be lighted to be used as astimulus for the participant [14]. Wells et al. (2014)
showed that this tool is a reliable one to measurereaction time (RT) [15]. It has been used in different
sports to improve peripheral vision for elite athletes
and their reaction time [14].
Eye movements provide a functional signature on
how vision is achieved. Interestingly, during the last
decade novel statistical robust analytical methods offixation mapping have been developed [16-18]
contributing to the investigation of different visual
processes. Interestingly, while using these methods,
reliable eye movement differences have been foundacross cultures for face recognition [19-24], therecognition of facial expressions of emotion [25-26] ;for a review see: [27], for visual scenes [28-29], or
between healthy and clinical patients [30-32].
Therefore, eye movements are an optimal technique toprobe the hypothesis of better visual skills from visual
information intake in professional athletes comparedto healthy observers.
In this paper, we investigated performance andreaction time differences using a paradigm that isinspired from the Dynavision Visuomotor Training
Device (D2) tool. We used a Go/NoGo task, in whicha group of 10 professional athlete hockey players andstudents were required to follow or inhibit green andred dots, respectively. Instead of pressing a labeled key
when a stimulus is on screen, participants are required
to make a saccade (fast eye-movement) toward a green
stimulus or to inhibit if the stimulus is red.
II.

During experiment, participants were instructed toeither move their eyes towards a green dot or to inhibit
it when a red dot is presented. The experiment
included 10 blocks of 64 trials each (32 green and red
dots per block). Each trial begun with a fixation crossshown randomly between 500 and 700ms followed by
a 200ms blank screen and subsequent dot displayed for
700ms in a specific color and eccentricity. Before thenext trial starts a blank screen for 500ms wasdisplayed. The paradigm is illustrated in Figure 2.

Figure 2. An example of a Go and NoGo trial. In thisexample, the eccentricity of the dot is 2°.

B. Procedure
We implemented the Go/NoGo task in Matlab(version 2013b), using the Psychtoolbox (PTB-3) [3335] and EyeLink Toolbox extensions [36]. The
experiment was displayed on a 1920 x1080 pixels
VIEWPixx monitor. We recorded the eye movementsof participants at a sample rate of 1000 Hz (only lefteye was recorded) with an SR Research DesktopMount EyeLink . Participants were invited to sit in frontof the screen at a viewing distance of 70 cm and wereinstructed about the Go/NoGo task (see Section B). At
the beginning of the experiment and between the blocksof the experiment, a 9-points calibration procedure wasconducted.

METHODS

A. Participants
Ten male elite hockey players from Fribourg
Gotteron (average age = 25 ± 5) and 10 male students
of Fribourg’s university (average age = 22 ± 3)
participated in our experiment.

III.

ANALYSES

Nystrom &Preprocessing: The algorithm ofHolmqvist [37] was applied to detect the onset of thefirst saccade (RT in ms) for the Go condition. For eachparticipant, RT that were higher or equal to 2.5SDs
from the mean were discarded (1.81%).

B. Stimuli and Paradigm Go/NoGo
Visual stimuli were dots that subtended a 0.4° ofvisual angle and were displayed at an eccentricity of
2°,5°,8° or 11°, see Figure 1. A dot with a green (red)color is defined as the Go (NoGo) condition
respectively.

Performance: The generalized linear mixed model(binomial family) was conducted [38] to investigate
both Correct Hit (CH) and Correct Rejections (CR)performances. CH refers to a presence of a saccade for
the Go condition and CR refers to an absence of asaccade for the NoGo condition. The group (hockeyplayers vs students) and the angle eccentricity of thedot were considered as predictors with their interaction
terms. The variable participant was considered as arandom factor to account for the dependency.
RT: The linear mixed model was performed toinvestigate the reaction time (RT) of participants for
the Go condition trials, only the correct trials wereanalyzed. The group (hockey players vs students) andthe angle eccentricity of the dot were considered as
predictors with their interaction terms. The variable

Figure 1. Representation of all possible locations ofdots with an eccentricity of 2°,5°,8°,11° respectively.

223

10.17, p <0.01, βangle11 = 68.18, CI = [59.92,76.44],t(6194) = 16.17, p <0.01. This result indicates that thecontrol group was faster for angle 2 (M = 269)
compared to angle 5 (M =302.58), angle 8 (M =318.44) and angle 11 (M = 345.92), however thereaction time seems not affected by the eccentricity forthe hockey group.

participant was considered as a random factor toaccount for the dependency.
We fitted all models in R [39] using the lme4 andlmerTest packages [40].
IV.

RESULTS

A. Performance
Correct Hits: The results revealed significant effect ofgroup (βcontrol = 2.19, CI = [2.47,4.16], z(6391) =3.09,
p<0.01) and angle eccentricity (βangle5 = 0.66, CI =[0.80,3.58], z(6391)=2.51, p<0.05, βangle8 = 0.63, CI =[0.15, 1.18] z(6391) =2.43, p<0.05). The control groupperformed better (M = 99.6%] compared to the hockeyplayers (M = 96.5%), see Figure 3. Furthermore, while
the performance of the control group was similar for
all angles, the hockey players were better for angle 5(98.17%) and 8 (98.11%) compared to 2 (96.50%).
Correct Rejections: The results indicated significant
effect of group (βcontrol = -0.77, CI = [-1.38,-0.15],z(6391) = -2.44, p<0.01). The hockey players
performed better (M = 54%) compared to the control
group (M = 35%). However, both groups were below
chance level (Figure 3).

Figure 4. Reaction Times (ms) for both groups considering all
angles together. Error bars represent 95% confidence intervals of themean.

V.

CONCLUSION

The aim of this study was to investigate if a
difference exists between elite Hockey players and acontrol group during a Go/NoGo task. First, our data
show no significant differences in the reaction time
between both groups; second, while the control groupperformed better in the Correct Hit (CH), Hockey
players achieved better performances in the Correct
Rejections (CR), as they were better in inhibitingreflexive saccades in the NoGo condition. However,both groups were below chance level in the Correct
Rejections. These results suggest that the paradigm
design is maybe not suitable for both groups. We thus
believe that an additional paradigm should be designed
to explore the accuracy (CH and CR) and the reaction
time. A follow-up study in which participants press akey (instead of making a saccade) when a green dot
appears and inhibit a response when a red dot appears
could be interesting to analyze and compare the results
obtain in this present study. One future direction could
be to explore performance at the individual level, forexample before and after concussion.

Figure 3. Accuracy (in %) correct hits (CH) and Correct
Rejections (CR) considering all angles together. Error bars
represent 95% confidence intervals of the mean.

B. RT
The results showed no main effects of the group(βcontrol = 17.75, CI = [-9.30,44.81], t(21) = 1.28, p>0.05), see Figure 4. However, significant effects ofthe eccentricity was revealed for the control group withβangle5 = 15.52, CI = [7.30,23.55], t(6194) = 3.69, p<0.05, βangle8 = 42.47, CI = [34.28,50.66], t(6194) =224

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