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The aim of this study was to examine the neural bases for perceptual-cognitive superiority in a soccer anticipation task using functional magnetic resonance imaging (fMRI). Thirty-nine participants lay in an MRI scanner while performing a video-based task in which they predicted an oncoming opponent's movements. Video clips were occluded at four time points, and participants were grouped according to in-task performance. Early occlusion reduced prediction accuracy significantly for all participants, as did the opponent's execution of a deceptive maneuver; however, high-skill participants were significantly more accurate than their low-skill counterparts under deceptive conditions. This perceptual-cognitive superiority was associated with greater activation of cortical and subcortical structures involved in executive function and oculomotor control. The contributions of the present findings to an existing neural model of anticipation in sport are highlighted.
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Journal of Sport & Exercise Psychology, 2013, 35, 98-109
© 2013 Human Kinetics, Inc.
Daniel T. Bishop is with the Centre for Cognition and Neu-
roimaging and the Centre for Sports Medicine and Human
Performance, Brunel University, London, UK. Michael J.
Wright is with the Centre for Cognition and Neuroimaging,
Brunel University, London, UK. Robin C. Jackson is with the
Centre for Sports Medicine and Human Performance, Brunel
University, London, UK. Bruce Abernethy is with the School
of Human Movement Studies, University of Queensland,
Queensland, Australia.
Neural Bases for Anticipation Skill in Soccer: An fMRI Study
Daniel T. Bishop,1 Michael J. Wright,1 Robin C. Jackson,1 and Bruce Abernethy2
1Brunel University; 2University of Queensland
The aim of this study was to examine the neural bases for perceptual-cognitive superiority in a soccer anticipa-
tion task using functional magnetic resonance imaging (fMRI). Thirty-nine participants lay in an MRI scanner
while performing a video-based task in which they predicted an oncoming opponent’s movements. Video clips
were occluded at four time points, and participants were grouped according to in-task performance. Early
occlusion reduced prediction accuracy signicantly for all participants, as did the opponent’s execution of
a deceptive maneuver; however, high-skill participants were signicantly more accurate than their low-skill
counterparts under deceptive conditions. This perceptual-cognitive superiority was associated with greater
activation of cortical and subcortical structures involved in executive function and oculomotor control. The
contributions of the present ndings to an existing neural model of anticipation in sport are highlighted.
Keywords: cognitive, expert, oculomotor, perceptual, sport
In interceptive sports such as soccer, experts’ advan-
tage over their lesser skilled counterparts is due in part
to superior anticipation ability (Reilly, Williams, Nevill,
& Franks, 2000); they are more adept at picking up early
movement information, enabling them to execute an
appropriate response in a timely manner (Savelsbergh,
Van der Kamp, Williams, & Ward, 2005; Williams, Ford,
Eccles, & Ward, 2011). The temporal occlusion paradigm
has enabled researchers to identify the points at which
information pickup is greatest: Participants view video
clips of an opponent performing an action such as the
tennis serve; these clips are foreshortened at various
points relative to racket–ball contact so as to provide vary-
ing degrees of visual information. Experts consistently
detect kinematic information at very early, precontact
levels of occlusion to successfully determine not only the
direction of a projectile, but also the force with which it
is struck (Abernethy & Russell, 1987; Abernethy, Zawi,
& Jackson, 2008; Jones & Miles, 1978).
The expert anticipatory advantage at early levels
of occlusion also extends to the detection of deceptive
bodily movements. Jackson, Warren, and Abernethy
(2006) asked skilled and less-skilled rugby football
players to respond to video clips that depicted one-on-
one tackle situations: An attacking player ran toward
the participant (acting as the defending player) before
obliquely changing direction, as if to pass the defender
on the left or right. In deceptive trials the player effected
a contralateral “side step” maneuver before direction
change. Low-skill players were more susceptible to this
deception than were skilled players, who could accurately
predict the intended direction change even when view-
ing early-occluded sequences. Such expert sensitivity
and novice susceptibility to deceptive movements have
been found in boxing (Ripoll, Kerlirzin, Stein, & Reine,
1995), handball (Cañal-Bruland & Schmidt, 2009),
and basketball (Kunde, Skirde, & Weigelt, 2011)—but
experts may still require directional information such as
ball ight to move substantially beyond chance perfor-
mance (Rowe, Horswill, Kronvall-Parkinson, Poulter, &
McKenna, 2009).
Although the accumulation of perceptual experi-
ence underpins many explanations for anticipation skill
superiority, others have suggested that because action
perception and execution share common neural origins
(Prinz, 1997), then it is motor expertise, be it in deception
or otherwise, that determines the extent of this advan-
tage. This notion is corroborated by investigations of the
mirror neuron system (MNS), a parieto-frontal network
of neurons that are similarly active when individuals
perform, imagine, or witness an action within their
own repertoire (Rizzolatti & Maddalena Fabbri, 2007).
Subtle differences in this MNS motor resonance when
viewing and predicting sporting actions are manifest
in behavioral (Knoblich & Flach, 2001) neuroimaging
(Calvo-Merino, Grèzes, Glaser, Passingham, & Haggard,
2006) and psychophysiological (Aglioti, Cesari, Romani,
& Urgesi, 2008) data.
Official Journal of NASPSPA
Neural Bases for Soccer Anticipation 99
The roles of neural systems in sport anticipation
have been investigated more extensively in recent years.
Wright and Jackson (2007) employed the temporal
occlusion paradigm to examine novice tennis players’
cortical fMRI activation when predicting an opponent’s
serve direction. Action prediction signicantly activated
MNS regions when contrasted with a passive observa-
tion condition. Wright, Bishop, Jackson, and Abernethy
(2010) subsequently found stronger activations for early-
than for late-occluded sequences of a badminton shot,
notably in premotor MNS regions and in medial frontal
cortex. Experts also exhibited greater frontal MNS and
medial frontal cortex activation than did novices when
viewing the early-occluded sequences. To assess the
relative contribution of kinematic information to these
differences, Wright, Bishop, Jackson, and Abernethy
(2011) compared expert, intermediate, and novice bad-
minton players’ responses to normal video and point-light
displays of opponents in a badminton prediction task.
Activations were highly similar for both video formats,
reinforcing the prominence of kinematic information;
moreover, greater frontal activity was apparent in experts
when viewing early-occlusion sequences. There was also
evidence for suppression of low-level, task-irrelevant
stimuli in experts, suggesting greater attentional ef-
ciency. However, experts’ comparatively high levels of
activation in anticipation tasks stands in sharp contrast
to that witnessed during imagery of a self-paced sport:
Milton, Solodkin, Hluštík, and Small (2007) compared
the neural activity of expert and novice golfers as they
mentally prepared for a hypothetical putt shot. The
authors found almost ubiquitously stronger activation
in novices, in areas of the brain associated with motor
planning and execution—most notably the basal ganglia;
this collection of nuclei are pivotally involved in deci-
sion making and subsequent action selection, making
reciprocal connections with motor and premotor areas
of the cortex. Milton et al. interpreted the comparatively
lower activity in experts as a reduction in the complex-
ity of dynamic motor control, thereby promoting greater
movement consistency.
Milton et al.’s (2007) ndings contrast with the very
active role for the basal ganglia proposed by Yarrow,
Brown, and Krakauer (2009) in their affordance compe-
tition model of motor preparation and decision making,
based on Cisek’s (2007) affordance competition hypoth-
esis. Yarrow et al. propose a complex cortico-subcortical
network comprising not only regions of the MNS, but
also prefrontal cortex, ventral and dorsal visual pathways,
and two subcortical structures—the basal ganglia and the
cerebellum. In this model, visual inputs are transformed
into motor plans, which may be manifested in commonly
observed MNS resonance, before the basal ganglia behav-
iorally bias the best possible motor action, by encoding
the difference between expected and actual reward of a
given course of action (Stocco, Lebiere, & Anderson,
2010)—ultimately leading to action execution; the hours
of deliberate practice accrued by expert performers (Eric-
sson, Krampe, & Tesch-Römer, 1993) may potentiate this
function of the basal ganglia. According to the model, the
cerebellum is primarily involved in transforming visual
input into motor plans. However, activation in the culmen,
a region of the cerebellum, has been correlated with low
response time variability in children performing a go/
no-go task (Simmonds et al., 2007), which indicates a
potential role for this region also in biasing the correct
response. Yarrow et al. propose that the basal ganglia
and cerebellum serve important functions in generating
and selecting motor plans. Accordingly, we might expect
greater activation in superior anticipators, in both of these
subcortical structures, which is contrary to neural activity
witnessed in golf putting (Milton et al.) and in previous
fMRI studies of anticipation skill in sport (Wright et al.,
2010, 2011).
The primary aim of this study was to provide an
insight into those neural mechanisms identied in the
affordance competition model (Yarrow et al., 2009) that
may differentiate those demonstrating superior anticipa-
tion skill from their lesser skilled counterparts, using
rapidly occurring and unpredictable stimuli (see Mann,
Williams, Ward, & Janelle, 2007); this is a novel
step for an fMRI study in sport. A second aim was to
uncover a neural basis for the previously identied
expert advantage when confronted with deceptive
actions, as this has hitherto received no attention in
neuroimaging studies of sport anticipation thus far. In
accordance with existing sport anticipation fMRI data
(Wright et al., 2010, 2011) and research into decep-
tion in sport (e.g., Jackson et al., 2006; Kunde et al.,
2011), we propose four primary hypotheses: (1) That
high-skilled anticipators’ superiority will be greatest
when viewing early-occluded sequences and when
viewing deceptive footage; (2) that this group dispar-
ity will be greatest when participants view deceptive
footage at the earliest point of occlusion; (3) that there
will be comparatively higher levels of MNS and medial
frontal cortex activation in high-skilled anticipators when
predicting an oncoming opponent’s actions; and (4) that
the differences in MNS activation will be greater still
under combined early occlusion and deceptive conditions.
Yarrow et al.’s (2009) affordance competition model pro-
vides us with a useful basis for predictions, grounded as it
is in an extensive corpus of experimental and behavioral
research; hence, we also cautiously predict increased
activation, in superior anticipators, of basal ganglia and
cerebellar nuclei.
A convenience sample1 of 41 male participants was
recruited on the basis of their competitive experience
in soccer: Experiences ranged from none to regular
semiprofessional competition. The study was approved
by the Brunel University Research Ethics Committee
in accordance with the Declaration of Helsinki, and all
participants gave their informed consent before partici-
100 Bishop et al.
pation. Two participants’ data were excluded from the
analysis due to a z-plane drift in excess of 2 mm from their
original position during fMRI data acquisition. Soccer
playing expertise is a concatenation of many attributes,
one of which is anticipation skill (Reilly et al., 2000).
Therefore, to specically examine the neural mechanisms
underpinning anticipation skill in the present task, overall
prediction accuracy was used to categorize participants;
this criterion has recently been advocated as a valid means
by which differences in sport anticipation skill can be
investigated (Huys et al., 2009; Roca, Williams, & Ford,
2012; Vaeyens, Lenoir, Williams, & Philippaerts, 2007;
Williams & Ericsson, 2005; Williams & Ford, 2008).
Consequently, the remaining 39 participants (Mage =
22.5 years, SD = 3.73 years) were classied post hoc
into three groups differing in anticipation skill: low-skill
anticipators (chance-level performance or below, n = 11;
mean competitive experience [Mexp] = 2.4 years, SD = 4.1
years), intermediate-skill anticipators (51–59% accuracy;
n = 14; Mexp = 10.2 years, SD = 6.0 years) and high-skill
anticipators ( 60% accuracy, n = 14, Mex p = 13.2 years,
SD = 3.1 years).
We lmed sequences of three junior international-level
soccer players dribbling toward a video camera (NV
GS400; Panasonic Corporation, Secaucus, NJ) placed
at a distance of 11.5 m from the start of the players’
run, in an indoor sports hall. The actors ran toward the
camera and then moved obliquely in a predetermined
direction (left/right), as they would when attempting to
evade a defending player’s interception. They performed
a deceptive maneuver known as a stepover in 50% of
runs immediately before direction change; for the
remaining 50% of prediction trials no deception was
performed. Video clips were edited using video edit-
ing software (Pinnacle Studio Pro v. 11.0, Pinnacle
Systems, Mountain View, CA) to create four levels of
temporal occlusion for each video format: at the point of
direction change (t0), 160 ms before t0 (hereafter, –160
ms), 80 ms before t0 (–80 ms), and 80 ms after t0 (+80
ms). Forty-eight experimental video clips (3 actors × 2
directions × 2 levels of deception × 4 iterations) and 24
control clips of the same soccer players walking casu-
ally across the eld of view with the ball were created
and presented on six occasions each, yielding a total of
432 stimuli. No anticipation was required in the control
clips, which enabled a contrast with experimental clips,
for levels of MNS activation.
fMRI Data Acquisition
We acquired functional and structural images on a Trio
3T MRI scanner (Siemens, Erlangen, Germany) via an
eight-channel array head coil. For each functional run, a
standard, whole-brain, echo planar gradient-echo imag-
ing sequence was used to acquire 41 transverse slices (3
mm in thickness; TR, 3000 ms; TE, 31 ms; ip angle =
90°). Whole-brain anatomical data were collected using
a 176-slice, 1-mm3 voxel size, MP-RAGE T1-weighted
Experimental Procedure
Participants were familiarized with both the experimental
protocol and the scanner environment before commenc-
ing the study. Each participant lay in the supine position
in the scanner while viewing back-projected video stimuli
via an overhead mirror. For experimental stimuli, they
were required to press one of two buttons on an MRI-
compatible response box (LUMItouch; Photon Control,
Inc., Burnaby, BC, Canada) to indicate the direction in
which they believed the video clip actor would move
(left/right); they pushed a third button to indicate control
footage. Participants were asked to respond as quickly and
accurately as possible. Prediction accuracy and response
time were collected via experiment generator software
(E-Prime v. 2.0, Psychology Software Tools, Inc., Pitts-
burgh, PA). Stimuli were blocked according to level of
occlusion; the order in which blocks were viewed was
partially counterbalanced across all participants. Presen-
tation of the three video clip types (deceptive/nondecep-
tive/control) was automatically randomized within each
block. A total of 108 clips, each lasting approximately 2
s, were presented in each of the four occlusion blocks.
All clips were followed by a blank gray screen lasting
1.7 s, during which participants registered their response.
Participants performed a simple visual cognition task for
1 min between blocks. Thus, each block lasted approxi-
mately 400 s. On-screen instructions gave additional
guidance to the participants. Brain imaging data were
acquired throughout.
Data Analysis
Response Data. Response data were analyzed not
only to conrm the validity of the within-task criterion
for group formation, but also to investigate the extent
to which performance was mediated by factors such as
level of occlusion and deception; hence, a mixed Group
(high, intermediate, and low skill) × Occlusion (–160 ms,
–80 ms, t0, +80 ms) × Condition (control, deception, no
deception) factorial MANOVA was applied to the data.
Due to a button box fault, one high-skill participant did not
contribute response data. All analyses were performed using
PASW Statistics 18 (v 18.0; IBM, Armonk, NY). Where
signicant main effects or interactions were detected,
simple main effects analysis followed using one-way
ANOVA and Tukey’s post hoc test, or dependent t tests
where appropriate. Signicance was accepted at p < .05.
fMRI Data. Brain imaging data were analyzed using
SPM8 (http://www. Functional
images were spatially realigned to the first image
in the series then co-registered with the T1 image.
Images were normalized to the Montreal Neurological
Institute (MNI) template and then smoothed using a
Gaussian kernel of 7 mm full-width half-maximum.
The design matrix convolved the experimental design
Neural Bases for Soccer Anticipation 101
with a hemodynamic response function. The model was
estimated using proportional scaling over the session to
remove global effects, and with a high-pass lter of 128
s. Contrasts were computed to assess the change from the
implicit baseline in each combination of experimental
conditions, for each participant. Random effects analysis
was performed by entering the contrast images derived
into SPM’s full factorial model. For each experimental
contrast, signicantly activated voxels were to be dened
as those within the whole-brain smoothed gray matter
mask that satised a family-wise error (FWE) rate of p
< .05 and exceeded an extent threshold of 20 voxels. We
labeled brain locations of the peaks of activation with
reference to anatomical landmarks and Brodmann areas
(BAs) using WFU PickAtlas (Maldjian, Laurienti, Kraft,
& Burdette, 2003).
Response Data
Analyses revealed signicant main effects of group,
Wilks’s lambda (.27), F(4,68) = 15.93, ηp2 = .48, p <
.001; occlusion, Wilks’s lambda (.08), F(6,30) = 56.10,
ηp2 = .92, p < .001; and condition, Wilks’s lambda (.02),
F(4,32) = 324.57, ηp2 = .98, p < .001. Univariate tests,
pairwise comparisons, and descriptive statistics for all
main effects are shown in Table 1.2
There were signicant interactions for Group ×
Condition, Wilks’s lambda (.39), F(8,64) = 4.90, ηp2 =
.38, p < .001 and Occlusion × Condition, Wilks’s lambda
(.09), F(12,24) = 19.25, ηp2 = .91, p < .001. Follow-up
univariate tests revealed that differences in prediction
Table 1 Univariate F Tests and Pairwise Comparisons for All Main Effects
Factor Skill Level DV
Group Low Prediction Accuracy (%)* 66.3 39.8
Intermediate 72.7 32.8
High 79.5 26.6
Low Response Time (ms)** 2156.4 187.7
Intermediate 2175.9 199.7
High 2063.8 210.9
a *F(2,35) = 38.43, p < .001, ηp2 = .69; High > Intermediate > Low, p < .001.
**F(2,35) = 1.05, p > .05, ηp2 = .06.
Occlusion –160 ms Prediction Accuracy (%)* 65.3 46.4
–80 ms 65.8 41.6
t0 76.2 32.1
+80 ms 86.3 18.3
–160 ms Response Time (ms)** 2199.5 157.0
–80 ms 2153.6 183.6
t0 2095.7 221.4
+80 ms 2069.1 259.0
b *F(3,105) = 111.16, ηp2 = .76, p < .001; +80 ms > t0 > –80 ms, –160 ms, p < .001.
a **F(3,105) = 4.84, ηp2 = .12, p < .005; –160 ms > –80 ms > t0, p < .05.
Condition Control Prediction Accuracy (%)* 96.4 0.2
Deception 33.5 23.9
No Deception 90.2 6.5
Control Response Time (ms)** 1895.9 105.3
Deception 2270.9 12.9
No Deception 2221.6 67.7
b *F(2,70) = 947.49, ηp2 = .96, p < .001; Control > No Deception > Deception, p < .001.
b **F(2,70) = 40.47, ηp2 = .54, p < .001; Deception > No Deception > Control, p < .001.
aTukey’s HSD.
bBonferroni corrected for multiple comparisons.
102 Bishop et al.
accuracy accounted for the observed Group × Condi-
tion interaction, F(4,315) = 20.84, ηp2 = .54, p < .001;
however, paired t tests showed that all participants were
signicantly more accurate when viewing control footage
than in the experimental conditions, and when viewing
nondeceptive, as compared with deceptive, footage p <
.005. Differences in both prediction accuracy, F(6,210)
= 59.47, ηp2 = .63, p < .001 and response time, F(6,210)
= 5.07, ηp2 = .13, p < .001 accounted for the Occlusion ×
Condition interaction: Paired t tests showed that predic-
tion accuracy was greater for the control condition than
for predictive conditions at the three earliest levels of
occlusion, p < .001, but not at t +80 ms, p > .05. In addi-
tion, participants took signicantly longer to respond to
deceptive footage than they did to nondeceptive footage
at the two later levels of occlusion, p < .001. Group ×
Occlusion and Group × Occlusion × Condition interac-
tions did not reach signicance, p > .05. The simple main
effects of group for prediction accuracy at each level of
condition and occlusion are displayed in Figure 1.
fMRI Data
There were signicant main effects of group, occlusion,
and condition (FWE corrected p < .05). On closer scru-
tiny, some contrasts contributed more strongly than others
to these effects; these activations, which met the stringent
threshold criteria, are shown in Table 2.3 Activation in
cerebellum (pyramis, culmen), inferior visual cortex,
superior temporal gyrus, and precuneus differentiated
high-skill anticipators from their intermediate- and low-
skill counterparts when seeking to predict an opponent’s
movements. Further, when visual information was most
restricted (i.e., at the earliest level of occlusion), there was
also activation of a combination of cortical and subcorti-
cal structures—basal ganglia (lentiform nucleus in Table
2), thalamus, and cingulate/supplementary eye eld. In
addition, the greatest activation differences in high-skill
participants occurred between the two earliest levels of
occlusion—160 ms and 80 ms before the opponent’s
direction change; the foci were in the superior temporal
gyrus, superior and inferior parietal lobules, and supe-
rior frontal gyrus. Figure 2 shows the loci of activations
in high-skill anticipators for each of three contrasts, in
cerebellum (pyramis), basal ganglia (lentiform nucleus),
and anterior cingulate cortex (ACC) (this gure is in color
in the PDF [online] version of this article).
The data from the Prediction > Control contrast
did not show any signicant foci at the original display
threshold criterion (p < .05, FWE corrected for multiple
comparisons), which may be the result of a diminished
contrast-to-noise ratio for these rapidly alternating
stimuli. However, at a lowered voxel-wise threshold of p
< .005 (uncorrected), activation patterns were similar to
those found for both novices and experts in earlier studies
of badminton (Wright et al., 2010, 2011), in which pre-
diction and control conditions were separately blocked.
Areas included precuneus, premotor cortex, extrastriate
Figure 1 — Main simple effects of group, by occlusion and condition.
Neural Bases for Soccer Anticipation 103
Figure 2 — (This gure is in color in the PDF [online] version.) Greater
cerebellar, basal ganglia, and right anterior cingulate cortex activation
for experts when predicting opponents’ movements.
cortex, inferior frontal gyrus, superior frontal gyrus, and
supplementary eye elds (SEF). Loci of signicant acti-
vations at the new threshold, but at an extent threshold
of 60 voxels, are shown for all participants combined in
Table 3. Figure 3 illustrates the activations witnessed for
the same contrast (prediction vs. control) for each of the
three groups separately (this gure is in color in the PDF
[online] version of this article).
The foremost contribution of this study was to identify
potential neural bases for anticipation skill superiority in
soccer. Two additional novel developments on previous
fMRI-based studies of anticipation in sport (Wright et
al., 2010, 2011) were (i) the introduction of video clips
in which the actor was performing a deceptive maneuver
and (ii) the randomized interspersing of these deceptive
stimuli with nondeceptive and control clips so as to
reduce predictability—and therefore the potential for in-
task learning. As per our rst hypothesis, the high-skill
anticipators were signicantly better than lesser skilled
participants at predicting opponents’ actions in the decep-
tive condition—although this did not vary according to
level of occlusion, contrary to our second prediction. The
understanding of others’ actions was reected somewhat
in brain activations, in line with our third hypothesis:
There was evidence of stronger activation of MNS (e.g.,
inferior parietal lobule, BA6) and related areas in high-
skill participants when compared with the intermediates,
who in turn exhibited greater MNS activation than did the
low-skill group, when predicting an opponent’s actions
(see Figure 3; cf. Wright et al., 2010, 2011)—albeit
only when deceptive and nondeceptive conditions were
examined conjointly; there was also no apparent three-
way interaction (i.e., differences in MNS activations were
Figure 3 — (This gure is in color in the PDF [online] version.) Mirror neuron system activations for all participants (red = high
skill; green = intermediate; blue = low skill).
Table 2 Loci of Activation for Experimental Contrasts, Determined at a Family-Wise
Error–Corrected Display Threshold p < .05 and Extent Threshold k > 20
Region BA Size
Z x y z
(a) High-Skill > Intermediate, Low-Skill for Prediction (Deception + No Deception), All Occlusion Levels
R Pyramis 525 .001 6.05 6 –79 –26
R Culmen 525 .001 5.37 30 –40 –35
R IOG 18 192 .001 5.44 39 –85 –2
R STG 39 192 .026 4.56 60 –61 22
R SPL 19 62 .049 4.4 33 –76 49
(b) High-Skill > Intermediate, Low-Skill for Prediction at –160 ms
L Lentiform Nucleus 49 .009 5.79 –18 5 -8
L SFG 6 22 .018 5.58 –9 32 61
L SEF 6 29 .001 5.26 –6 –7 58
L Cingulate Gyrus 24 29 .02 4.63 –15 2 46
R Thalamus 25 .002 5.12 3 –10 1
(c) High-Skill > Intermediate, Low-Skill for Deception at –160 ms
R ACC 33 22 .003 5.06 9 17 19
(d) –160 ms > –80 ms for Prediction, High-Skill Participants
L STG 22 340 0.003 5.07 –60 –16 1
R Precuneus 7 240 0.01 4.78 18 –55 70
L IPL 7 160 0.013 4.73 –45 –64 52
L IPL 39 160 0.015 4.69 –51 –61 46
R SFG 6 95 0.022 4.6 24 2 70
Note. In Montreal Neurological Institute coordinates. ACC = anterior cingulate cortex; BA = Brodmann area; IOG = inferior occipital gyrus;
IPL = inferior parietal lobule; MFG = middle frontal gyrus; SEF = supplementary eye eld; SPL = superior parietal lobule; STG = superior temporal
Neural Bases for Soccer Anticipation 105
Table 3 Loci of Activation for Prediction >
Control; Determined at a Trend-Level Display
Threshold p < .005 and Extent Threshold k > 60
Region BA
Z x y z
All participants
L SEF 6 520 3.00 –24 –4 67
R SEF 6 376 3.16 21 –10 67
R SPL 7 210 3.92 36 –46 58
L MFG 6 148 4.06 –24 –7 61
L premotor 6 148 2.79 –39 –1 61
L premotor 6 148 2.88 –51 2 43
R IOG 18 136 3.42 24 –94 –8
L IFG 9 77 3.11 –45 8 25
L SFG 6 72 3.14 –3 17 49
Note. In Montreal Neurological Institute coordinates. BA = Brodmann
area; IFG = inferior frontal gyrus; IOG = inferior occipital gyrus;
MFG = middle frontal gyrus; SEF—supplementary eye eld; SFG =
superior frontal gyrus; SPL = superior parietal lobule; STG = superior
temporal gyrus.
Figure 3 (continued)
not magnied when participants viewed early-occluded
deceptive footage).
Also in keeping with our predictions, differences
between the high-skilled and lower-skilled participants
were most clearly manifest in both behavioral and fMRI
data when early-occluded sequences were viewed (i.e.,
when the least information was available), but the most
robust differences in neural activation—which included
cortical and subcortical areas identied in the affordance
competition model—occurred consistently between
high-skill and intermediate/low-skill participants com-
bined; there was negligible difference between the latter
two groups, which is noteworthy when considering that
the intermediates had still accrued considerably more
competitive experience, on average, than their novice
counterparts (t[23] = 3.58, p < .005). Thus, the brain
activation differences witnessed may correspond to not
only the surpassing of a threshold for hours accumulated
in practice/competition to become sufciently expert (see
Ericsson et al., 1993), but also the quality of such practice.
The strongest activation of MNS regions that cor-
respond to those found in badminton (Wright et al., 2010,
2011) were witnessed only in high-skill participants,
when –160 ms was contrasted with –80 ms (Table 2[d]).
This is a somewhat unanticipated nding, because we
might expect greater MNS activation when an increased
amount of familiar visual information is presented, but
this may simply reect an increased level of engagement
with the more challenging brief stimulus duration. Indeed,
this is consistent with the notion that early occlusion
actually increases participants’ attention (Wright et al.,
2010). When novices’ data were considered in isolation
(Figure 3), they did not exhibit signicant MNS activa-
tion when viewing the prediction sequences, relative to
baseline, which is consistent with their comparative lack
of experiences in soccer and thus lack of familiarity with
the actions performed, be they deceptive or otherwise.
106 Bishop et al.
Similar to ndings in tennis (Rowe et al., 2009), but
in contrast to ndings from rugby (Jackson et al., 2006),
the high-skill participants’ performance in the presence
of deception did not move above chance level until t0—
the point of direction change; however, intermediates’
performance did not do so until the opponent’s nal
direction of movement was visible (+80 ms), and low-
skill participants never rose above chance level. Thus,
while the high-skill participants were still being deceived
regularly at the two earliest stages of occlusion, there was
clear behavioral (Figure 1) and neuroimaging evidence
(Table 2) of their superiority. Mirror neuron system
activation was not clearly apparent when the deceptive
condition was considered in isolation, contrary to our
hypotheses. However, this may have been a function of
a low signal-to-noise ratio in the data, derived from rapid
alternating presentation of video stimuli; this is a novel
step for such neuroimaging studies, but it is an important
one if real-world conditions faced are to be approximated.
Nonetheless, there was highly robust evidence (p < .05,
FWE corrected) for activity in high-skill participants
of a cortico-subcortical network of structures compris-
ing cerebellum, thalamus, basal ganglia, and ACC—a
network that has been implicated not only in executive
function (Heyder, Suchan, & Daum, 2004; Kim, Kroger,
& Kim, 2011; Lütcke, Gevensleben, Albrecht, & Frahm,
2009), but also in oculomotor control (Heyder et al., 2004;
Tanaka & Kunimatsu, 2011). Moreover, the cerebellar
and basal ganglia activations are consistent with the
predictions of the affordance competition model (Yarrow
et al., 2009).
The single activation that discriminated high-skilled
players from both intermediates and low-skill participants
when viewing deceptive maneuvers arose in a nite
region of right ACC (x = 9, y = 17, z = 19; cluster size = 22
voxels). We previously found right ACC (rACC) activa-
tion in badminton experts relative to novices, when they
were required to respond to point-light representations of
opposing players’ actions (Wright et al., 2011); further
fMRI data using point-light displays will help us to better
understand the informativeness of opponent kinematics,
as opposed to other cues (e.g., opponent’s gaze), with
regard to deception. The ACC has consistently been
identied as an important structure in the monitoring of
response conict, specically when a motor response is
required (Turken & Swick, 1999)—and right-lateralized
activation reects the processing of visuospatial stimuli
(K. E. Stephan et al., 2003). Highly comparable activa-
tion has been shown in a similarly focalized and right-
lateralized region of ACC (x = 5, y = 21, z = 34) when
participants either correctly rejected, or failed to reject,
incorrect stimuli in a go/no-go task (Lütcke & Frahm,
2008); similar activation was found in rACC (x = 9, y =
16, z = 32) when participants were required to manage
competing response alternatives in a Stroop interference
task (Kim et al., 2011). Thus, the rACC activation wit-
nessed in the deceptive condition may represent not only
the suppression of the high-skill anticipators’ prepotent
responses to the deceptive maneuver—to anticipate/move
in the direction of the deception—but also to monitor any
incorrect decisions made; this is comparable to the role
proposed for the basal ganglia in assessing the “reward
value” of potential response options (Yarrow et al., 2009).
Given the absence of any response accuracy differ-
ences at –160 ms, the latter rACC function is the more
likely of the two, for the present data. Such inhibition
is highly adaptive in situations for which the cost of
not doing so may be high; for example, the tendency of
handball goalkeepers to perceive opponents’ movements
as deceptive may stem from a cost–benets analysis that
ultimately favors caution (Cañal-Bruland & Schmidt,
2009). It is also noteworthy that—peculiarly—all partici-
pants’ performance in the control condition was still not at
100% accuracy, irrespective of level of occlusion, which
suggests that key press errors occurred. Performance for
all participants in the nondeceptive condition was not only
high, but also largely equivalent, except at occlusion level
t0–80 ms (see Figure 1), suggesting that the actors’ move-
ment intentions were easy to predict in the absence of
deception. Hence, the ability to perceive, and then inhibit
a prepotent response to, an opponent’s deception could
be a key factor that discriminates perceptual-cognitively
skilled soccer players from those not so skilled.
High-skill anticipators’ activations at the earliest
stage of occlusion comprised regions similar to those
previously identied as supplementary eye elds (SEF),
regions of the frontal lobes that are involved in the plan-
ning and control of saccadic eye movements (Amiez &
Petrides, 2009; Grosbras, Laird, & Paus, 2005; Pierrot-
Deseilligny, Milea, & Müri, 2004) and of a network
comprising striatal (lentiform nucleus), thalamic, and
cingulate areas identied as coacting in executive
control processes (Heyder et al., 2004; Lütcke et al.,
2009). Not only do the ventroanterior region of the
thalamus and the basal ganglia appear to play important
roles in the generation of volitional saccades (Tanaka
& Kunimatsu, 2011), but the latter also plays a key
role in biasing the correct motor response selection
(Yarrow et al., 2009). The greater cerebellar activations
in the high-skill anticipators are also consistent with
the notion of increased oculomotor activity and motor
preparation (Simmonds et al., 2007; Yarrow et al., 2009)
and working memory-driven saccades (cf. Nitschke et
al., 2004; T. Stephan et al., 2005). These activations col-
lectively suggest that skilled participants’ performance
incorporated better preparation of intentional saccades,
through biasing oculomotor activity, which relates well
to the commonly observed efciency of expert visual
search patterns (Gegenfurtner, Lehtinen, & Säljö, 2011;
Mann et al., 2007).
Some of the activations observed are pertinent to the
shifting of attention, rather than saccadic activity, such as
that observed in the lentiform nucleus (see Grosbras et
al., 2005). The precuneus, an important part of the dorsal
visual stream identied in the affordance competition
model (Yarrow et al., 2009) that plays an integral role
in orientation of attention (Cavanna & Trimble, 2006)
and execution of voluntary saccades (Grosbras et al.,
Neural Bases for Soccer Anticipation 107
2005), was more active in high-skilled participants as
they viewed the shortest occlusion condition footage
(–160 ms), when contrasted with the next shortest (–80
ms), suggesting a change in attentional strategy when
confronted with very limited visual information. There
is also evidence for superior shifting of attention in high-
skill anticipators across all levels of occlusion, in the
activation of superior parietal lobule. Almost identical
activation has been found for exogenously controlled
shifts of attention (Molenberghs, Mesulam, Peeters, &
Vandenberghe, 2007). If this is also the case for our data,
then high-skill participants’ visual search/attentional
strategy was predominantly determined by features of
the stimulus (e.g., the opponent’s movements), not by
a preconceived plan as to which sections of the display
would be most informative.
Given the complex, naturalistic qualities of the
stimuli used in the current study, the extent to which
our data parallel those from the studies cited above, in
which simple experimental stimuli were used, is very
encouraging. However, there was a notable absence of
coactivation of some structures, when we might reason-
ably have expected it, at the strict FWE threshold; this
may be a function of the experimental design. Further
analyses from protocols comprising longer blocks (~20
s) of deceptive stimuli may produce data that yield this
coactivation; however, the imperative to reduce predict-
ability remains (see Mann et al., 2007). Functional con-
nectivity analyses would conrm/disconrm the proposed
operations of the affordance competition model (Yarrow
et al., 2009); the present data depict many robust activa-
tions predicted by this model, but cannot tell us about
interrelations between the different regions. Trial-by-trial
feedback would help us to clarify the role of ACC in the
recognition of conict between outcome and reward
(reward in this case would be correct prediction).
To our knowledge, this is the rst study to identify
activity in brain regions comprising a cortico-subcortical
network, over-and-above putative attentional and MNS
systems, that may underpin perceptual-cognitive supe-
riority in sport anticipation tasks. Consistent with our
predictions, high-skill anticipators were more attuned to
both early kinematic information and deceptive move-
ments than were their less-skilled counterparts; neuro-
imaging data also showed greater activation of MNS and
related structures in this group. The advantage was most
profound when viewing deceptive footage, but this was
irrespective of occlusion—contrary to our predictions.
There was also neuroimaging evidence for changes in
high-skilled participants’ allocation of attention when
visual information was constrained, whether these
shifts were stimulus or goal driven. Although Yarrow et
al.’s (2009) affordance competition model has provided
a suitable foundation for the predictions made, some
activations—most notably those in basal ganglia and
cerebellum—have been conspicuously lacking in previ-
ous studies (e.g., Wright et al., 2010, 2011). However,
there was robust evidence for greater activation of these
structures in the present data. In addition, there was evi-
dence for thalamic activation in high-skill participants
when viewing early-occluded footage, and evidence of
conict monitoring (ACC) when viewing opponents’
deceptive actions. Hence, we tentatively propose that
these two highly interconnected structures (see Heyder
et al., 2004) may be added to the affordance competition
model, which would then more comprehensively illus-
trate the interactions of diverse cortical and subcortical
neural systems that characterize superior anticipation
skill in sport.
1. This sample size was recruited according to (a) power
calculations based on preliminary analysis of the response
data and (b) threshold sample sizes previously established as
appropriate for such fMRI designs (Desmond & Glover, 2002;
Zandbelt et al., 2008).
2. The main effect of anticipation skill is not meaningful per
se, because the groups were formed on this basis. However,
these data are presented in Table 1 to conrm the reliability
of the classication used; additionally, Figure 1 elucidates the
extent to which overall performance was moderated by level
of occlusion and deception (i.e., whether high-skill anticipators
were superior uniformly, or only under specic conditions).
3. There were a large number of highly signicant activations
across all contrasts, even with stringent corrections applied to
p values. Therefore, to aid interpretability and informativeness,
activations were only included for group contrasts when they (a)
satised the imposed threshold criteria (FWE) and (b) related
to the performance differences.
We extend our gratitude to Jasmine Field and Adrian Williams
for their assistance with fMRI data preprocessing and Matlab
programming, respectively.
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Manuscript submitted: May 22, 2012
Revision accepted: November 23, 2012
... Indeed, in elite soccer, the use of motor skills has largely been studied from a subjective perspective , but mastery of these skills (Castañer et al., , 2016aWallace and Norton, 2014) is directly linked to motor versatility (Bishop et al., 2013) and consequently to the ability to execute complex intentional actions (Memmert et al., 2013). Motor versatility in both individual and team sports requires the integration of multiple skills (Bishop et al., 2013); it is a particularly important quality in attackers such as strikers and wingers and is closely linked to motor anticipation (Murgia et al., 2014). ...
... Indeed, in elite soccer, the use of motor skills has largely been studied from a subjective perspective , but mastery of these skills (Castañer et al., , 2016aWallace and Norton, 2014) is directly linked to motor versatility (Bishop et al., 2013) and consequently to the ability to execute complex intentional actions (Memmert et al., 2013). Motor versatility in both individual and team sports requires the integration of multiple skills (Bishop et al., 2013); it is a particularly important quality in attackers such as strikers and wingers and is closely linked to motor anticipation (Murgia et al., 2014). In fact, the ability to efficiently and effectively execute skilled movement patterns is the most important aspect of soccer performance and players must apply cognitive, perceptual and motor skills to rapidly changing situations (Ali, 2011). ...
... In addition, most of these movements are interlinked. Laterality (Teixeira et al., 2011;Bishop et al., 2013), for example, refers not only to left-right preference but also to how a player orients his body spatially (Bishop et al., 2013;Loffing et al., 2015). Previous research (Castañer et al., 2016a) has demonstrated that Lionel Messi-a left-footed player whose has achieved some of his best results playing on the right wing-is a good example of laterality. ...
... Neuroimaging studies have identified a bilateral network within frontal premotor, parietal, and temporooccipital cortex (Caspers et al., 2010). In particular, the frontoparietal network has been shown to be a dynamic control system that provides predictive computations (Avenanti et al., 2012), which have been seen throughout the temporal occlusion literature, including hockey (Wimshurst et al., 2016), tennis (Wright & Jackson, 2007), and soccer (Bishop et al., 2013) . ...
... tDCS has also been examined as a means to enhance performance in normal subjects during visual working memory tasks and selective attention tasks (Clark et al., 2012). Expert athlete performers have been shown to rely more heavily on parietal region functioning compared with novices during occlusion tasks (Abreu et al., 2012;Yarrow et al., 2009) suggesting a shift toward a superior attention strategy due to limited visual cues (Bishop et al., 2013). The parietal lobe has been shown to be a key component in the AON in general (Buccino et al., 2001), as well as providing predictive reasoning during action observation (Fontana et al., 2012). ...
Effective anticipation skills in sporting cognition have been shown to facilitate expertise in sports. Transcranial direct current stimulation (tDCS) has shown to improve motor and cognitive functioning. Therefore, this study aimed to determine the assistive effects of tDCS on the action observer network in both novice and expert gamers during an occlusion task, as well as the related electroencephalographic spectral power response. Twenty-three novice and 23 expert video gamers received either sham or active tDCS with a right parietal anode and left frontal cathode. Only experts demonstrated a significant improvement in predicting ball direction for the overall and early occlusions after tDCS. Spectral power results revealed significant changes in theta, high-gamma, and delta frequencies. The findings indicate that tDCS was able to modulate anticipatory behavior and cortical activity in experts compared with novice participants, suggesting a facilitatory role for tDCS to improve anticipatory effects and assist as a neurocognitive training technique.
... This ability to attenuate the negative impact of deceptive actions of others might be based on two different factors. First, experts typically have extensive motor experience of producing such fake actions themselves (e.g., Bishop et al., 2013;Wright et al., 2013). Second, experts experience such fake actions as observers. ...
... Moreover, the head-fake effect was smaller for the group of basketball players than for all other groups. This finding is in accordance with previous studies on fake actions in sports (e.g., Bishop et al., 2013;Cañal-Bruland & Schmidt, 2009;Sebanz & Shiffrar, 2009;Wright et al., 2013) and with studies, which investigated anticipation performance for actions without any deceptive intent (e.g., Abernethy et al., 2008;Abernethy & Zawi, 2007;Urgesi et al., 2012). The superiority in basketball players found here might be grounded in their action representations, which improve perceptual processing of similar actions of others (i.e., common-coding theory; Schütz-Bosbach & Prinz, 2007). ...
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The present study was conducted to disentangle the relative impact of visual and motor experience on the processing of the head fake in basketball. In a pre-test-intervention-post-test study, we investigated if the head-fake effect can be reduced with either a one-week visual-training intervention (visual-training group: N = 17, 10 females, 7 males, mean age = 21.2 years) or with a one-week motor-training intervention (motor-training group: N = 17, 10 females, 7 males, mean age = 20.9 years). Additionally, a waiting-control group (N = 17, 8 females, 9 males, mean age = 23.1 years) without any intervention and a group of experienced basketball players (N = 21, 9 females, 12 males, mean age = 23.9) was tested in the pre-post-test design (i.e., without intervention). The size of the head-fake effect was measured in a laboratory setting with a reaction time experiment, in which participants had to classify the pass direction of a faking or non-faking basketball player, who was shown in a video on a screen wall. The study revealed that the head-fake effect decreased after the training interventions. Surprisingly, the waiting-control group showed similar improvements. Thus, the reduced head-fake effect appears to be based on test-repetition effects. Moreover, after a single test session the head-fake effect approached a level that experts displayed from the outset. Even a small amount of practice (i.e., test-repetition) is sufficient to reduce, though not to abolish, the head-fake effect. We discuss this finding with regard to the common-coding approach and working memory capacity.
... The journey towards becoming an expert can therefore be viewed as a process of becoming attuned to specifying information or making better use of non-specifying information [29,29]. Issues arise, however, when an opponent is deceptive, meaning the most salient information is hidden, leading to inaccurate anticipating, or perhaps more truthfully, excellent deception [30][31][32][33]. Anticipation is also inhibited when probabilistic information is incongruent with the event. ...
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Elite sport offers a suitable setting to understand the ability to anticipate future events—a phenomenon that is central to animal life. Critically, however, whilst anticipation in sport has been studied for several decades, there have been few attempts to understand its development throughout childhood and adolescence. Additionally, whilst it is widely acknowledged that the need to anticipate emerges from temporal pressure, there has been no effort to understand the nonlinear effect that temporal demands have on the development of anticipatory skill. This is important as its consequences have different implications for sports authorities compared to an individual player. To bridge the gap in our understanding, this article draws attention to the mathematical concepts of concavity and convexity to explain the nonlinear relationship between temporal demands and the development of anticipatory skill. This viewpoint has implications for the design of junior sport, including the modification of rules, which has gained worldwide interest in recent years.
... This is problematic as it appears intuitive to consider that disguise is replete within experts' actions and likely replete within their typical actions in order to limit opponents' ability to develop grip. This is evidenced by the recurrent finding that both skilled and less-skilled players demonstrate success that is often significantly above chance levels when anticipating non-deception [7,38,39,[44][45][46][47]. This emphasises the need for experts to regularly employ disguise within their actions if they are to succeed against expert opponents. ...
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Expert performers in fast-ball and combat sports continuously interact with their opponents and, if they are to be successful, adapt behaviour in order to gain an advantage . For example, disguise and deception are recognised as skilful behaviours that are employed to disrupt an opponent’s ability to successfully anticipate their actions. We contend that such skilled behaviour unfolds during the interaction between opposing players, yet typical research approaches omit and/or artificially script these interactions. To promote the study of skilled behaviour as it emerges during competitive interactions, we offer an account informed by contemporary ecological perspectives for shaping investigation into how deception and disguise can be used to gain an advantage over an opponent and the challenges it poses to anticipation. We propose that each player attempts to develop maximum grip on the interaction through exploiting information across multiple timescales to position themselves as to facilitate openness to relevant affordances. The act of deception can be understood as offering a misleading affordance that an opponent is invited to act on, imposing a significant challenge to an opponent’s ability to attain grip by manipulating the information available. Grounded in our ecological perspective, we emphasise the need for future investigation into: (1) the role of disguise for disrupting anticipation; (2) how deception can be employed to gain an advantage by manipulating information on multiple timescales, before detailing; (3) how opposing performers go beyond merely exploiting information and actively elicit information to deal with deception and disguise during an interaction.
... fMRI has high spatial resolution and has been widely used in cognitive neuroscience, psychology, and sports science. In order to explore exercise-induced brain plasticity, researchers have done many experiments with elite athletes as subjects (Babiloni et al., 2010;Pezzulo et al., 2010;Chang et al., 2011;Bishop et al., 2013;Callan and Naito, 2014;Kim et al., 2014;Naito and Hirose, 2014). Most of these studies adopt the expert-novice paradigm, aiming to compare the differences in brain plasticity between athletes and non-athletes or novices. ...
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This study investigated the differences in morphometry and functional plasticity characteristics of the brain after long-term training of different intensities. Results showed that an aerobic group demonstrated higher gray matter volume in the cerebellum and temporal lobe, while an anaerobic group demonstrated higher gray matter volume in the region of basal ganglia. In addition, the aerobic group also showed significantly higher fractional amplitude of low-frequency fluctuation (fALFF) and degree centrality (DC) in the motor area of the frontal lobe and parietal lobe, and the frontal gyrus, respectively. At the same time, the anaerobic group demonstrated higher fALFF and DC in the cerebellum posterior lobe (family-wise error corrected, p < 0.01). These findings may further prove that different brain activation modes respond to different intensities of physical activity and may help to reveal the neural mechanisms that can classify athletes from different intensity sports.
... Note that the activity of the motor system is not exactly identical between observing and executing an action-if this were the case, then a person would move every time they observed another person acting (Babiloni et al., 2016(Babiloni et al., , 2017. Brain regions rich in mirror neurons show increased activation when anticipating the opponent's movements in soccer (Bishop et al., 2013). ...
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The key to action control is one’s ability to adequately predict the consequences of one’s actions. Predictive processing theories assume that forward models enable rapid “preplay” to assess the match between predicted and intended action effects. Here we propose the novel hypothesis that “reading” another’s action intentions requires a rich forward model of that agent’s action. Such a forward model can be obtained and enriched through learning by either practice or simulation. Based on this notion, we ran a series of studies on soccer goalkeepers and novices, who predicted the intended direction of penalties being kicked at them in a computerized penalty-reading task. In line with hypotheses, extensive practice in penalty kicking improved performance in penalty reading among goalkeepers who had extensive prior experience in penalty blocking but not in penalty kicking. A robust benefit in penalty reading did not result from practice in kinesthetic motor imagery of penalty kicking in novice participants. To test whether goalkeepers actually use such penalty-kicking imagery in penalty reading, we trained a machine-learning classifier on multivariate fMRI activity patterns to distinguish motor-imagery-related from attention-related strategies during a penalty-imagery training task. We then applied that classifier to fMRI data related to a separate penalty-reading task and showed that 2/3 of all correctly read penalty kicks were classified as engaging the motor-imagery circuit rather than merely the attention circuit. This study provides initial evidence that, in order to read our opponent’s action intention, it helps to observe their action kinematics, and use our own forward model to predict the sensory consequences of “our” penalty kick if we were to produce these action kinematics ourselves. In sum, it takes practice as a penalty kicker to become a penalty killer.
... Another area to examine is the brain activity that takes place in various brain regions when making quick decisions under time pressure, compared to analytical decisions when more time is available (Basevitch et al., 2020). With the use of fMRI and consideration of the expert-novice paradigm, brain activity (i.e., spatial and temporal activation of brain areas) can be examined and linked to various DM-related processes, such as anticipation and detection of deceptive actions (Bishop et al., 2013). However, fMRI measures are less ecologically valid than typical EEG measures, and researchers using fMRI will be required to use video-based paradigms (or similar lab-based methods). ...
Decision-making (DM) has been studied from two main perspectives: cognitive and ecological. Findings indicate that experts have advanced DM skills that enhance performance. The underlying mechanisms of DM skills relate to the attention and anticipation capacities to function without interruption under pressure of time and to counter various sources of stress (e.g., self-regulation and coping strategies). There are still many questions that must be addressed to fully account for the DM process and apply the findings in a real-world environment. The most urgent questions relate to the neurophysiological mechanisms underlying DM, team DM processes, training and measuring DM, making creative decisions, and comprehending the process of coaches’ DM during competitive conditions and other real-life situations.
... The first is the prediction of the agent action outcome, the other of what the agent will do subsequently (i.e., the upcoming motor act). Examples of outcome prediction may be taken from studies of tennis, basketball, baseball, rugby, badminton (see Bishop et al., 2013), most of them using temporal occlusion paradigms. This type of paradigm consists of presenting a dynamic stimulus interrupted at different delays from its onset. ...
While it is well documented that the motor system is more than a mere implementer of motor actions, the possible applications of its cognitive side are still under-exploited, often remaining as poorly organized evidence. Here, we will collect evidence showing the value of action observation treatment (AOT) in the recovery of impaired motor abilities for a vast number of clinical conditions, spanning from traumatological patients to brain injuries and neurodegenerative diseases. Alongside, we will discuss the use of AOT in the maintenance of appropriate motor behavior in subjects at risk for events with dramatic physical consequences, like fall prevention in elderly people or injury prevention in sports. Finally, we will report that AOT can help to tune existing motor competencies in fields requiring precise motor control. We will connect all these diverse dots into the neurophysiological scenario offered by decades of research on the human mirror mechanism, discussing the potentialities for individualization. Empowered by modern technologies, AOT can impact individuals' safety and quality of life across the whole lifespan.
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Decision-making is an advanced cognitive function that promotes information processes in complex motor situations. In recent years, many neuroimaging studies have assessed the effects of long-term motor training on athletes’ brain activity while performing decision-making tasks, but the findings have been inconsistent and a large amount of data has not been quantitatively summarized until now. Therefore, this study aimed to identify the neural mechanism of long-term motor training affecting the decision-making function of athletes by using activation likelihood estimation (ALE) meta-analysis. Altogether, 10 studies were included and comprised a total of 350 people (168 motor experts and 182 novices, 411 activation foci). The ALE meta-analysis showed that more brain regions were activated for novices including the bilateral occipital lobe, left posterior cerebellar lobe, and left middle temporal gyrus (MTG) in decision-making tasks compared to motor experts. Our results possibly suggested the association between long-term motor training and neural efficiency in athletes, which provided a reference for further understanding the neural mechanisms of motor decision-making.
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This meta-analysis integrates 296 effect sizes reported in eye-tracking research on expertise differences in the comprehension of visualizations. Three theories were evaluated: Ericsson and Kintsch’s (Psychol Rev 102:211–245, 1995) theory of long-term working memory, Haider and Frensch’s (J Exp Psychol Learn Mem Cognit 25:172–190, 1999) information-reduction hypothesis, and the holistic model of image perception of Kundel et al. (Radiology 242:396–402, 2007). Eye movement and performance data were cumulated from 819 experts, 187 intermediates, and 893 novices. In support of the evaluated theories, experts, when compared with non-experts, had shorter fixation durations, more fixations on task-relevant areas, and fewer fixations on task-redundant areas; experts also had longer saccades and shorter times to first fixate relevant information, owing to superiority in parafoveal processing and selective attention allocation. Eye movements, reaction time, and performance accuracy were moderated by characteristics of visualization (dynamics, realism, dimensionality, modality, and text annotation), task (complexity, time-on-task, and task control), and domain (sports, medicine, transportation, other). These findings are discussed in terms of their implications for theories of visual expertise in professional domains and their significance for the design of learning environments.
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Abstract We examined whether soccer players with varying levels of perceptual-cognitive expertise can be differentiated based on their engagement in various types and amounts of activity during their development. A total of 64 participants interacted with life-size video clips of 11 versus 11 dynamic situations in soccer, viewed from the first-person perspective of a central defender. They were required to anticipate the actions of their opponents and to make appropriate decisions as to how best to respond. Response accuracy scores were used to categorise elite players (n = 48) as high- (n = 16) and low-performing (n = 16) participants. A group of recreational players (n = 16) who had lower response accuracy scores compared to the elite groups acted as controls. The participation history profiles of players were recorded using retrospective recall questionnaires. The average hours accumulated per year during childhood in soccer-specific play activity was the strongest predictor of perceptual-cognitive expertise. Soccer-specific practice activity during adolescence was also a predictor, albeit its impact was relatively modest. No differences were reported across groups for number of other sports engaged in during development, or for some of the key milestones achieved. A number of implications for talent development are discussed.
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There are several eye fields in the primate frontal cortex. The number and location of these oculomotor control zones remain controversial, especially in the human brain. In the monkey, the frontal eye field (FEF) is located in the rostral bank of the arcuate sulcus at approximately the level of the posterior end of the sulcus principalis, the supplementary eye field (SEF) is located on the dorsomedial frontal cortex, and the cingulate eye field (CEF) in the dorsal bank of the cingulate sulcus. In the human frontal cortex, the location of the FEF varies depending on the method used, electrical stimulation or functional neuroimaging, to establish it. Some investigators have argued that the SEF is located on the medial wall of the frontal lobe but its presumed location remains controversial. The location of the CEF in the human brain is not known. The present article reviews electrophysiological and functional neuroimaging evidence regarding the location of these frontal oculomotor areas in the macaque monkey and human brains and, in light of new findings in the human brain, attempts to reconcile the differences observed in the location of these eye fields using the different techniques. Together, these data suggest the existence of at least four eye fields in the frontal cortex, i.e. the FEF, the SEF, the CEF, and a premotor eye field, and suggest that their anatomical relationships are preserved from monkey to human brain.
The theoretical framework presented in this article explains expert performance as the end result of individuals' prolonged efforts to improve performance while negotiating motivational and external constraints. In most domains of expertise, individuals begin in their childhood a regimen of effortful activities (deliberate practice) designed to optimize improvement. Individual differences, even among elite performers, are closely related to assessed amounts of deliberate practice. Many characteristics once believed to reflect innate talent are actually the result of intense practice extended for a minimum of 10 years. Analysis of expert performance provides unique evidence on the potential and limits of extreme environmental adaptation and learning.
We review contemporary research focusing on expertise and expert performance in sport. The deliberate practice theoretical framework is presented, and the level of investment in purposeful practice needed to reach the elite level in sport is illustrated. We highlight some of the adaptations that occur as a result of extended engagement in practice and training, with particular reference to perceptual-cognitive skills, such as anticipation and decision-making. These psychological adaptations are explained through reference to long-term working memory theory. Finally, the expert performance approach is presented as a guiding framework for studying expertise in sport, and some suggestions for future research are proposed. The study of expertise and expert performance in sport offers a unique source of data that help promote understanding of the factors that constrain human achievement and the extent to which these may be overcome by systematic engagement in practice and training.
The aim of this research was to analyze information processing, decision making and visual search activity of boxers (French boxing) of various levels of expertise (experts, intermediates, and novices) in simulated and video problem-solving situations replicating the natural task demands. Subjects were placed in front of a screen on which a front-viewed filmed boxer, considered as an opponent, carried out different boxing manoeuvres to which they had to respond by manipulating a joystick according to previously learned responses. Two experiments were carried out. The first was used to analyse subjects' responses in situations whose level of complexity varied. Different actions carried out by an opponent (attacks, openings, and feints) were presented in each situation. In simple situations, subjects had to react to one type of manoeuvres only, whereas in complex situations they had to react to a wider variety and choose the appropriate responses. Response accuracy and reaction time were analysed. Results indicated that differences between groups occurred only in complex situations. The responses of expert boxers were more accurate but reaction time was the same in all groups. This experiment was also used to select the appropriate sequences retained for the second experiment, in which the visual behaviour of boxers was analysed by using an Eye Movement Recorder (Nac Eye Mark recorder V) during the test. The spatial (nature, number, frequency of visual fixations, and scan-paths), and the temporal (mean duration of fixation, and total duration of fixation) characteristics of the visual search activity were analysed. Results demonstrated a significant correlation between level of expertise and subjects' visual strategy.
We review contemporary research on perceptual-cognitive expertise in sport and consider implications for those working in the field of applied cognitive psychology. We identify the important perceptual-cognitive skills that facilitate anticipation in sport and illustrate how these skills interact in a dynamic manner during performance. We also highlight our current understanding of how these skills are acquired and consider the extent to which the underlying processes are specific to a particular domain and role within that domain. Next, we briefly review recent attempts to facilitate the acquisition of perceptual-cognitive expertise using simulation training coupled with instruction and feedback on task performance. Finally, we discuss how research on elite athletes can help inform applied cognitive psychologists who are interested in capturing and enhancing perceptual-cognitive expertise across various domains. Copyright © 2010 John Wiley & Sons, Ltd.
Two experiments are described comparing the temporal and spatial characteristics of the anticipatory cues used by expert ( n =20) and novice ( n =35) racquet sport players. In both experiments the perceptual display available in badminton was simulated using film, and display characteristics were selectively manipulated either by varying the duration of the stroke sequence that was visible (Experiment 1) or by selectively masking specific display features (Experiment 2). The subjects* task in all cases was to predict the landing position of the stroke they were viewing. It was found in Experiment 1 that experts were able to pick up more relevant information from earlier display cues than could novices, and this appeared in Experiment 2 to be due to their ability to extract advance information from the playing side arm, in addition to the racquet itself. These differences, it was concluded, were congruent with predictions that could be derived from traditional information-processing notions related to recognition of display redundancy. The roles of different anticipatory cue sources in the independent predictions of stroke speed and direction were also examined, and it was concluded that directional judgments were more dependent on cue specificity than were depth judgments.