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J Orthop Res. 2021;1–10. wileyonlinelibrary.com/journal/jor | 1
Received: 30 October 2020 | Revised: 12 February 2021 | Accepted: 21 February 2021
DOI: 10.1002/jor.25014
S P E C I A L I S S U E R E S E A RCH AR T I C L E
Visual cognition associatedwith knee proprioception, time tostability, and sensory integration neural activity after ACLreconstruction
Meredith Chaput1,2 | James A. Onate3 | Janet E. Simon2,4 | Cody R. Criss2 |
Steve Jamison5 | Michael McNally6 | Dustin R. Grooms1,2,4
1Division of Physical Therapy, School of
Rehabilitation & Communication Sciences,
College of Health Sciences and Professions,
Ohio University, Athens, Ohio, USA
2Ohio Musculoskeletal & Neurological
Institute, Ohio University, Athens, Ohio, USA
3Division of Athletic Training, School of
Health and Rehabilitation Sciences, College of
Medicine, The Ohio State University,
Columbus, Ohio, USA
4Division of Athletic Training, School of
Applied Health Sciences and Wellness,
College of Health Sciences and Professions,
Ohio University, Athens, Ohio, USA
5TrueMotion, Boston, Massachusetts, USA
6Tampa Bay Rays Baseball Club, St.
Petersburg, Florida, USA
Correspondence
Meredith Chaput, 1 Ohio University, W290
Grover Center, Athens, OH 45701, USA.
Email: [email protected]
Funding information
The Ohio State University College of
Medicine; National Athletic Trainers'
Association Research and Education
Foundation; National Strength and
Conditioning Association Foundation
Abstract
Visual cognitive ability has previously been associated with anterior cruciate liga-
ment injury and injury risk biomechanics in healthy athletes. Neuroimaging reports
have identified increased neural activity in regions corresponding to visual‐spatialprocessing, sensory integration, and visual cognition in individuals after anterior
cruciate ligament reconstruction (ACLR), indicating potential neural compensatory
strategies for motor control. However, it remains unclear whether there is a re-
lationship between visual cognition, neural activity, and metrics of neuromuscular
ability after ACLR. The purpose of this study was to (1) evaluate the relationship
between visual cognitive function and measurements of neuromuscular control
(proprioception and time to stability [TTS]), isokinetic strength, and subjective
function, and (2) examine the neural correlates of visual cognition between ACLR
(n = 16; time since surgery 41.4 ± 33.0 months) and demographically similar controls
(n = 15). Visual cognition was assessed by the ImPACT visual motor and visual
memory subscales. Outcome variables of proprioception to target knee angle 20°,
landing TTS, strength, and subjective function were compared between groups, and
visual cognition was correlated within groups to determine the relationship be-
tween visual cognition and outcome variables controlled for time from surgery
(ACLR group). The control group had better IKDC scores and strength. Visual
memory and visual motor ability were negatively associated with proprioception
error (r = −0.63) and TTS (r = −0.61), respectively, in the ACLR group but not con-
trols. Visual cognition was associated with increased neural activity in the pre-
cuneus and posterior cingulate cortex in the ACLR group but not control
participants. These data suggest the neural strategy in which ACLR participants
maintain proprioception and stability varies, and may depend on visual cognition
and sensory integration neural activity.
K E YWORD S
ACL, knee, proprioception, visual‐cognition
© 2021 Orthopaedic Research Society. Published by Wiley Periodicals LLC
1 | INTRODUCTION
Prevalence of anterior cruciate ligament (ACL) injuries continues to
rise,1 with the majority occurring through noncontact mechanisms.2
The noncontact injury mechanism can be attributed to a sensor-
imotor prediction error that results in poor neuromuscular control
and knee valgus collapse.3,4 Noncontact injuries occur shortly after
foot contact with the ground during instances of deceleration,
change of direction, pivoting, or landing.2 When an ACL injury occurs,
an athlete's visual attention is generally fixated on a key external
environmental factor such as a sport ball or another player.2 External
visual attention at the time of an ACL injury indicates that visually
mediated cognition (i.e., visual cognition) may influence injury risk
neuromuscular control.
The immediate post‐concussion assessment and cognitive test-
ing (ImPACT) assessment constructs evaluate visual cognition.5
Swanik et al.6 observed that athletes who sustained a noncontact
ACL injury demonstrated lower baseline scores on four ImPACT
composite subscales when compared with uninjured teammates.
Specifically, individuals who sustained an ACL injury demonstrated
the greatest deficit on the visual memory subscale of the ImPACT
assessment at preseason.6 Monfort et al.7 examined how visual
cognitive ability influences biomechanics in healthy individuals in a
soccer ball‐handling 45˚ run‐to‐cut task, reporting that poorer Im-
PACT visual memory scores were associated with greater peak knee
valgus angle.7 Likewise, Herman et al.8 examined the concussion
resolution index (CRI) across three composite indices: reaction
time, complex reaction time (visual memory), and processing speed
to stratify healthy individuals into high versus low neurocognitive
performers. Findings indicated that lower CRI performance was
associated with ACL injury risk landing mechanics of increased
peak vertical ground reaction force (GRF), peak anterior tibial
shear force, knee abduction moment, and knee abduction angle
during an unanticipated landing.8 These studies indicate the po-
tential of visual cognitive abilities to influence ACL injury risk
neuromuscular control, but do not give insight into how injury may
further influence the relationship between visual cognition and
sensorimotor control.
Previous works have indicated that musculoskeletal injuries may
accentuate visual cognitive‐related deficits or dependence for
maintaining neuromuscular control.9 After ACL injury, simple knee
motor control tasks to engage the quadriceps,10,11 complete a supine
heel slide,12 and active joint position sense (AJPS)13 require greater
frontal cortex and visual‐spatial brain region activity. These neural
activity differences may contribute to visually mediated neurocog-
nitive load, reducing postural stability in those with prior injury.14
Changes in neural demands and accompanying functional deficits
after ACL injury are commonly attributed to a disruption in liga-
mentous afferents that maintain both muscular responses and joint
position sense (proprioception) for joint stability.15 However, as-
sessment of proprioception typically involves active or passive
reposition to a target angle and requires patients to “memorize”
their knee joint spatial location that entails working memory.16
Thus, current measurements of proprioceptive deficits might be at-
tributed to the ligamentous afferent disruption or alterations in
sensorimotor and visual cognitive control (particularly, visual mem-
ory) of joint position.
Sensorimotor prediction errors that result in ACL injury occur
during the first 100 ms of foot contact with the ground.17 Al-
terations in visual cognition and associated neural activity may
negatively influence the ability to rapidly stabilize from landing
within this brief time period. A metric that can more accurately
quantify motor coordination that contributes to rapid stabilization
ability is time to stabilization (TTS), a technique that measures the
time taken to regain postural stability after a dynamic task, such as
landing from a single‐leg jump.18,19 TTS is a reliable measure of
lower extremity stability and has been shown to detect deficits in
dynamic stability after ACL injury.18,20 Although longer TTS after
injury is typically attributed to reduced muscle strength, altered
muscle firing,21 and biomechanics, the nature of rapid stabilization
could also depend on visual cognitive function, specifically visual
motor speed.
The current study aimed to investigate the relationships between
neural activity, visual cognitive ability, and sensorimotor function after
ACL reconstruction (ACLR), relative to healthy controls, and address
gaps in knowledge specific to the contribution of visual cognition to
proprioception and dynamic stability after ACLR. Specifically, the aims
of this study were to (1) evaluate the relationship between visual
cognitive processing and assessments of sensorimotor control (pro-
prioception and TTS) in ACLR individuals, relative to similar demo-
graphic controls, and (2) determine the neural correlates of visual
cognitive function during knee motor control between ACLR individuals
and demographically similar controls.
2 | METHODS
2.1 | Participants
This case‐control study enrolled 16 individuals with a history of left
unilateral primary ACLR (6 male, 21.5 ± 2.6 years, 69 ± 15.9 kg,
Tegner 7.4 ± 1.1, time since surgery 41.4 ± 33.0 months, 13 ham-
string, 3 bone patella‐tendon bone grafts) and 15 healthy controls
(6 male, 22.9 ± 3.03 years, 70.9 ± 14.9 kg, Tegner 7.5 ± 1.1) aged 18
to 35 years. ACLR participants demonstrated MRI compliance, time
since surgery: 6 months to 5 years, a Tegner activity score ≥6, and
they were cleared for sport participation by their surgeon. Control
participants demonstrated similar demographics (age, mass, and
physical activity level), reported no history of lower extremity injury,
and were MRI compliant. Individuals with right extremity, bilateral
ACL injury and/or revision surgery were excluded. There was no
significant difference between groups or between graft types for age,
mass, or activity level (p > .05). The current study was approved by
The Ohio State University Biomedical Sciences Institutional Review
Board and informed consent was obtained before participant
enrollment.
2 | CHAPUT ET AL.
2.2 | Measurement of cognitive function
ImPACT (ImPACT Applications, Inc.) was used to assess neurocognitive
function and was administered in a private office/laboratory.5 The Im-
PACT is a reliable22 computerized assessment that aims to evaluate
neurocognitive ability on six modules: working memory, design memory,
X's and O's, symbol matching, color matching, and three letters. Four
subscale composite scores to quantify verbal memory, visual memory,
reaction time, and visual motor speed ability are generated on the basis
of the six modules.22 Reliability and ceiling effects have been established,
with the visual memory composite score being moderately reliable
(r= .53), a ceiling score of 100 (1.6% of scores at ceiling), and a visual
motor composite score being the most reliable (r= .69) with a ceiling
score of 52.9 (0.5% of scores at ceiling).23 For either visual cognitive
ImPACT composite score, higher scores indicate better performance.
Previous literature demonstrates increased injury risk biomechanics and
ACL injury risk in healthy athletes with lower ImPACT performance,
specifically on subscales related to visual cognition (visual memory and
visual motor subscales).6–8 ACLR may further accentuate visual cognitive
deficits and/or dependence on vision for sensorimotor integration;
therefore, the visual memory and visual motor subscales were used in
analyses. The visual memory construct aims to assess visual attention,
scanning, and memory. The visual motor construct aims to evaluate re-
action and/or anticipatory responses to visual stimuli and integrates
components of decision‐making, working memory, and learning.
2.3 | Measurement of proprioception
Knee proprioception by AJPS24 was measured using an isokinetic dy-
namometer (Biodex, System 3). Participants were seated and strapped
into the dynamometer with their hips and contralateral (right) knee
flexed to 90° and the involved (left) knee flexed to 45°, blindfolded, and
ears covered. Participants were instructed to straighten their left ex-
tremity from the starting angle of 45° to the target angle of 20° and
asked to remember that knee position. The participants' knee was then
flexed back to 45° and supported by the dynamometer. Participants
then actively returned to the 20° target angle and hit a button to lock
the dynamometer in place when they believed to have reproduced the
target angle. Proprioceptive error was determined by the absolute
difference from reproduced angle from the target 20°. Each re-
production trial was preceded by the target acquisition trial for a total
of four trials, with the average absolute error of the trials used for
statistical analysis.
2.4 | Measurement of time to stability
The maximal jump height for each participant was determined on the
basis of a standing vertical jump. Participants were instructed to
stand beneath a Vertec (Vertec Power Systems) on both feet and
complete a maximum vertical jump touching the highest rung pos-
sible. Technique for vertical jump (countermovement, etc.) was not
restricted. The peak height jumped of three successful trials was
recorded and used for the following methods. After maximal
jump height was established, the Vertec was adjusted to 50% of the
maximal height determined by the rung that was halfway between
the baseline standing reach and maximal jump height. Participants
stood behind a mark on the floor 70 cm away from the center of the
landing force platform recording at 1000 Hz (Model 4060 NC; Bertec
Inc). They were instructed to complete a forward bipedal jump to-
ward the platform, touch the previously set rung of the Vertec with
one hand, and land on their left foot on the force platform (Figure 1).
Upon landing, participants placed their hands on their hips as fast as
possible and maintained balance for 10 seconds (s).20 If the partici-
pant missed the Vertec target height, was unable to land without
stepping, or employed other measures to regain balance that re-
quired putting the other foot on the ground or stepping off the force
plate, the trial was omitted. Three successful trials were completed
for the left (involved) lower extremity of each participant. Partici-
pants completed at minimum two practice trials.
TTS uses the triplanar GRF to determine dynamic postural sta-
bility as the time it takes for the landing GRF to stabilize. Raw GRF
data were filtered with a second‐order dual low‐pass 30 Hz filter.
TTS is calculated using GRF from a 10 s window, starting at maximal
resultant GRF. Horizontal range variation was determined as mini-
mum rectified anterior–posterior (AP) and medial–lateral (ML) GRF
from the last half of the 10 s window of interest. An unbounded
F IGURE 1 Time to stability assessment [Color figure can be viewed at wileyonlinelibrary.com]
CHAPUT ET AL. | 3
third‐order polynomial was fitted to each of the AP and ML com-
ponents of the GRF. TTS for each GRF component is the point at
which the unbounded third‐order polynomial transects the hor-
izontal range variation.19 The root of the summed squared TTS from
AP and ML GRF was then calculated and used for analysis.20
2.5 | MRI paradigm and data acquisition
Scans were completed on a 3.0‐T MAGNETOM (Siemens AG) scanner
using a 12‐channel head coil. Each session consisted of a structural
T1‐weighted image, followed by a functional scan. Blood oxygen level‐dependent functional acquisition consisted of four blocks of 30 s of knee
flexion/extension (beginning at 45º of flexion to full terminal extension)
interleaved with five blocks of rest periods.10 To normalize motor per-
formance and minimize head motion, participants were temporally cued
using an auditory metronome paced at 1.2Hz during each movement
block.25 Furthermore, the use of an ankle dorsiflexion splint was placed
on the left ankle to assure that the only joint movement was from the
knee. Each functional session included 90 whole‐brain gradient echo-
planar scans: TR=3000ms; TE =28ms; field of view=220mm; slice
thickness =2.5mm; voxel size = 2.5mm3 for 55 slices.10
2.6 | Image processing and neuroimaging dataanalysis
Preprocessing fMRI data using software package functional magnetic
resonance imaging of the brain software library (FSL) consisted
of brain extraction, MCFLIRT motion correction, Gaussian kernel
FWHM 5mm spatial smoothing, and mean‐based intensity normal-
ization of all volumes.26–30 Independent Component Analysis‐basedstrategy for Automatic Removal of Motion Artifacts was used to
further denoise and reduce motion‐induced signal.31,32 After motion
artifact denoising, fMRI preprocessing included high‐pass filtering at
90 Hz.30 All T1‐weighted three‐dimensional structural images and
standard Montreal Neurological Institute and Hospital coordinate sys-
tem 152, 2mm space were extracted using FSL's brain extraction tool
and co‐registered with functional images using nonlinear image regis-
tration.26,27 Subject level rest versus move contrasts and group‐levelneural correlate analysis on the demeaned visual memory and visual
motor subscale scores were completed with p < .05 cluster corrected
for multiple comparisons and z> 3.1 to identify regions of activation
during knee motor control that were groupwise correlated to visual
motor and visual memory composite subscales.
2.7 | Self‐report function
The International Knee Documentation Committee (IKDC) was
completed. The IKDC is a reliable self‐reported functional scale after
ACL injury and is scored from 0 to 100 points (higher score indicated
greater self‐perceived function).33,34
2.8 | Isokinetic strength assessment
Isokinetic knee extension strength was measured with participants
seated on the dynamometer, straps crossing the chest and upper
thighs, and hips and knees flexed to 90°. Participants performed a
standardized warm‐up consisting of five isokinetic contractions at
60°/second.35 Limb symmetry index (LSI) was calculated ([Involved
Limb/Uninvolved Limb] x100) for strength. For control participants,
the involved extremity was the left lower extremity to mimic the
ACLR group.
2.9 | Statistical analysis
Six independent samples t test was used to compare means of all
dependent variables (IKDC, strength, ImPACT subscales, AJPS, and
TTS) between groups (ACL vs. control). For controls, Pearson's cor-
relation (r) was used to determine the relationship between visual
memory composite scores with AJPS, IKDC, and strength. Also, vi-
sual motor composite scores were correlated with TTS, IKDC, and
strength for control participants. Partial correlations controlling for
time since surgery were used to examine the relationship for the
same ImPACT visual‐cognitive subscales with AJPS, TTS, IKDC, and
strength for ACLR participants. Alpha was at 0.05 for all analyses
with no correction, as these results are exploratory in nature. Cor-
relations were interpreted as low (0.1–0.40), moderate (0.41–0.6),
and strong (0.61–1.0) associations.36
3 | RESULTS
One control participant did not complete the IKDC ques-
tionnaire and two did not complete the AJPS or isokinetic strength
assessments due to equipment malfunction or missed data collection.
As a result, correlations for these variables were completed with 14
and 13 individuals, respectively. One ACLR participant did not
complete the strength assessment; therefore, 15 ACLR participants
were included in strength analyses.
3.1 | ACLR versus controls comparisons
When comparing between groups, the control participants demon-
strated better IKDC scores (p < .001) and isokinetic strength LSI
(p = .021), with no difference in visual motor composite score, visual
memory composite score, AJPS, or TTS (p > .05) (Table 1).
3.2 | ACLR and control correlations
For the ACLR participants, partial correlations indicate that higher
performance on visual memory composite scores was strongly as-
sociated (r = −0.63, p = .02) with lower absolute AJPS error (better
4 | CHAPUT ET AL.
proprioception) (Table 2, Figure S1). In addition, higher performance
on the visual motor composite score was strongly associated
(r = −0.61, p = .03) with better TTS performance (decreased time to
stabilize) (Table 3, Figure S2). There were no significant correlations
in controls between any outcome variables (p > .05, Figures S3 and
S4). Visual memory and visual motor scores were not associated
with IKDC or isokinetic strength LSI for either group (p > .05,
Tables 2 and 3).
3.3 | Neural activity associated with visualcognitive function
In ACLR participants, brain regions correlated with visual memory
function were the right precuneus and posterior cingulate gyrus (PPC)
(p< .001), and visual motor function was correlated with right precuneus
activity (p= .022). There were no neural correlates with either measure
of visual cognitive function in control participants (Table 4, Figure 2). As
this was a neural correlate identification analysis, the effect size (r value)
between neural activity and visual cognitive function is not reported to
avoid circularity (effect size and voxel selection are not independent). A
follow‐up validation study is required to estimate effect size with iden-
tified regions.37
4 | DISCUSSION
The current study aimed to evaluate the relationship between
visual cognitive processing and assessments of sensorimotor
control in individuals with a history of ACLR and demographically
similar controls. Despite no between‐group differences for visual
cognition, higher visual motor and visual memory composite
scores were associated with decreased time to stabilize and less
proprioceptive error, respectively, in the ACLR cohort only. No
such relationship was present in the control group. In addition,
there was no relationship between either visual motor or visual
memory ability and isokinetic strength or IKDC in either group.
Neural correlates of visual cognitive function were examined
during an involved (left) knee motor task in each cohort to de-
termine if a neural mechanism may afford visual cognition to
functionally compensate for the afferent deficits of ACL re-
construction. Visual memory and visual motor composite scores
were associated with neural activity within the precuneus and
posterior cingulate cortex in the ACLR group, but there were no
neural correlates for the controls. These data indicate that ACLR
may induce unique neuroplasticity that results in visual cognition
contributing to proprioception and dynamic stability to a degree
that healthy controls do not require.
TABLE 1 Mean ± standard deviations for major outcomes
ACLR (mean ± SD) Control (mean ± SD) p Value
IKDC 86.3 ± 11.02 (n = 16) 98.7 ± 2.00 (n = 14) p < .001
Isokinetic quadriceps symmetry (LSI%) 83.01 ± 17.2 (n = 14) 95.8 ± 7.41 (n = 13) p = .021
Visual motor composite score 41.5 ± 5.8 (n = 16) 43.1 ± 4.78 (n = 15) p = .347
Visual memory composite score 72.8 ± 18.5 (n = 16) 75.67 ± 12.13 (n = 15) p = .141
AJPS (degrees error) 3.8 ± 1.63 (n = 16) 4.3 ± 1.17 (n = 13) p = .117
TTS (seconds) 3.0 ± 0.58 (n = 16) 3.0 ± 0.45 (n = 15) p = .713
Note: Bold text represents statistically significant differences.
Abbreviations: ACLR, anterior cruciate ligament reconstruction; AJPS, active joint position sense; IKDC, International Knee Documentation Committee;
LSI, limb symmetry index; TTS, time to stability.
TABLE 2 Visual memory composite score correlates
AJPS IKDC Isokinetic strength
ACLR r = −.633 r = −.028 r = −.112
p = .02 p = .929 p = .716
n = 16 n = 16 n = 14
Controls r = .34 r = .247 r = −.233
p = .256 p = .394 p = .445
n = 13 n = 14 n = 13
Note: r, bivariate (Pearson) correlation for controls. Partial correlations
controlling for time since ACLR surgery. Bold text represents statistically
significant findings.
Abbreviations: ACLR, anterior cruciate ligament reconstruction; AJPS,
active joint position sense; IKDC, International Knee Documentation
Committee Subjective Knee Evaluation Form.
TABLE 3 Visual motor composite score correlates
TTS IKDC Isokinetic strength
ACLR r = −.610 r = −.242 r = −.086
p = .027 p = .426 p = .781
n = 16 n = 16 n = 14
Controls r = −.042 r = .219 r = .277
p = .881 p = .451 p = .359
n = 15 n = 14 n = 13
Note: r, bivariate (Pearson) correlation for controls. Partial correlations
controlling for time since ACLR surgery. Bold text represents statistically
significant findings.
Abbreviations: ACLR, anterior cruciate ligament reconstruction; IKDC,
International Knee Documentation Committee Subjective Knee
Evaluation Form; TTS, time to stability.
CHAPUT ET AL. | 5
4.1 | Visual cognition as a compensatorymechanism to preserve proprioception after ACLR
Proprioception is the unconscious ability of the nervous system to
integrate afferent signals to detect location of a joint in space.38
Previous literature suggests that ACL rupture results in proprio-
ceptive deficits incompletely recovered with reconstructive surgery
and subsequently results in greater error when assessed clinically as
compared with healthy controls. Assessments of proprioception, such
as AJPS, require cognitive attention and memory concentrated to the
joint position, limiting isolation of somatosensory contributions to
proprioception, which is the intended goal of the assessments.38 Our
data demonstrate no statistical difference in proprioception between
ACLR and control participants, contradicting a previous meta‐analysisthat found control participants on average have 0.35° less error
(better joint position sense) than those with ACLR.39 Another meta‐analysis evaluated proprioceptive ability between ACLR and uninjured
limbs and found greater error (0.23°) in reconstructed than in con-
tralateral knees.24 Regardless of the graft type, proprioceptive ability as
detected by active, passive, or detection of passive movement appears
to recover by 6 months after surgery as compared with the uninjured
extremity.40 However, in these meta‐analyses, the average proprio-
ceptive error difference between groups or limbs does not exceed the
standard error of the measurement (1.2°−1.7°), indicating lack of clinical
significance. The lack of group differences in our study, relative to the
meta‐analyses, is likely attributed to the longer time since surgery
(41.4 ± 33.0 months), as proprioceptive deficits are most evident
6 months or sooner after ACLR.
Our data indicate that visual memory ability may provide a
means to normalize proprioception as assessed by AJPS in those with
TABLE 4 Brain activity associated with visual memory and visual motor ImPACT subscales in ACLR group
Peak MNI Voxel
Cluster index Brain regions Voxel p Value x y z Z stat‐max
Knee motor control neural activity associated with visual motor composite score
1 Precuneus, posterior
cingulate gyrus
244 .00153 8 −56 22 5.48
Knee motor control neural activity associated with visual motor composite score
1 Precuneus 525 .0223 20 −52 22 3.83
Note: Regions of brain activity are reported that were identified in FSLeyes with the Harvard‐Oxford Cortical & Subcortical Structural atlas and\or the
Cerebellar Atlas in MNI152 space after normalization with FNIRT and with FSL tool atlasquery.
Abbreviations: ACLR, anterior cruciate ligament reconstruction; FMRIB, Functional Magnetic Resonance Imaging of the Brain; FNIRT, FMRIB's nonlinear
image registration tool; FSL, FMRIB Software Library; MNI, Montreal Neurological Institute and Hospital coordinate system.
F IGURE 2 ACLR task‐based neural activity associated with visual memory and visual motor ImPACT composite scores. Color barscorrespond to z values for raw data. Blue shade represents neural activity associated with visual memory ability (precuneus and posteriorcingulate gyrus) and red orange represents neural activity associated with visual motor ability (precuneus). A, anterior; ACLR, anterior cruciateligament reconstruction; L, left; P, posterior; R, right [Color figure can be viewed at wileyonlinelibrary.com]
6 | CHAPUT ET AL.
ACLR. Those with a history of ACLR and better visual memory ability
may allow for enhanced internal visualization (i.e., memorization) of
joint position, thus aiding in target angle reproduction. This corre-
sponds to the methodology of assessing AJPS as well as the aim of
the visual memory ImPACT score, which requires conscious cognitive
attention to establish spatial position. This finding highlights the
ongoing limitations with isolating proprioception with a clinical test
and the inability to ascribe purely the afferent neural pathway to
AJPS acuity. The afferent disruption from the ACL injury may cause
patients to utilize visual cognition to assist with knee‐related sen-
sorimotor function, as a significant correlation was present for only
the ACLR group. The lack of prior studies not controlling for visual
cognitive abilities as a means to compensate for ACLR disrupted
afferents to maintain proprioception may explain the mixed results
and small effect sizes of prior joint position sense studies.41
4.2 | Visual cognition as a compensatorymechanism to preserve stability after ACLR
TTS is a measure of dynamic postural stability and it evaluates the
ability of an individual to quickly gain control after a dynamic
movement. A previous study in Division I female athletes20 found
that ACLR participants took 0.11 s longer (2.01 ± 0.15 s) to stabilize
than controls (1.90 ± 0.07 s) and concluded that dynamic postural
control deficits existed despite all participants having returned to full
sport participation (average 2.5 years post‐surgery).20 We found no
difference between groups for TTS; however, both of our cohorts
took longer to stabilize (Table 1) than those in Webster and
Gribble,20 potentially because our cohort ranged from competitive
collegiate to high‐level reactional athletes rather than all elite‐levelcollege athletes. The longer TTS in our cohort could also be sec-
ondary to the calculation. Webster employed an average ± 3 stan-
dard deviations body weight across all trials to establish the HRVL
(threshold to determine when stability was achieved), whereas we
calculated the HRVL within each trial as originally described by Ross
et al.,19 as we did not complete as many trials (3 vs. 10)20 to take an
average from. Thus, our stability threshold may have been lower
requiring a longer TTS.
Although no group differences in TTS were present, visual cog-
nition (visual motor composite score) was only correlated to TTS in
the ACLR group. This suggests that although functional performance
was similar between groups, the mechanisms for rapid stabilization
potentially differ between ACLR and healthy athletes, with visual
motor processing contributing to stabilization ability only in those
with ACLR history. Afferent receptors within the knee joint and
adjacent musculature detect joint position through both rapid and
slow mechanisms.15 When performing the TTS task, the single‐leglanding requires rapid afferent transmission for detection of joint
position to stabilize after landing. The emphasis during visual motor
ImPACT testing is speed of motor response to a sensory stimulus.
Therefore, the overall goal of quick sensory integration to produce a
motor action is representative in both the visual motor score as well
as the TTS assessment. Potentially secondary to the disrupted af-
ferent signals from the ACLR knee, more reliance on rapid visual
motor processing is required to achieve TTS to the level of healthy
controls. This may result in participants with an ACLR to engage in a
different neural control strategy compensating with visual cognition
to maintain dynamic postural control.42 Our findings coincide with a
previous investigation that patients with ACLR engage different
components of cognition for gait adaptation as compared with con-
trols, allowing them to preserve or even enhance function potentially
via altered cognition or other compensations for motor control.42
4.3 | Neural activity associated with visualcognition
The neural correlate analysis demonstrated that those with ACLR
had higher activity in the PCC when engaged in knee motor control
that was associated with visual memory and visual motor scores,
respectively. The precuneus is the medial aspect of the parietal lobe
and is a multi‐modal region for sensory processing, cognition, and
motor control,43 and it demonstrates increased activity during
attention‐demanding tasks requiring visual–somatosensory integra-
tion. Traditionally, the precuneus has been divided on the basis
of functional connectivity into anterior, middle, and posterior re-
gions. Anterior precuneus is connected to the motor cortex, insula,
and superior parietal lobule (somatosensory–motor integration),
middle precuneus to the prefrontal and inferior parietal lobes (cog-
nitive), and the posterior portion, predominantly the location of the
visual cognitive neural correlate, is functionally connected to visual
regions.44 Thus, the specific location of the increased precuneus
activity associated with visual cognition in this study could be spe-
cific to ACL deafferentation reweighting sensory processing toward
increased parietal‐visual processing regions.
After ACLR, increased precuneus neural activity associated with
visual cognition (both included ImPACT subscales) may indicate
sensory integration inefficiency (more neural activity to complete
same task), relative to control participants, which promotes reliance
on visual cognition. During goal‐oriented tasks, precuneus activity
increases with relative complexity, because more sensory informa-
tion is needed for task completion.44 Therefore, PCC and precuneus
activity associated with visual cognition when engaging in a relatively
simple knee movement could provide a neural compensatory path-
way for visual cognition to maintain proprioception and dynamic
stability.45
An alternative hypothesis for heightened precuneus and PCC
activity after ACLR stems from repeated co‐activation between
frontal cortex (cognition) and with knee motor regions, mimicking
standard rehabilitation. The precuneus and PCC are “core hubs” of
the default‐mode network responsible for strong connectivity to the
frontal cortex.44,46 Functional connectivity of the PCC and pre-
cuneus with the medial prefrontal cortex provides motor planning
regions with bodily representation and sensory information.43,47
Thus, the visually cognitive focus on knee motor function during
CHAPUT ET AL. | 7
rehabilitation could depend on internal body representation and
cognitive resources, increasing associated precuneus and PCC ac-
tivity to maintain motor function after ACLR.
5 | IMPLICATIONS
Although the ACLR participants appeared to be similar to controls on
measures of proprioception and TTS, their neural strategy to main-
tain performance was altered. The association of visual cognitive
processing to proprioception and dynamic stability may not only be
secondary to the afferent disruption after ACL injury, but due in
part to how rehabilitation is typically prescribed. Direct visual cog-
nitive attention and visual memory is consistently used throughout
rehabilitation whereby patients are taught movement strategies like
squatting and cutting using internal visual representations of their
knee. Commonly used verbal and visual cues direct attention toward
the injured knee joint, altering how knee motor control typically
functions (with minimal direct visual attention) and potentially
compromising the role of visual cognition when returned to sport,
where visual attention is directed to the environment and not the
knee.48,49 Therefore, the transfer of a movement strategy (such as
jump landing stability) from the controlled clinic to chaotic sport
environment can be limited50 in those with ACLR by the level of
visual cognition they are able to dedicate to the movement, as re-
habilitation encourages visual cognition to be employed to engage in
body movement execution to maintain knee motor control instead of
movement planning based on environmental constraints. Clinicians
may consider integrating various aspects of motor learning or at-
tention manipulation to alter the course of typically allowed com-
pensations after ACLR.48
6 | LIMITATIONS
The small sample size is a limiting factor for broad generalization of
these data; however, the ACLR and control group were matched on
age, sex, activity level, and education status to limit confounds. The
current findings were a part of a secondary analysis from a study
with the primary purpose of investigating neural activity differences
between healthy controls and individuals post ACLR; therefore, an a
priori power analysis was not conducted and the risk of committing a
type 2 statistical error (failure to find a significant difference when
one exists) is possible for the between‐group comparisons. However,
the main findings from our study pertain to the significant within‐group relationships of visual cognition with proprioceptive acuity and
dynamic stability, to better understand how history of ACLR may
result in differential contributions of visual cognition to sensorimotor
control. Another limitation is that we only assessed AJPS at one
target angle and with active reposition. Assessing AJPS or passive
detection of motion at multiple joint angles might result in different
findings.24,39 Furthermore, despite long time duration since surgery,
our cohort was highly active and still engaged in competitive
athletes, which possibly contributed to no group differences. How-
ever, despite a high activity level, the ACLR cohort had lower
strength LSI and IKDC scores, relative to controls.
Future research should consider visual cognitive elements in
movement testing, such as eye tracking or other measures of at-
tention, movement complexity, or dual tasking to better isolate visual
cognitive contributions to sensorimotor control after injury. In ad-
dition, although our metrics were primarily quadriceps‐dominant,
future work should consider integrating hamstring strength and
quadriceps‐to‐hamstring ratio, as alterations in hamstring function
may contribute to neural control changes after injury.51,52 Long-
itudinal investigations are needed to understand the contributions of
visual cognition to postural stability throughout rehabilitation to
return to sport to determine ideal windows for potential adjunctive
interventions to reduce dependence on visual cognition for dynamic
stability. Considering that visual cognitive differences may be pre-
sent before injury or influenced by rehabilitation strategies, future
research should consider evaluating neural activity associated with
cognitively demanding motor control processes before and after
musculoskeletal injury.
7 | CONCLUSION
The findings of this preliminarily investigation implicate visual cog-
nition as a compensatory mechanism to sustain knee proprioception
and dynamic stability after ACLR, potentially through increased
sensory integration neural activity.
ACKNOWLEDGMENTS
The contributing authors have no conflicts of interests correspond-
ing with this manuscript. This study was funded in part by the
National Athletic Trainers' Association Research and Education
Foundation, National Strength and Conditioning Association Foun-
dation, and The Ohio State University College of Medicine. Dr
Grooms has current and ongoing funding support from the National
Institutes of Health/National Center for Complementary and
Integrative Health (R21 AT009339‐02), National Institute of
Arthritis and Musculoskeletal and Skin Diseases (R01 AR076153‐01A1), and the Department of Defense Peer Reviewed Orthopedic
Research Program (OR170266). Opinions, interpretations, conclu-
sions, and recommendations are those of the author and are not
necessarily endorsed by the Department of Defense.
AUTHOR CONTRIBUTIONS
Meredith Chaput and Janet E. Simon contributed to the analysis and
interpretation of data, writing, and revisions of the manuscript.
James A. Onate contributed to manuscript revisions. Cody R. Criss
contributed to the analysis, interpretation of data, and writing. Steve
Jamison contributed to data collection, analysis, and methodology.
Michael McNally made contributions to experimental design, data
collection, and revisions. Dustin R. Grooms contributed to experi-
mental design, conceptualization, analysis, data interpretation,
8 | CHAPUT ET AL.
writing, and revisions. All authors have approved the manuscript for
submission.
ORCID
Meredith Chaput https://orcid.org/0000-0003-2254-8774
Dustin R. Grooms https://orcid.org/0000-0001-6102-8224
REFERENCES
1. Beck NA, Lawrence JTR, Nordin JD, DeFor TA, Tompkins M. ACL
tears in school‐aged children and adolescents over 20 years.
Pediatrics. 2017;139(3):e20161877. https://doi.org/10.1542/peds.
2016-1877
2. Waldén M, Krosshaug T, Bjørneboe J, Andersen TE, Faul O,
Hägglund M. Three distinct mechanisms predominate in non‐contactanterior cruciate ligament injuries in male professional football
players: a systematic video analysis of 39 cases. Br J Sports Med.
2015;49(22):1452‐1460. https://doi.org/10.1136/bjsports-2014-
094573
3. Grooms DR, Onate JA. Neuroscience application to noncontact
anterior cruciate ligament injury prevention. Sports Health. 2016;
8(2):149‐152. https://doi.org/10.1177/19417381156191644. Swanik C. “Buz.” Brains and sprains: the brain's role in noncontact
anterior cruciate ligament injuries. J Athl Train. 2015;50(10):
1100‐1102. https://doi.org/10.4085/1062-6050-50.10.085. Iverson GL, Lovell MR, Collins MW. Interpreting change on ImPACT
following sport concussion. Clin Neuropsychol. 2003;17(4):460‐467.https://doi.org/10.1076/clin.17.4.460.27934
6. Swanik CB, Covassin T, Stearne DJ, Schatz P. The relationship be-
tween neurocognitive function and noncontact anterior cruciate li-
gament injuries. Am J Sports Med. 2007;35(6):943‐948. https://doi.org/10.1177/0363546507299532
7. Monfort SM, Pradarelli JJ, Grooms DR, Hutchison KA, Onate JA,
Chaudhari AMW. Visual‐spatial memory deficits are related to in-
creased knee valgus angle during a sport‐specific sidestep cut.
Am J Sports Med. 2019;47(6):1488‐1495. https://doi.org/10.1177/0363546519834544
8. Herman D, Barth J. Drop‐jump landing varies with baseline neuro-
cognition: implications fro anterior cruciate ligament injury risk and
prevention. Am J Sports Med. 2016;44(9):2347‐2353. https://doi.org/10.1177/0363546516657338
9. Hutchison M, Comper P, Mainwaring L, Richards D. The influence of
musculoskeletal injury on cognition: implications for concussion
research. Am J Sports Med. 2011;39(11):2331‐2337. https://doi.org/10.1177/0363546511413375
10. Grooms DR, Page SJ, Nichols‐Larsen DS, Chaudhari AMW,
White SE, Onate JA. Neuroplasticity associated with anterior
cruciate ligament reconstruction. J Orthop Sports Phys Ther. 2017;
47(3):180‐189. https://doi.org/10.2519/jospt.2017.700311. Lepley AS, Grooms DR, Burland JP, Davi SM, Kinsella‐Shaw JM,
Lepley LK. Quadriceps muscle function following anterior cruciate
ligament reconstruction: systemic differences in neural and mor-
phological characteristics. Exp Brain Res. 2019;237(5):1267‐1278.https://doi.org/10.1007/s00221-019-05499-x
12. Criss CR, Onate JA, Grooms DR. Neural activity for hip‐knee control
in those with anterior cruciate ligament reconstruction: a task‐based functional connectivity analysis. Neurosci Lett. 2020;730:
134985. https://doi.org/10.1016/j.neulet.2020.134985
13. Baumeister J, Reinecke K, Weiss M. Changed cortical activity after
anterior cruciate ligament reconstruction in a joint position para-
digm: an EEG study. Scand J Med Sci Sports. 2008;18(4):473‐484.https://doi.org/10.1111/j.1600-0838.2007.00702.x
14. Miko SC, Simon JE, Monfort SM, Yom JP, Ulloa S, Grooms DR.
Postural stability during visual‐based cognitive and motor dual‐tasks
after ACLR. J Sci Med Sport. Published online. 2020;24:146‐151.https://doi.org/10.1016/j.jsams.2020.07.008
15. Johansson H, Sjölander P, Sojka P. A sensory role for the cruciate
ligaments. Clin Orthop. 1991;268:161‐178.16. Lee H‐M, Cheng C‐K, Liau J‐J. Correlation between proprio-
ception, muscle strength, knee laxity, and dynamic standing
balance in patients with chronic anterior cruciate ligament de-
ficiency. Knee. 2009;16(5):387‐391. https://doi.org/10.1016/j.
knee.2009.01.006
17. Koga H, Nakamae A, Shima Y, et al. Mechanisms for noncontact
anterior cruciate ligament injuries: knee joint kinematics in 10 injury
situations from female team handball and basketball. Am J Sports
Med. 2010;38(11):2218‐2225. https://doi.org/10.1177/03635465
10373570
18. Colby SM, Hintermeister RA, Torry MR, Steadman JR. Lower limb
stability with ACL impairment. J Orthop Sports Phys Ther. 1999;29(8):
444‐454. https://doi.org/10.2519/jospt.1999.29.8.44419. Ross SE, Guskiewicz KM. Time to stabilization: a method for ana-
lyzing dynamic postural stability. Int J Athl Ther Train. 2003;8(3):
37‐39. https://doi.org/10.1123/att.8.3.3720. Webster KA, Gribble PA. Time to stabilization of anterior cruciate
ligament–reconstructed versus healthy knees in National Collegiate
Athletic Association Division I Female Athletes. J Athl Train. 2010;
45(6):580‐585. https://doi.org/10.4085/1062-6050-45.6.58021. Wikstrom EA, Tillman MD, Schenker S, Borsa PA. Failed jump
landing trials: deficits in neuromuscular control. Scand J Med Sci
Sports. 2008;18(1):55‐61. https://doi.org/10.1111/j.1600-0838.
2006.00629.x
22. Schatz P. Long‐term test–retest reliability of baseline cognitive as-
sessments using imPACT. Am J Sports Med. 2010;38(1):47‐53.https://doi.org/10.1177/0363546509343805
23. Gaudet CE, Konin J, Faust D. Immediate post‐concussion and cog-
nitive testing: ceiling effects, reliability, and implications for inter-
pretation. Arch Clin Neuropsychol Off J Natl Acad Neuropsychol. 2020.
https://doi.org/10.1093/arclin/acaa074
24. Kim H‐J, Lee J‐H, Lee D‐H. Proprioception in patients with anterior
cruciate ligament tears: a meta‐analysis comparing injured and un-
injured limbs. Am J Sports Med. 2017;45(12):2916‐2922. https://doi.org/10.1177/0363546516682231
25. Kapreli E, Athanasopoulos S, Papathanasiou M, et al. Lateralization
of brain activity during lower limb joints movement. An fMRI study.
Neuroimage. 2006;32(4):1709‐1721. https://doi.org/10.1016/j.
neuroimage.2006.05.043
26. Jenkinson M, Smith S. A global optimisation method for robust affine
registration of brain images. Med Image Anal. 2001;5(2):143‐156.https://doi.org/10.1016/s1361-8415(01)00036-6
27. Jenkinson M, Bannister P, Brady M, Smith S. Improved optimization
for the robust and accurate linear registration and motion correc-
tion of brain images. Neuroimage. 2002;17(2):825‐841. https://doi.org/10.1016/s1053-8119(02)91132-8
28. Smith SM. Fast robust automated brain extraction. Hum Brain Mapp.
2002;17(3):143‐155. https://doi.org/10.1002/hbm.10062
29. Woolrich MW, Ripley BD, Brady M, Smith SM. Temporal auto-
correlation in univariate linear modeling of FMRI data. Neuroimage.
2001;14(6):1370‐1386. https://doi.org/10.1006/nimg.2001.0931
30. Worsley KJ. Statistical Analysis of Activation Images. Oxford Uni-
versity Press; 2020.
31. Pruim RHR, Mennes M, van Rooij D, Llera A, Buitelaar JK,
Beckmann CF. ICA‐AROMA: a robust ICA‐based strategy for re-
moving motion artifacts from fMRI data. Neuroimage. 2015;112:
267‐277. https://doi.org/10.1016/j.neuroimage.2015.02.064
32. Pruim RHR, Mennes M, Buitelaar JK, Beckmann CF. Evaluation of
ICA‐AROMA and alternative strategies for motion artifact removal
in resting state fMRI. Neuroimage. 2015;112:278‐287. https://doi.org/10.1016/j.neuroimage.2015.02.063
CHAPUT ET AL. | 9
33. Irrgang JJ, Anderson AF, Boland AL, et al. Development and vali-
dation of the international knee documentation committee sub-
jective knee form. Am J Sports Med. 2001;29(5):600‐613. https://doi.org/10.1177/03635465010290051301
34. Irrgang JJ, Ho H, Harner CD, Fu FH. Use of the International Knee
Documentation Committee guidelines to assess outcome following
anterior cruciate ligament reconstruction. Knee Surg Sports
Traumatol Arthrosc Off J ESSKA. 1998;6(2):107‐114. https://doi.org/10.1007/s001670050082
35. Myer GD, Ford KR, Barber Foss KD, Liu C, Nick TG, Hewett TE. The
relationship of hamstrings and quadriceps strength to anterior
cruciate ligament injury in female athletes. Clin J Sport Med Off J Can
Acad Sport Med. 2009;19(1):3‐8. https://doi.org/10.1097/JSM.
0b013e318190bddb
36. Akoglu H. User's guide to correlation coefficients. Turk J Emerg Med.
2018;18(3):91‐93. https://doi.org/10.1016/j.tjem.2018.08.001
37. Kriegeskorte N, Lindquist MA, Nichols TE, Poldrack RA, Vul E. Ev-
erything you never wanted to know about circular analysis, but
were afraid to ask. J Cereb Blood Flow Metab. 2010;30(9):1551‐1557.https://doi.org/10.1038/jcbfm.2010.86
38. Hillier S, Immink M, Thewlis D. Assessing proprioception: a sys-
tematic review of possibilities. Neurorehabil Neural Repair. 2015;
29(10):933‐949. https://doi.org/10.1177/154596831557305539. Relph N, Herrington L, Tyson S. The effects of ACL injury on knee
proprioception: a meta‐analysis. Physiotherapy. 2014;100(3):
187‐195. https://doi.org/10.1016/j.physio.2013.11.00240. Angoules AG, Mavrogenis AF, Dimitriou R, et al. Knee propriocep-
tion following ACL reconstruction; a prospective trial comparing
hamstrings with bone‐patellar tendon‐bone autograft. Knee. 2011;
18(2):76‐82. https://doi.org/10.1016/j.knee.2010.01.00941. Gokeler A, Benjaminse A, Hewett TE, et al. Proprioceptive deficits
after ACL injury: are they clinically relevant? Br J Sports Med. 2012;
46(3):180‐192. https://doi.org/10.1136/bjsm.2010.082578
42. Stone AE, Roper JA, Herman DC, Hass CJ. Cognitive performance
and locomotor adaptation in persons with anterior cruciate ligament
reconstruction. Neurorehabil Neural Repair. 2018;32(6‐7):568‐577.https://doi.org/10.1177/1545968318776372
43. Wenderoth N, Debaere F, Sunaert S, Swinnen SP. The role of
anterior cingulate cortex and precuneus in the coordination of
motor behaviour. Eur J Neurosci. 2005;22(1):235‐246. https://doi.org/10.1111/j.1460-9568.2005.04176.x
44. Zeharia N, Hofstetter S, Flash T, Amedi A. A whole body sensory‐motor gradient is revealed in the medial wall of the parietal lobe.
J Neurosci Off J Soc Neurosci. 2019;39(40):7882‐7892. https://doi.org/10.1523/JNEUROSCI.0727-18.2019
45. Pearson JM, Heilbronner SR, Barack DL, Hayden BY, Platt ML.
Posterior cingulate cortex: adapting behavior to a changing world.
Trends Cogn Sci. 2011;15(4):143‐151. https://doi.org/10.1016/j.tics.2011.02.002
46. Chivukula S, Jafari M, Aflalo T, Yong NA, Pouratian N. Cognition in
sensorimotor control: interfacing with the posterior parietal cortex.
Front Neurosci. 2019;13:140. https://doi.org/10.3389/fnins.2019.00140
47. Xu Y. The posterior parietal cortex in adaptive visual processing.
Trends Neurosci. 2018;41(11):806‐822. https://doi.org/10.1016/j.
tins.2018.07.012
48. Benjaminse A, Gokeler A, Dowling AV, et al. Optimization of the anterior
cruciate ligament injury prevention paradigm: novel feedback techni-
ques to enhance motor learning and reduce injury risk. J Orthop Sports
Phys Ther. 2015;45(3):170‐182. https://doi.org/10.2519/jospt.2015.498649. Gokeler A, Benjaminse A, Hewett TE, et al. Feedback techniques to
target functional deficits following anterior cruciate ligament re-
construction: implications for motor control and reduction of sec-
ond injury risk. Sports Med. 2013;43(11):1065‐1074. https://doi.org/10.1007/s40279-013-0095-0
50. Davids K, Araújo D, Hristovski R, Chow JY. 7 Ecological dynamics
and motor learning design in sport. Published online. 2012:19.
51. Courtney CA, Rine RM. Central somatosensory changes associated
with improved dynamic balance in subjects with anterior cruciate
ligament deficiency. Gait Posture. 2006;24(2):190‐195. https://doi.org/10.1016/j.gaitpost.2005.08.006
52. Courtney C, Rine RM, Kroll P. Central somatosensory changes and
altered muscle synergies in subjects with anterior cruciate ligament
deficiency. Gait Posture. 2005;22(1):69‐74. https://doi.org/10.1016/j.gaitpost.2004.07.002
SUPPORTING INFORMATION
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How to cite this article: Chaput M, Onate JA, Simon JE, et al.
Visual cognition associated with knee proprioception, time to
stability, and sensory integration neural activity after ACL
reconstruction. J Orthop Res. 2021;1‐10.https://doi.org/10.1002/jor.25014
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