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: mc242819@ohio.edu

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

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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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