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. Author manuscript; available in PMC: 2025 Oct 4.
Published in final edited form as: Arch Phys Med Rehabil. 2022 Jan 6;103(8):1592–1599. doi: 10.1016/j.apmr.2021.12.010

Cerebellar Contributions to Motor and Cognitive Control in Multiple Sclerosis✰✰✰

Nora E Fritz a,b,c,d,e, Erin M Edwards c,e, Chuyang Ye f, Jerry Prince g, Zhen Yang g, Timothy Gressett h, Jennifer Keller a, Emily Myers c, Peter A Calabresi i,j, Kathleen M Zackowski a,b,i
PMCID: PMC12494151  NIHMSID: NIHMS2103821  PMID: 34998712

Abstract

Objective:

To evaluate relationships between specific cerebellar regions and common clinical measures of motor and cognitive function in persons with multiple sclerosis (PwMS).

Design:

Cross-sectional.

Setting:

Laboratory.

Participants:

Twenty-nine PwMS and 28 age- and sex-matched controls without multiple sclerosis (MS) (N=57).

Interventions:

Not applicable.

Main Outcome Measures:

Both diffusion and lobule magnetic resonance imaging analyses and common clinical measures of motor and cognitive function were used to examine structure-function relationships in the cerebellum.

Results:

PwMS demonstrate significantly worse motor and cognitive function than controls, including weaker strength, slower walking, and poorer performance on the Symbol Digit Modalities Test, but demonstrate no differences in cerebellar volume. However, PwMS demonstrate significantly worse diffusivity (mean diffusivity: P=.0003; axial diffusivity: P=.0015; radial diffusivity: P=.0005; fractional anisotropy: P=.016) of the superior cerebellar peduncle, the primary output of the cerebellum. Increased volume of the motor lobules (I-V, VIII) was significantly related to better motor (P<.022) and cognitive (P=.046) performance, and increased volume of the cognitive lobules (VI-VII) was also related to better motor (P<.032) and cognitive (P=.008) performance, supporting the role of the cerebellum in both motor and cognitive functioning.

Conclusions:

These data highlight the contributions of the cerebellum to both motor and cognitive function in PwMS. Using novel neuroimaging techniques to examine structure-function relationships in PwMS improves our understanding of individualized differences in this heterogeneous group and may provide an avenue for targeted, individualized rehabilitation aimed at improving cerebellar dysfunction in MS.

Keywords: Cognition, Cerebellum, Diffusion tensor imaging, Magnetic resonance imaging, Multiple sclerosis, Rehabilitation

Multiple sclerosis (MS) is a complex disease that affects the central nervous system. The cerebellum, a brain region that is critical for both motor and cognitive processing, is a common site for MS-related disability.1,2 As a result, persons with MS (PwMS) experience an array of severely debilitating motor (walking, balance, strength)3 and cognitive4 impairments that dramatically affect quality of life. At present, effective therapies for cerebellar dysfunction in MS are lacking,5 which may be attributed to limited understanding of structure-function relationships within the cerebellum.

The cerebellum is functionally segregated in corticonuclear subcircuits that are integrated within both motor and cognitive networks,6 including specific motor (1–5, and 8) and cognitive (6,7) lobules.7 In MS, conventional magnetic resonance imaging (MRI) studies broadly demonstrate cerebellar pathology as a major determinant of physical and cognitive disability across disease phases.8 Yet, how pathology in specific functional cerebellar regions affects functional performance remains unclear.2 Critical to this study is prior work in MS using diffusion tensor imaging (DTI), a quantitative MRI technique that indirectly assesses myelin content via water mobility along axons9 and is reflected by the primary outcome measure, fractional anisotropy (FA). In MS, decreased cerebellar FA has been linked to slower walking speed10,11 and increased postural sway.12,13 Nonetheless, evidence indicating associations between decreased cerebellar FA and clinical function1 and cognition14 remain inconclusive. FA may not be a reliable marker of myelin content.15–17 Therefore, the utility of other DTI metrics independent of diffusion direction (ie, mean diffusivity [MD]) to interpret underlying MS pathology are critical. Additionally, crossing fibers, which are highly abundant in the cerebellum, have a notable effect on anisotropy analysis in which the axon itself can override myelin integrity.18 Therefore, findings from additional DTI metrics and different neuroimaging tools may strengthen the interpretation of DTI results.19

Despite the need for effective therapies for cerebellar dysfunction in MS, few studies focus on specific functional areas of the cerebellum20 and their links to motor and cognitive impairments. Therefore, the aim of this study was to evaluate microstructural (DTI) and volumetric measures of the cerebellum in PwMS. We used DTI and lobule analyses to evaluate the relationship of specific cerebellar regions to common clinical measures of motor and cognitive function. We hypothesized that (1) diffusivity of the superior cerebellar peduncle (SCP), the primary output of the cerebellum, would be strongly associated with clinical measures of motor performance and (2) volumetric measures of the motor and cognitive lobules would be specifically associated with performance on motor and cognitive tasks, respectively.

Methods

Individuals with relapsing–remitting MS and age- and sex-matched controls without MS enrolled in a larger intervention trial were recruited for this study. PwMS were included if they were ambulatory with or without an assistive device. Participants were excluded if they had experienced MS relapse within 3 months of testing, reported corticosteroid use within 30 days of testing, or reported a history of orthopedic or neurologic conditions that might interfere with testing procedures. All participants were able to follow study-related commands and gave written informed consent. The Institutional Review Boards at both Johns Hopkins Medical Institute and Kennedy Krieger Institute approved the study procedures.

In a single session, demographic information (age, sex, symptom duration, Expanded Disability Status Scale21), cognitive function, and quantitative measures of strength, sensation, lower extremity coordination, balance, and walking were collected. Neuroimaging measures were collected within 3 weeks of this session.

Motor measures

Strength assessment

Maximal voluntary contraction of bilateral hip flexion, hip extension, and hip abduction was assessed with a handheld dynamometera using previous methods from our laboratory.22 The average of 2 trials of each muscle was recorded, and summed strength was calculated from the sum of bilateral hip flexion, extension, and abduction measurements. Strength examination was restricted to hip musculature because our laboratory has demonstrated negative associations between hip weakness and walking impairment in PwMS.23,24 Quantitative strength testing is reliable and valid for PwMS.25

Sensation assessment

Sensation was quantified bilaterally at the great toe using a Vibratron II device.b The Vibratron provides reliable and objective quantitative measures of vibratory sensation in PwMS.25 Participants identified which of 2 rods was vibrating using a 2-alternative forced-choice procedure. The threshold26 from the worse toe was calculated and used for data analysis.

Fall assessment

Participants self-reported a 1-month fall history.

Six Spot Step Test

Participants were instructed to walk as quickly and safely as possible in a crisscross pattern to 6 spots along a 5-m pathway. Each “spot” includes a weighted box that participants kicked away from its original position using the medial and lateral sides of their foot. Participants used only 1 foot to kick all 6 weights, and time was recorded. Participants performed 2 trials with each leg, and the average time of 4 trials was the final score.27 The Six Spot Step Test (SSST) requires lower extremity coordination and is validated in PwMS.28

Romberg Balance Assessment

Participants were asked to balance in 6 different positions adapted from the Romberg and Sharpened Romberg tests.29,30 To progress to the next condition, participants had to stand independently for 30 seconds in the prior condition. Scores were tallied for the number of successful conditions (maximum score of 6), including feet apart–eyes open, feet together–eyes open, feet apart–eyes closed, feet together–eyes closed, feet in tandem–eyes open, and feet in tandem–eyes closed.

Walking measures

Walk velocity

Participants were instructed to walk at their quickest, safe speed across a 20-foot Zeno Walkway,c which records footfalls in real time. Participants completed 6 walking trials across the mat. Average walk velocity for each individual was calculated using a custom MATLAB program.d

Timed 25-foot walk

Participants were instructed to walk at their quickest, safe speed along a flat 25-foot walkway.31 Participants completed 2 walking trials, with the final score calculated as the average of the 2 trials. The timed 25-foot walk (T25FW) has established reliability32 and validity.33

Timed Up and Go

Participants were instructed to stand from a chair, walk 10 feet, turn, walk back, and return to a sitting position in the chair at their quickest and safest speed without running.34 The Timed Up and Go (TUG) is reliable and clinically relevant in MS35 because it incorporates dynamic balance during functional tasks of turning, transitioning, and walking.

Two-minute walk test

Participants were instructed to cover as much distance as possible while walking for 2 minutes. The 2-minute walk test (2MWT) is a feasible alternative to the 6-minute walk test,36 which has established reproducibility and reliability in MS.37

Cognitive measures

Symbol Digit Modalities Test: oral administration

Participants received a key with 9 numbers each corresponding to a symbol and were asked to orally determine the number belonging with a series of symbols using this key. The score is the number of correct answers in 90 seconds. The Symbol Digit Modalities Test (SDMT) is a validated and reliable test in MS to analyze information processing speed38 and is recognized as the single best measure to assess cognition in PwMS under time constraints.4

Structural MRI acquisition

Whole-brain images were collected on the same 3-Tesla Intera scannere for all participants. Two axial whole-brain sequences were acquired, a T2-weighted fluid-attenuated inversion recovery (acquired resolution: 0.9 × 0.9 × 1.0 mm; TE: 365 ms; TR: 4.8 s; TI: 1.6 s; SENSE factor: 1); and a 3-dimenstional magnetization-prepared rapid acquisition of gradient echoes (acquired resolution: 0.8 × 0.8 × 1.2 mm; TE: 6 ms; TR: 10 ms; flip angle: 8°; SENSE factor: 1). Finally, 32-direction diffusion-weighted images were acquired at an isotropic resolution of 2.2 mm.

MRI analysis

Peduncle analysis

We used the diffusion data and an automatic method39 to segment the cerebellar peduncles. The volume, FA, MD, radial diffusivity (RD), and axial diffusivity (AD) were then calculated for each cerebellar peduncle (SCP, middle cerebellar peduncle [MCP], inferior cerebellar peduncle [ICP]), and the right and left sides were averaged for analysis. FA is normalized between 0 and 1; higher FA values indicate more anisotropic diffusion in tissue and a greater degree of white matter integrity. AD indicates the direction of highest diffusivity, which typically coincides with the fiber tract axis.40,41 Animal work suggests that AD may be specific to axonal degeneration, while RD (diffusivity perpendicular to the dominant fiber direction) may be modulated by myelin42 and therefore sensitive to demyelination.43 MD represents an average and is not indicative of direction.

Lobule analysis

We performed fully automated segmentation of the cerebellar lobules.44 Prior volumetric studies in healthy and other clinical populations have identified topographic organization in the cerebellum including discrete motor and cognitive areas7; lobules 1–5 and 8 have been linked to motor function,7 including posture45 and gait coordination.46 Lobules 6 and 7 have been linked to cognition in MS-relevant domains (ie, information processing, working and visuospatial memory).7

Statistical analyses

All analyses were performed in SPSS version 25.f All data were screened for univariate outliers, and assumptions of normality were met; T tests were used to compare cerebellar lobule and peduncle segmentations between PwMS and matched controls. To understand the relationship of cerebellar imaging metrics to performance on clinical measures of motor and cognitive function, the MS and control groups were combined, and Spearman correlations were used to assess the associations among quantitative measures of motor and cognitive function and MRI measures.

Results

Study population

Thirty-one PwMS and 29 age- and sex-matched controls without MS participated in this study. Three participants failed segmentation (n=2 relapsing-remitting MS; n=1 control) because of excess motion in the scan, leaving 29 PwMS and 28 controls for final analysis. There were no significant differences between PwMS and controls for age or sex (table 1).

Table 1.

Demographics, functional measures, and MRI measures among individuals with MS and controls

Control (n=28) Multiple Sclerosis (n=29) P Value
Demographics
Age (y) 51.0±11.7 50.0±11.3 .74
Sex 8 M; 20 F 11 M; 18 F .46
Symptom duration (y) – 12.8±9.9 –
EDSS – 4.0 (1.0–6.5) –
Motor measures
T25FW (s) 4.08±0.717 5.55±2.26 .0020*
TUG (s) 5.75±1.07 7.73±2.30 .0003*
Walk velocity (m/s) 1.97±0.325 1.63±0.49 .0036*
2MWT (m) 199.5±32.0 163.8±45.4 .0016*
Summed strength (lb) 299.5±61.9 210.7±93.7 .0001*
SSST (s) 6.70±1.36 9.91±3.48 <.0001*
Balance (No. Romberg) 6.0±0.00 4.76±1.06 <.0001*
Vibration sensation (vu) 2.52±1.61 5.92±3.17 <.0001*
Falls (>1 past mo) 0±0 0.52±0.51 <.0001*
Cognitive measures
SDMT 59.6±6.15 47.7±12.4 <.0001*
Diffusion measures
Superior cerebellar peduncle
MD 0.0009716±0.0000705 0.0010509±0.0000832 .0003*
AD 0.001514±0.0000889 0.0015997±0.0000997 .0015*
RD 0.0007005±0.0000665 0.0007765±0.0000793 .0005*
FA 0.50±0.030 0.48 ±0.032 .016*
Middle cerebellar peduncle
MD 0.0009612±0.0000327 0.0009685±0.0000439 .48
AD 0.0015001±0.0000483 0.0015032±0.000055 .82
RD 0.0006918±0.0000285 0.0007011±0.000042 .33
FA 0.52±0.017 0.51±0.023 .15
Inferior cerebellar peduncle
MD 0.0007798±0.0000574 0.0008069±0.0000533 .070
AD 0.0012485±0.0000759 0.0012717±0.0000624 .21
RD 0.0005455±0.0000501 0.0005745±0.0000512 .035*
FA 0.51±0.025 0.50±0.028 .087
Volume measures
Lobules I–V and VIII (mm3) 32561.71±3005.0 32199.41±3121.7 .66
Lobules VI–VII (mm3) 71018.18±6504.4 69250.21±6273.8 .30
Superior cerebellar peduncle (mm3) 1925.738±288.1 1826.257±310.8 .22
Middle cerebellar peduncle (mm3) 12416±1636.3 11960.02±1296.3 .25
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NOTE. Data are presented as mean ± SD with the exception of sex, which is number, and EDSS, which is median (range). ICP volume is not included because values from the algorithm are not reliable.

Abbreviations: EDSS, Expanded Disability Status Scale; F, female; M, male.

*

Significance at P<.05.

Performance of PwMS vs controls (see table 1)

PwMS demonstrated significantly worse motor and cognitive function than controls without MS, including weaker strength, higher vibration thresholds, slower walking velocity, slower time to complete the TUG, slower time to complete the T25FW, shorter distances on the 2MWT, greater reports of falls, and significantly poorer performance on the SDMT.

For diffusion measures, the SCP FA, MD, AD, and RD were significantly worse (ie, lower FA, higher MD, AD, RD) in PwMS than controls. Although MCP diffusivity measures were not significantly different in PwMS compared with controls, PwMS demonstrated significantly worse ICP RD than controls, with FA and MD not statistically significant.

The cerebellar lobule volumes and peduncle volumes in PwMS were not significantly different from controls.

Relationships between cerebellar volume and functional performance (table 2)

Table 2.

Relationships between cerebellar volume and functional performance

Variable SCP Volume MCP Volume Motor Lobules (I, V, and VIII) Cognitive Lobules (VI and VII)
T25FW −0.284* −0.330* −0.330* −0.329*
.034 .013 .013 .013
TUG −0.333* −0.339* −0.304* −0.330*
.011 .010 .022 .012
Walk velocity 0.346* 0.284* 0.236 0.411*
.008 .032 .077 .001
2MWT 0.352* 0.210 0.218 0.261
.010 .131 .117 .059
Summed strength 0.288* 0.233 0.359* 0.287*
.031 .083 .007 .032
SSST −0.264 −0.258 −0.287* −0.386*
.066 .074 .045 .006
Balance 0.168 0.182 0.227 0.240
.215 .180 .093 .075
Vibration sensation 0.106 −0.067 −0.226 −0.089
.460 .641 .110 .533
SDMT 0.273* 0.308* 0.266* 0.347*
.040 .020 .046 .008
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NOTE. Values for each variable represent correlation then significance.

Abbreviation: EDSS, Expanded Disability Status Scale.

*

Significance at P<.05.

Motor measures

Increased volume across all cerebellar regions of interest (SCP, MCP, motor lobules, cognitive lobules) were significantly associated with better performance (ie, faster) on the T25FW and the TUG. Increased volume in the SCP, MCP, and cognitive lobules were significantly associated with walk velocity; by contrast only increased volume of the SCP was related to walking endurance, the 2MWT. Additionally, increased volume in the SCP, motor lobules, and cognitive lobules were significantly related to greater summed strength. Increased volume in the motor and cognitive lobules were also significantly related to faster performance on the SSST.

Cognitive measures

Increased volume across all cerebellar regions of interest were significantly associated with faster performance (ie, better) on the SDMT.

Relationships among cerebellar peduncle diffusivity and functional performance (table 3)

Table 3.

Relationships among cerebellar peduncle diffusivity and functional performance

Variable SCP
 MCP
 ICP
MD AD RD FA MD AD RD FA MD AD RD FA
Motor function
 T25FW 0.281* 0.235 0.295* −0.217 0.123 0.008 0.193 −0.233 0.290* 0.225 0.320* −0.239
.036 .081 .027 .108 .365 .955 .154 .084 .030 .095 .016 .075
 TUG 0.362* 0.305* 0.379* −0.225 0.185 0.081 0.240 −0.228 0.230 0.143 0.278* −0.245
.006 .022 .004 .057 .173 .553 .075 .091 .088 .294 .038 .069
 Walk velocity −0.288* −0.245 −0.300* 0.204 −0.108 −0.041 −0.145 0.123 −0.167 −0.126 −0.186 0.141
.032 .069 .025 .131 .426 .764 .285 .368 .219 .354 .169 .300
 2MWT −0.3837* −0.357* −0.314* 0.217 −0.11 −0.005 −0.014 −0.069 −0.012 0.048 −0.053 0.080
.0085 .009 .024 .122 .940 .970 .923 .625 .932 .738 .708 .575
 Summed strength −0.248 −0.237 −0.244 0.071 −0.179 −0.076 −0.177 0.106 −0.266* −0.176 −0.302* 0.248
.065 .078 .070 .602 .187 .579 .191 .439 .048 .195 .024 .065
 SSST 0.482* 0.441* 0.470* −0.241 −0.470 −0.161 0.005 −0.048 0.164 0.092 0.191 −0.173
<.001 .001 <.001 .080 .735 .246 .970 .731 .237 .506 .166 .211
 Balance −0.551* −0.551* −0.0508* 0.256 −0.215 −0.144 −0.218 0.142 −0.291* −0.268* −0.307 0.168
<.001 <.001 <.001 .057 .112 .288 .107 .297 .029 .046 .021 .217
 Vibration sensation 0.242 0.271* 0.204 −0.015 −.012 −0.040 −0.022 0.011 0.189 0.113 0.215 −0.140
.072 .043 .132 .915 .933 .770 .875 .935 .163 .407 .112 .304
Cognitive Function
 SDMT −0.469* −0.504* −0.427* 0.207 −0.134 0.005 −0.188 0.136 −0.164 −0.133 −0.181 0.071
<.001 <.001 .001 .126 .326 .969 .164 .317 .228 .329 .183 .605
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Values for each variable represent correlation then significance.

Abbreviation: EDSS, Expanded Disability Status Scale.

*

Significance at P<.05.

Motor measures

For the SCP, decreased MD and RD were significantly associated with better performance (ie, faster) on the T25FW and walk velocity. Additionally, decreased SCP MD, AD, and RD were significantly associated with faster performance on the TUG and longer distanced walked on the 2MWT. Decreased SCP MD, AD, and RD were also significantly related to faster performance on the SSST and better balance, and decreased SCP AD was significantly associated with better sensory function.

For the ICP, decreased MD and RD were significantly associated with faster performance on the T25FW and greater summed strength. Additionally, decreased ICP RD was significantly related to faster TUG time. Decreased ICP MD and AD were also significantly related to better balance.

For the MCP, no cerebellar diffusivity measures were related to functional performance.

Cognitive measures

For the SCP, MD, AD, and RD were significantly associated with better performance, or a greater number of correct responses, on the SDMT. No other associations were identified.

Discussion

This study evaluated relationships between functional cerebellar regions using DTI and volume and measures of motor and cognitive function in PwMS and controls without MS. PwMS performed significantly worse across all functional measures than to age- and sex-matched controls without MS (see table 1), consistent with previous work demonstrating functional deficits in PwMS.46 We demonstrate both significant differences in the SCP, the major output of the cerebellum, between PwMS and controls, as well as a strong relationship between SCP diffusivity and clinical measures of motor and cognitive performance.

A critical finding was that increased cerebellar volume across all regions studied was significantly related to better performance on clinical measures of motor and cognitive performance (see table 2). We hypothesized that we would find unique associations of motor and cognitive lobule volume with motor and cognitive performance, respectively. However, both motor and cognitive lobules were associated with both motor and cognitive performance (see table 2). Prior research reports relationships of cerebellar volume to falls47 and to tasks that require motor and cognitive demands, including gait coordination46 and attention processing speed.48 Indeed, the link between walking and cognition has been well established in MS49; walking may become cognitively demanding as a result of compensatory mechanisms driven by MS pathology.50 Therefore, PwMS may have required greater cognitive resources to maintain walking performance. Previous reports in MS also demonstrate associations between cerebellar volume and postural control.45 We showed significant relationships between cerebellar volumes in the SCP, MCP, motor lobules, and cognitive lobules and TUG, a validated and reliable test of dynamic balance abilities,51 but not static balance as measured by the Romberg (see table 2). This may suggest limited sensitivity of the Romberg, where ability to complete each condition was considered without regard for quality of movement. These results highlight the importance of the cerebellum in both motor cognitive functioning.

Prior DTI studies in MS demonstrate reductions in whole cerebellar FA in PwMS compared with controls without MS12,13,20 and associate decreased FA with worse motor function. However, given the limitations of FA reflecting myelin content15–17 and the abundant crossing fibers in the cerebellum52 that can affect anisotropy,18 we expected that FA would not be a strong metric for examining cerebellar diffusivity. Indeed, there were no strong relationships with FA of any cerebellar area with functional performance (see table 3). However, MD, which is independent of diffusion direction, did show strong relationships with motor and cognitive function. Specifically, diffusivity (MD, AD, RD) of the SCP, the major efferent pathway of the cerebellum,10 was strongly associated with clinical measures of motor performance (see table 2), namely measures of walking, coordination, and balance. This finding supports our first hypothesis and builds on studies linking SCP damage to motor deficits in PwMS.10–13

This study fills a gap in the MS literature regarding the utilization of novel neuroimaging parcellation methods to examine specific cerebellar correlates of cognitive function. Our results show that diffusivity of the SCP was related to processing speed as reflected by SDMT performance (see table 3). Our findings build on previous studies in MS that report relationships between decreased whole cerebellar volume and slower information processing7 and underscore the importance of further examination of cerebellar-cognitive contributions.

No significant differences were detected between groups across diffusivity measures or volumetric measures of the MCP (see table 1), and in the ICP, only RD was significantly different (see table 1) between groups. This lack of MRI-derived differences may be indicative of subtle underlying pathology in cerebellar regions that is below the sensitivity threshold of the chosen neuroimaging techniques10 or attributed to our limited sample. It is possible that the primary findings in the SCP are because of size of the peduncles, lesion load, or the information carried; the larger size of the MCP is associated with greater lesion load11 and may dilute the findings compared with ICP and SCP.53 Notably, the ICP is not as reliably segmented with this algorithm (see Methods), which may affect the findings in the ICP.

Lastly, our data show that both motor and cognitive function are related to diffusivity in the cerebellum, unique from strength (see table 3), and support the interrelated nature of motor and cognitive systems.6 This cross talk between motor and cognitive systems is relevant to the goal of rehabilitation in MS, which strives for normalized function and includes the combination of both motor and cognitive tasks when completing daily activities.54 In MS, dual-task (motor and cognitive task simultaneously) impairments are common,55 and dual-task walking is linked to falls,56 poorer supplemental motor area connectivity,57 and poorer cerebellar volume58 in MS. Therefore, future studies should examine the combined role of the cerebellum and other brain areas in dual-task performance.

Study limitations

We acknowledge our small sample size of 29 individuals with MS, which may not generalize to ambulatory individuals with progressive MS. All data were collected cross-sectionally; longitudinal studies59 may provide evidence of whether volume and diffusivity measures of the cerebellum can capture changes in performance over time. We considered our volumetric and diffusivity metrics as statistically independent, whereas given the vast complexity of subcortical associations, various neuroimaging markers may have interaction with one another. We did not examine lesion load; we acknowledge that lesions sharing connections to the cerebellum could influence functional performance.60 We used DTI to examine myelin, and recent advancements in MRI, including myelin-water imaging, have allowed for increased specificity of myelin microstructure, which is particularly relevant in MS.15,16 Newer cerebellar parcellation methods61 may allow for increased specification of cerebellar regions. We did not consider the cerebellar cognitive affective syndrome (Schmahmann syndrome), which is a well-known MS disturbance.62 Additional cognitive tests that isolate domains affected by cerebellar cognitive affective syndrome (ie, executive function, spatial cognition, verbal fluency) are critical to include in future work. Other factors that could influence MRI measurements, including physical activity, fatigue, and spasticity were not assessed. Future studies collecting these data should consider the use of modeling to account for these covariates.

Conclusions

These data highlight the contributions of the cerebellum to both motor and cognitive function in PwMS. Examining specific structure-function relationships using multiple neuroimaging modalities in PwMS improves our understanding of individualized differences in this heterogeneous group and may provide an avenue for targeted, individualized rehabilitation aimed at improving cerebellar dysfunction in MS.

Acknowledgments

We thank all of our participants, as well as Chen Chun Chiang, Rhul Marasigan, and Allen Chiang for assistance with data collection; Scott Newsome, Pavan Bhargava, Kiran Thakur, Dorlan Kimbrough, and Bryan Smith for assistance with EDSS assessments; and Ke Li and Jeff Glaister for assistance with MRI data analysis.

Supported by a National Multiple Sclerosis Society Research Grant (K.M.Z.).

The study was supported by NIH grants R01NS082347 (PAC) and R01EY032284 (JP) as well as a National Multiple Sclerosis Society Research Grant (KMZ).

List of abbreviations:

2MWT

2-minute walk test

AD

axial diffusivity

DTI

diffusion tensor imaging

FA

fractional anisotropy

ICP

inferior cerebellar peduncle

MCP

middle cerebellar peduncle

MD

mean diffusivity

MRI

magnetic resonance imaging

MS

multiple sclerosis

PwMS

persons with multiple sclerosis

RD

radial diffusivity

SCP

superior cerebellar peduncle

SDMT

Symbol Digit Modalities Test

SSST

Six Spot Step Test

T25FW

timed 25-foot walk

TUG

Timed Up and Go

Footnotes

Disclosures

Dr Fritz serves on the MS scientific advisory board for Helius Medical. Dr Prince is a founder of Sonovex Inc and serves on its Board of Directors. He has received consulting fees from JuneBrain LLC and is PI on a grant from Biogen and a coinvestigator on research grants from JuneBrain LLC and Genentech. Dr Calabresi has received consulting fees from Disarm, Nervgen, and Biogen for serving on scientific advisory boards and is PI on a grant from Genentech to Johns Hopkins University. The other authors have nothing to disclose.

Declaration of Competing Interest

None.

This work was previously presented at the Consortium of Multiple Sclerosis Centers Annual Meeting, May 29, 2015, Indianapolis, IN.

a.

Dynamometer; Hoggan Health Industries, West Jordan, UT.

b.

Vibratron II; Physitemp, Huron, NJ.

c.

Zeno Walkway; Protokinetics, Havertown, PA.

d.

MATLAB; MathWorks Inc, Natick, MA.

e.

Intera scanner; Philips Medical Systems, Best, The Nether-lands.

f.

SPSS version 25; IBM, Armonk NY.

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