Functional neuroplasticity in response to cerebello-thalamic injury underpins the clinical presentation of tremor in multiple sclerosis

Abstract

Background:

Tremor is present in almost half of multiple sclerosis (MS) patients. The lack of understanding of its pathophysiology is hampering progress in development of treatments.

Objectives:

To clarify the structural and functional brain changes associated with the clinical phenotype of upper limb tremor in people with MS.

Methods:

Fifteen healthy controls (46.1 ± 15.4 years), 27 MS participants without tremor (46.7 ± 11.6 years) and 42 with tremor (46.6 ± 11.5 years) were included. Tremor was quantified using the Bain score (0–10) for overall severity, handwriting and Archimedes spiral drawing. Functional magnetic resonance imaging activations were compared between participants groups during performance of a joystick task designed to isolate tremulous movement. Inflammation and atrophy of cerebello-thalamo-cortical brain structures were quantified.

Results:

Tremor participants were found to have atrophy of the cerebellum and thalamus, and higher ipsilateral cerebellar lesion load compared to participants without tremor (p < 0.020). We found higher ipsilateral activation in the inferior parietal lobule, the premotor cortex and supplementary motor area in MS tremor participants compared to MS participants without tremor during the joystick task. Finally, stronger activation in those areas was associated with lower tremor severity.

Conclusion:

Subcortical neurodegeneration and inflammation along the cerebello-thalamo-cortical and cortical functional neuroplasticity contribute to the severity of tremor in MS.

Keywords

Multiple sclerosis functional magnetic resonance imaging magnetic resonance imaging

Introduction

Multiple sclerosis (MS) is the leading non-traumatic neurological disorder in young adults, with 2.3 million people worldwide affected.¹ Tremor is reported in approximately 45% of people with MS, primarily affecting the upper limbs.² It is defined as an ‘involuntary, rhythmic, oscillatory movement of a body part’.³ MS tremor often manifests during (1) postures held against gravity (postural tremor); (2) voluntary movement (kinetic tremor) and (3) visually guided target-oriented movement (intention tremor).³ The presence of tremor significantly impacts patients’ quality of life, with more than half of patients with mild tremor being unemployed.^2,4,5 MS tremor can occur at any stage of the disease but is most often observed and is most severe, in people with secondary progressive MS.^2,6 Furthermore, there is currently no effective treatment available to help alleviate the severity of tremor in MS.⁷

There is limited understanding of the anatomical correlates of tremor in MS. Two case studies have reported MS patient with tremor had a lesion within the superior cerebellar peduncle (SCP), and thalamus and red nucleus, respectively.^8,9 A later study by Feys et al.¹⁰ demonstrated a link between tremor severity in MS patients and T2 lesion load in the contralateral pons. Finally, in a focussed study by our group, we confirmed damage to the SCP; thalamus is associated with tremor severity.¹¹ Taken together, these studies suggest that cerebello-thalamo-cortical (CTC) tract pathology is an important contributor to tremor in MS. However, these studies were low in sample size and limited to structural magnetic resonance imaging (MRI). In contrast to structural MRI, functional MRI (fMRI) offers the unique ability to assess brain activation in vivo during tremulous movement and can therefore provide direct insights into tremor pathophysiology. To date, there have been no functional imaging studies of tremor in people with MS. However, fMRI studies of general hand function in people with MS have reported that increased activation of ipsilateral activation was associated with compensatory effects on hand function.^12,13

This study aimed to examine the functional correlates of tremor in MS. Specifically, the relative contributions of structural and functional brain changes to the presence and severity of tremor in patients with MS. We hypothesised that tremor is associated with pathology within the CTC tract based on our previous pilot results.¹¹ Furthermore, we also hypothesised that functional reorganisation of sensorimotor brain networks might play a role in ameliorating the severity of tremor.

Methods

Study design

This study is the part of a registered clinical trial studying the efficacy of onabotulinumtoxina for MS-related tremor (ACTRN12617000379314).

Participants

Sixty-nine participants with MS were included of which 42 participants presented with unilateral upper limb tremor and 27 presented without tremor. Detailed medical and tremor history were obtained for all participants. Inclusion criterium was normal or near-normal upper limb strength (Medical Research Council (MRC) score >4+/5). A qualified neurologist determined the Expanded Disability Status Scale (EDSS)¹⁴ scores for all participants. Tremor components were defined according to the Consensus Statement of the Movement Disorder Society, 1998³ and assessed according to our previously described protocol.¹⁵ The Bain score¹⁶ was used to rate tremor severity observed while writing a standardised sentence (‘This is a sample of my best handwriting’) and drawing an Archimedes spiral on a pre-drawn pattern with the dominant hand.¹⁷ Finally, 15 healthy controls were recruited for this study and assessed using the same protocol.

Standard protocol approvals, registrations and patient consents

The study was approved by the Melbourne Health Human Research Ethics Committee. All of the participants gave informed voluntary written consent.

Imaging protocols

Participants were imaged using a 3T MRI system (Trio, Siemens, Erlangen). Structural imaging included (1) high-resolution three-dimensional (3D) T1-weighted magnetization-prepared rapid acquisition with gradient echo (MPRAGE) scan with online motion correction (recovery time (TR) = 2530 ms; echo time (TE) = 2.5 ms; inversion time (TI) = 1260 ms; field of view (FOV) = 176 × 256 mm; voxel size = 1.0 × 1.0 × 1.0 mm) and (2) high-resolution 3D T2-weighted double inversion recovery (DIR) sequence (TR = 7400 ms; TE = 324 ms; TI = 3000 ms; flip angle = 120°; echo train length (ETL) = 625; FOV = 144 × 220 mm; voxel size = 1.0 × 1.0 × 1.0). Functional imaging included two runs (TR = 1.5 ms, TE = 33 ms, FOV = 2040 × 2040, matrix = 104 × 104, slice thickness = 2.5, flip angle = 85.0, multi-band slice acceleration factor = 3, volumes = 200). For, healthy controls only the T1-weighted MPRAGE scan was performed.

Joystick task

The fMRI task performed is described in detail in Boonstra et al.¹⁸ Briefly, the task involved participating in a simple game using an MRI-compatible joystick. There were three conditions in the game (PLAY, WATCH and MOVE) and each condition started with an instruction screen indicating which condition would follow. During PLAY, the participant manoeuvred a paddle under a ball to bounce it up. During WATCH, the participant only watched a ball move along the screen. During MOVE, the participant moved the joystick to the left and right of the screen continuously, while the ball was frozen on the screen. The PLAY condition includes visual tracking, attention and basic motor activity. Furthermore, this condition has shown to elicit tremulous movement in tremor participants compared to healthy controls.¹⁸ The WATCH condition required no motor activity but controlled for visual aspects and visual attention components of PLAY. In addition, the WATCH condition controls visual aspects. The MOVE condition required no visual attention but controlled for the baseline movement activity component of PLAY.

Joystick task analysis

Analyses of the tremor-like movement measured using the joystick are described in Boonstra et al.¹⁸ Briefly, we measured the average power of frequencies between 3 and 10 Hz, expressed in decibels (dB), to represent the amplitude of tremor-like movement during the different conditions.

Functional imaging analyses

Task fMRI was analysed using FSL FEAT 5.0.8.¹⁹ The data were y-flipped for all participants with a left-handed tremor, resulting in images in which the hemisphere contralateral to the tremor-affected side was on the same side for each participant.^20,21 Only the prefrontal cortex showed lateralization (see Supplementary Figure 1). However, we found no significant difference between the flipped and the un-flipped functional images. Possible bias was further limited by were near equal numbers of participants flipped in both the MS participants group with tremor and without tremor.

To create the best template for our group of MS participants, we created a study-specific template using Advanced Neuroimaging Tools (ANTs).²² A nonlinear registration was performed within FEAT to the main structural image and the ANTs template. Pre-processing of fMRI images included motion correction FMRIB Linear Registration Tool (MCFLIRT), high-pass filtering (<0.01 Hz) and spatial smoothing (4 mm). FSL motion outlier detection was used to detect slices within the data that were corrupted by large movements defined as movement above the 75th percentile + 1.5 times the interquartile range. Finally, we added standard motion parameters. Run-level general linear models for the following contrasts were performed:

PLAY > WATCH (motor component);

PLAY > MOVE (visual attention component);

PLAY > WATCH + MOVE (tremor component).

For each contrast, second-level analyses were used to combine the two task runs for each participant. Subsequently, third-level analyses were used to compare each contrast between participants with MS with and without tremor. For PLAY > WATCH + MOVE, we compared the main activation between participants with MS with tremor and without tremor to identify the areas related to tremor, while controlling for visual and motor components. The cluster(s) that showed a significant difference between participants with MS with and without tremor were selected (z-stat > 2.3, cluster size threshold p = 0.05). We measured the intensity of the voxel with the maximum activation within the cluster(s) for each subject, as the maximum is not biased towards the size of the cluster

Structural imaging analyses

Structural MRI was analysed using FreeSurfer version 5.3 (http://surfer.nmr.mgh.harvard.edu/), Osirix Lite v9.0.2 and Lesion Segmentation Toolbox (LST) version 2.0.15 for Statistical Parametric Mapping (SPM).²³ Based on previous literature, we selected the thalamus, SCP and cerebellum as structural region of interests (ROIs). In addition, cortical thickness was measured to examine its effect on any functional changes. FreeSurfer was used to determine the volumes of the thalamus and cerebellum and average cerebral cortical thickness from the MPRAGE images. The area of the SCP was manually labelled as described previously in Boonstra et al.¹¹ Lesion load in MS participants within the cerebellum and the thalamus was derived from the DIR images using the lesion prediction algorithm within LST. Due to the size of the SCP, we did not separately calculated lesion load for this structure. To optimise the automatic lesions segmentation, we manually determined the optimal threshold for each participant and then corrected the final lesion maps (see Supplementary Figure 2 for an example of the lesion segmentation). Lesion load within the thalamus and cerebellum was determined using the brain segmentation maps derived from the FreeSurfer analyses described above.

Statistical analyses

Statistical analyses were performed in SPSS version 24. To test for group differences in clinical measures (Bain and EDSS scores), we used non-parametric Mann–Whitney tests. For structural measures, corrected for intracranial volume (ICV) by division, group differences were measured using a one-way analysis of variance (ANOVA) with Turkey post hoc test. Group difference in lesion load, corrected for ICV, was assessed using an independent t-test. For the MS participants, tremor-like movement was compared during the MOVE and PLAY conditions using two-way repeated measures ANOVA (within-subject factor: condition; between-subject factor: group). To examine the relationship between fMRI activation level and tremor severity within the participants with tremor, we used a linear regression with the Bain scores as predictors and the maximum activation within the cluster(s) and age as covariates. Finally, to determine the effect of overall disease severity on tremor-associated pathology, we used a Spearman’s rank correlation between all imaging parameters and general disease severity (EDSS) in tremor participants, while correcting for age and disease duration using regression. Correction of multiple comparisons using the false discovery rate was performed.

Results

Demographic and clinical data

Healthy controls had a mean age of 46.1, 60% was female and 80% performed the joystick task with the right hand (see Table 1). The participants without tremor had a mean age of 46.7, mean disease duration of 11.4 years, 55.4% had secondary progressive MS, 73.8% was female, 71.4% performed the joystick task with their right hand and a median EDSS of 3. The MS participants with tremor had a mean age of 46.6, mean disease duration of 14 years, 61.3% had secondary progressive MS, 77.8% was female, 74.1% had a right-sided tremor, mean tremor duration was 8.5 years and a median EDSS of 4. Furthermore, one participant with tremor presented with primary progressive MS. There were no significant differences between age, disease duration, disease course and EDSS. EDSS visual and sensory scores were mild and not different between the participants groups. The clinical tremor measures, Bain severity, handwriting and Archimedes were significantly higher in the participants with tremor compared to without tremor (p < 0.001).

Table 1.

Demographic and clinical tremor data for multiple sclerosis participants with tremor and without tremor.

	Healthy controls	MS Without tremor	MS with tremor	p-value
N	15	27	42	–
Age mean (SD)	46.1 (15.4)	46.7 (11.6)	46.6 (11.5)	0.910
Disease duration, years, mean (SD)	–	11.4 (7.7)	14.0 (7.4)	0.168
Tremor duration, years, mean (SD)	–	–	8.5 (8.0)	–
Affected hand right %	80	71.4	74.1	0.816
Gender female %	60	73.8	77.8	0.461
EDSS median (IQR)	–	3 (2.5, 5)	4 (2.75, 6)	0.062
EDSS visual median (IQR)	–	0 (0, 1)	0 (0, 1)	0.763
EDSS sensory median (IQR)	–	1 (0, 2)	1 (0, 2)	0.794
Disease course, secondary progressive %		55.6%	61.9%	0.388
Bain severity median (IQR)	–	0 (0, 0)	3 (2, 5)	<0.001^a
Bain handwriting median (IQR)	–	0 (0, 0)	3 (2, 5.5)	<0.001^a
Bain Archimedes median (IQR)	–	0 (0, 0)	3 (2, 4.5)	<0.001^a

MS: multiple sclerosis; SD: standard deviation; EDSS: Expanded Disability Status Scale; IQR: interquartile range.

False discovery rate corrected p < 0.05.

Structural group differences

There were significant structural differences between healthy controls, MS participants with and without tremor (Table 2 and Supplementary Figure 3). After correction for multiple comparisons, post hoc analyses revealed that for both the contralateral and ipsilateral cerebellum, MS participants with tremor had a smaller volume compared to healthy controls (p = 0.002 and p = 0.001) and MS participants without tremor (p < 0.001 and p = 0.001). Furthermore, the lesion load in the ipsilateral cerebellum was significantly higher (p = 0.018) in MS participants with tremor compared to without tremor. Tremor participants had a smaller contralateral and ipsilateral thalamic volume than healthy controls (p < 0.001 and p = 0.003) and MS participants without tremor (p = 0.013 and p = 0.014). No significant differences between tremor participants compared to healthy controls and MS participants without tremor were found for the volume of the SCP.

Table 2.

Volumetric and lesion load data for multiple sclerosis participants with tremor and without tremor.

	Healthy controls	MS without tremor	MS with tremor	p-value
ICV mean (SD)	1.07 × 10⁶ (2.49 × 10⁵)	1.07 × 10⁶ (2.59 × 10⁵)	1.27 × 10⁶ (3.31 × 10⁵)	0.010^a
Cortical thickness, mm², mean (SD)	2.35 (0.07)	2.32 (0.12)	2.36 (0.15)	0.496
Cerebellar volume, mm³, mean (SD)
Contralateral	61,070 (12,536)	58,810 (8950)	55,065 (15,886)	<0.001^a
Ipsilateral	62,589 (11,585)	59,219 (9823)	55,377 (15,698)	<0.001^a
Thalamic volume, mm³, mean (SD)
Contralateral	7491 (1139)	6432 (796)	6294 (897)	<0.001^a
Ipsilateral	6920 (649)	6311 (926)	6129 (889)	0.001^a
SCP area, mm², mean (SD)
Contralateral	26.9 (4.65)	24.4 (5.08)	24.9 (4.56)	0.017
Ipsilateral	27.1 (4.33)	25.3 (5.19)	25.7 (4.91)	0.053
Total lesions, mL (SD)	–	14,583 (18,063)	16,946 (12,294)	0.901
Cerebellar lesions, mL (SD)
Contralateral	–	4.4 (13.1)	40.1 (153)	0.257
Ipsilateral	–	1.9 (5.4)	25.4 (67.8)	0.018^a
Thalamic lesions, mL (SD)
Contralateral	–	10.4 (22.4)	21.7 (85.7)	0.613
Ipsilateral	–	13.2 (24.3)	8.5 (22.7)	0.187

MS: multiple sclerosis; ICV: intracranial volume; SD: standard deviation; SCP: superior cerebellar peduncle.

False discovery rate corrected p < 0.05.

Tremulous movement during task

MS participants with tremor showed an increase in tremor-like movement during the PLAY and MOVE conditions compared to participants without tremor (p < 0.001). Furthermore, the amount of tremor-like movement within both groups was significantly higher in PLAY compared to MOVE (p < 0.001; Figure 1).

Functional group differences

Five tremor participants were unable to complete the fMRI experiment due to practical limitations and were excluded from fMRI analyses. Specifically, we were unable to fit the joystick inside the bore for two participants and experienced software difficulties for the remaining three. The main effect for MS participants with and without tremor using the three contrasts is displayed in Figure 2. The main effect using the contrast PLAY > WATCH showed activation of the motor cortex (Figure 2(a)), PLAY > MOVE showed the visual and attention areas (Figure 2(b)) and PLAY > WATCH + MOVE showed the attention areas remaining after subtracting the motor and visual component (Figure 2(c)). Compared to patients without tremor, tremor patients showed greater activation within the ipsilateral inferior parietal lobule (IPL) (Figure 2(d), cluster 1: 451 voxels; maximum/mean z-stat 2.99/1.30; Montreal Neurological Institute (MNI) coordinates of voxel with maximum z-stat 56, –56, 26), and the premotor/supplementary motor area (SMA) (Figure 2(e), cluster 2: 691 voxels; maximum/mean z-stat 3.10/1.12; MNI coordinates of voxel with maximum z-stat 36, 16, 52) when looking at PLAY > WATCH + MOVE.

Functional task activations and tremor severity

We identified some associations of modest significance. Specifically, one unit increase in cluster 1 activation was associated with a drop of 0.40 in Bain severity (p = 0.022), 0.59 in Bain handwriting (p = 0.018) and 0.43 in Bain Archimedes (p = 0.052). Furthermore, one unit increase in cluster 2 activation was associated with a drop of 0.24 in Bain severity (p = 0.065), 0.42 in Bain handwriting (p = 0.018) and 0.29 in Bain Archimedes (p = 0.069). Multiple comparisons corrected p = 0.043.

MRI and general disability in patients with tremor

In order to determine whether MRI variation was related to general disease progression rather than tremor-specific pathology, we determined the relationship between EDSS and the MRI parameters. No correlations between any of the structural MRI measures and EDSS were found. There was a moderate correlation between EDSS and the degree of activation within the ipsilateral SMA and premotor area (ρ = –0.379, p = 0.028). However, this correlation did not remain significant after correction for multiple comparisons.

Discussion

We examined the structural and functional brain changes related to the presence and severity of tremor in patients with MS. Two distinct features in the brains of patients with MS were found to be associated with the presence of moderate tremor: subcortical structural damage and cortical functional neuroplasticity. Subcortical structural damage presented as atrophy of the cerebellum and thalamus and increased lesion load within the ipsilateral cerebellum. Functional neuroplasticity was observed as increased activation within the ipsilateral cortex; specifically, the premotor cortex, supplementary motor area (SMA) and inferior parietal lobule (IPL).

Neurophysiological models of MS tremor have emphasised the effect of demyelinating lesions on cortico-cerebello-cortical loops by which motor commands are projected from the motor cortex via the cortico-ponto-cerebellar pathway to the cerebellum, and return via the CTC pathway back to the motor cortex.²⁴ Specifically, it has been proposed that MS tremor patients are more dependent on visual information, and that their internal representation of the state of the limb (position and velocity), thought to be encoded by an internal model in the cerebellum,²⁵ has been impaired.²⁴ Further evidence is provided by animal studies and surgical treatments that emphasise the SCP, thalamus and basal ganglia in the pathophysiology of tremor in patients with MS.^26–29 Furthermore, small cross-sectional structural imaging studies have indicated pathology of the SCP, pons, brainstem, internal capsule, thalamus and red nucleus are associated with tremor pathogenesis.^8,10,11,30 Our results support the involvement of neurodegeneration and inflammatory damage along the cerebello-thalamic tract in the pathophysiology of tremor in patients with MS.³¹ We observed bilateral atrophy in these structures in patients with tremor compared to patients without tremor. Importantly, logistic regression showed that ipsilateral cerebellar atrophy and contralateral thalamic atrophy were significant, independent predictors of tremor status. This is consistent with the anatomy of the cerebello-thalamic tract that decussates between these structures. Additional inflammatory lesion load in the contralateral cerebellar hemispheres was found. We observed a correlation between tremor and bilateral cerebellar and thalamic atrophy. This finding is inconsistent with the notion that unilateral tremor is attributable to damage of the ipsilateral cerebellum and contralateral thalamus – consistent with the known anatomy of the cerebellar-thalamo-cortical network. One study found a correlation between unilateral tremor severity and contralateral pontine lesions.¹⁰ However, these findings are in a small cohort (N = 14) of participants with bilateral MS tremor making it challenging to study tract lateralization. We attribute our finding to secondary trans-synaptic degeneration of contralateral cerebellar and thalamic neurons. Although it is not possible to test this directly using the cross-sectional data in this study, our findings are consistent with previous observations in MS¹¹ and in essential tremor.^32–34 Furthermore, the pons is a structure that is thought to have connectivity across both hemispheres, which supports our hypothesis that interhemispheric connections contribute to bilateral atrophy. Taken together, these findings support the hypothesis that damage, including both atrophy and inflammation, in the cerebellum and thalamus are involved in the pathogenesis of tremor in MS patients.

The observed subcortical damage, combined with animal and treatment studies, suggests causality of tremor pathophysiology. Consistent with previous neurophysiological models of intention tremor in MS,²⁴ the functional correlates reported here specifically link tremor during a visually guided task in MS to aberrant activity within a cortical region functionally linked to the cerebellum and thalamus. In addition to the more well-known connections between the premotor/SMA, and the cerebellum and thalamus in motor planning/control,^35,36 the IPL is a target of cerebellar efferents^37–39 and through this, it is thought to facilitate sensorimotor plasticity.³⁷ Furthermore, connectivity mapping and functional analyses have implicated regions of the IPL in both a lower-level, luminance-based and a higher-level, attention-based system for motion processing.⁴⁰ While performing the task, we found that patients with tremor show increased activation in both ipsilateral IPL and premotor/SMA compared to patients without tremor. Furthermore, the amount of activation showed a moderate negative correlation with tremor severity in the tremor group. This finding suggests that stronger activation of this network, involving motor planning and sensorimotor integration areas, is associated with neural processes that attenuate the tremor, or when the activation is weaker, the tremor is more pronounced.

Failure of functional neuroplasticity could be due to an overall increase in disease burden. Indeed, we observed that ipsilateral thalamic volume and premotor/SMA activation lower with worsening of general disease severity. Functional neuroplasticity thought to compensate for abnormal or inadequate motor movement has also been shown in other neurological diseases. In Parkinson’s disease, an increased activation within the ipsilateral premotor cortex was associated with better motor performance.⁴¹ Broersma et al.³² showed that increased activation in the primary motor cortex and cerebellum in essential tremor patients compared to healthy controls was associated with tremor. Cross-sectional studies are subject to antecedent-consequence bias, meaning that one cannot determine whether an observed difference is a cause or consequence of the disease. However, taken together, our results suggest that functional neuroplasticity within the ipsilateral cortex is a compensatory mechanism acting to alleviate the tremulous movement in patients that is invoked once a threshold for degeneration or demyelination within cerebello-thalamic pathways has been reached.

We showed that our joystick task was able to elicit tremulous movement in patients with clinical tremor. Patients in this study without clinical tremor still showed an increase in tremor-like movement during PLAY. Tremor-like movement is measured is the amount of movement with a frequency between the 3–10 Hz. During the PLAY condition, there is more ‘jerky’ movement which increases the likelihood of falling within the tremor frequency band. Compared to the controlled condition MOVE, this could explain the increased amount of measured tremor-like movement in the MS controls while playing the game. However, there was significantly higher amount of tremor-like movement in the MS tremor participants.

Understanding the pathophysiology of tremor is essential for examining how drugs affect the clinical presentation of tremor. There is insufficient evidence supporting the efficacy of pharmaceutical treatment options for tremor patients with MS, while surgical treatment is very invasive and is a last resort option.⁷ However, almost 50% of patients with MS with tremor use symptomatic medications.⁴² Anticonvulsants are thought to be the most effective treatment;⁴² however, the mechanism of effect remains unclear as it is prescribed for a variety of MS symptoms other than tremor.⁴³ Our study is the first in MS tremor research to use both structural and functional imaging. Of all the parameters, we found that when combined, the maximum activation within the ipsilateral premotor/SMA, contralateral cerebellar atrophy and ipsilateral cerebellar inflammation best predicts which patients with MS have tremor. Taken together, studies that examine the pathological processes for tremor in MS could help guide new treatments, understand treatment effect and assist in patient selection for specific treatments.⁴⁴

Longitudinal and treatment studies are warranted to better understand what leads to the failure of the functional neuroplasticity and to assess how treatments affect the tremor pathophysiology. Ultimately, new therapies can be introduced or targeted to tremor in patients with MS based on the in vivo structural and functional presentation of tremor in the brain.

Supplemental Material

MSJ837706_supplementary_figures – Supplemental material for Functional neuroplasticity in response to cerebello-thalamic injury underpins the clinical presentation of tremor in multiple sclerosis

Supplemental material, MSJ837706_supplementary_figures for Functional neuroplasticity in response to cerebello-thalamic injury underpins the clinical presentation of tremor in multiple sclerosis by Frederique MC Boonstra, Gustavo Noffs, Thushara Perera, Vilija G Jokubaitis, Adam P Vogel, Bradford A Moffat, Helmut Butzkueven, Andrew Evans, Anneke van der Walt and Scott C Kolbe in Multiple Sclerosis Journal

Footnotes

Acknowledgements

The authors would like to acknowledge the Murdoch Children’s Research Institute for providing access to the MRI suite and invaluable technical support. The authors would like to acknowledge C. Shanahan for her contributions to the project.

Author Contributions

F.M.C.B. has worked on study concept and design, data collection, data analyses, statistical analyses, data interpretation and critical revision of writing manuscript for intellectual content. G.N. has worked on study concept and design, data collection and critical revision of writing manuscript for intellectual content. T.P. has worked on study concept and design and critical revision of writing manuscript for intellectual content. V.G.J. has worked on data collection and critical revision of writing manuscript for intellectual content. A.P.V., H.B. and A.E. have worked on study concept and design, data interpretation and critical revision of writing manuscript for intellectual content. B.A.M. has worked on critical revision of writing manuscript for intellectual content. A.v.d.W. has worked on study concept and design, data collection, data interpretation and critical revision of writing manuscript for intellectual content. S.C.K. has worked on study concept and design, data collection, data analyses, data interpretation and critical revision of writing manuscript for intellectual content. A.v.d.W. and S.C.K. contributed equally.

Declaration of Conflicting Interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship and/or publication of this article: F. Boonstra reports no disclosures. G.N. reports no disclosures. T.P. reports no disclosures. V.G.J. received travel support from Biogen, Merck and Sanofi, and received speaker’s honoraria from Biogen. She receives fellowship funding from Multiple Sclerosis Research Australia. A.P.V. consults to Takeda and Pfizer. He is Chief Science Officer of Redenlab. He receives grant and fellowship funding from the National Health and Medical Research Council of Australia. B.A.M. is a National Imaging Fellow via the NCRIS program (Government of Australia), he has/had research and clinical trial contracts with Siemens, Roche, Piramal, Jansen, GE and CSIRO. H.B.: Compensation for steering committee, advisory board and consultancy fees from Biogen, Merck, Roche, Novartis, Teva, Oxford Pharmagenesis; research support from Novartis, Biogen, Merck, NHMRC Australia, MS Research Australia, UK MS Trust, Monash University. A.E. received honoraria from Novartis for giving presentations and providing consultancy services. He has participated in scientific advisory board meetings for Novartis, UCB Pharma, Allergan and Boehringer Ingelheim. He has received conference travel support from Boehringer Ingelheim. A.v.d.W. received travel support from Biogen Idec, Novartis, Teva, Merck, Sanofi and served on advisory boards for Biogen Idec, Novartis and Merck. She receives grant and fellowship funding from the National Health and Medical Research Council of Australia. S.C.K. received grant income from the National Health and Medical Research Council of Australia and has received honoraria from Novartis, Biogen and Merck.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This project was funded by an NHMRC Project Grant (1085461 CIA Van der Walt). The Bionics Institute receives Operational Infrastructure Support from the Victorian Government.

Supplemental Material

Supplemental material for this article is available online.

ORCID iDs

Frederique MC Boonstra

Adam P Vogel

Anneke van der Walt

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