Cerebellum and cognition in progressive MS patients: functional changes beyond atrophy?

Cerebellar pathology in multiple sclerosis and experimental autoimmune encephalomyelitis: current status and future directions

Recent decades have witnessed significant progress in understanding mechanisms driving neurodegeneration and disease progression in multiple sclerosis (MS), but with a focus on the cerebrum. In contrast, there have been limited studies of cerebellar disease, despite the common occurrence of cerebellar symptoms in this disorder. These rare studies, however, highlight the early cerebellar involvement in disease development and an association between the early occurrence of cerebellar lesions and risk of worse prognosis. In parallel developments, it has become evident that far from being a region specialized in movement control, the cerebellum plays a crucial role in cognitive function, via circuitry connecting the cerebellum to association areas of the cerebrum. This complexity, coupled with challenges in imaging of the cerebellum have been major obstacles in the appreciation of the spatio-temporal evolution of cerebellar damage in MS and correlation with disability and progression. MS studies based on animal models have relied on an induced neuroinflammatory disease known as experimental autoimmune encephalomyelitis (EAE), in rodents and non-human primates (NHP). EAE has played a critical role in elucidating mechanisms underpinning tissue damage and been validated for the generation of proof-of-concept for cerebellar pathological processes relevant to MS. Additionally, rodent and NHP studies have formed the cornerstone of current knowledge of functional anatomy and cognitive processes. Here, we propose that improved insight into consequences of cerebellar damage in MS at the functional, cellular and molecular levels would be gained by more extensive characterization of EAE cerebellar pathology combined with the power of experimental paradigms in the field of cognition. Such combinatorial approaches would lead to improved potential for the development of MS sensitive markers and evaluation of candidate therapeutics.

MR Imaging Signs of Gadolinium Retention Are Not Associated with Long-Term Motor and Cognitive Outcomes in Multiple Sclerosis

BACKGROUND AND PURPOSE

The long-term impact of gadolinium retention in the dentate nuclei of patients undergoing administration of seriate gadolinium-based contrast agents is still widely unexplored. The aim of this study was to evaluate the impact of gadolinium retention on motor and cognitive disability in patients with MS during long-term follow-up.

MATERIALS AND METHODS

In this retrospective study, clinical data were obtained from patients with MS followed in a single center from 2013 to 2022 at different time points. These included the Expanded Disability Status Scale score to evaluate motor impairment and the Brief International Cognitive Assessment for MS battery to investigate cognitive performances and their respective changes with time. The association with qualitative and quantitative MR imaging signs of gadolinium retention (namely, the presence of dentate nuclei T1-weighted hyperintensity and changes in longitudinal relaxation R1 maps, respectively) was probed using different General Linear Models and regression analyses.

RESULTS

No significant differences in motor or cognitive symptoms emerged between patients showing dentate nuclei hyperintensity and those without visible changes on T1WIs (P  = .14 and 0.92, respectively). When we tested possible relationships between quantitative dentate nuclei R1 values and both motor and cognitive symptoms, separately, the regression models including demographic, clinical, and MR imaging features explained 40.5% and 16.5% of the variance, respectively, without any significant effect of dentate nuclei R1 values (P  = .21 and 0.30, respectively).

CONCLUSIONS

Our findings suggest that gadolinium retention in the brains of patients with MS is not associated with long-term motor or cognitive outcomes.

Disability outcomes in early-stage African American and White people with multiple sclerosis

BACKGROUND

Factors driving differences in disease burden between African American and White people with multiple sclerosis (pwMS) remain unclear. Here, we explored whether differences in disability outcomes could be observed after controlling for major sociodemographic factors and comorbidities, and assessed the presence of a possible interaction between MS and race.

METHODS

In this cross-sectional study, 120 pwMS within 6 years from disease onset and 82 healthy controls between 18 and 70 years of age, self-identified as either African American or White, were prospectively enrolled. Inclusion criteria for pwMS were: diagnosis of MS according to the revised McDonald criteria, relapsing-remitting phenotype and Expanded Disability Status Scale (EDSS) < 6.5. Study outcomes included: (i) global disability (EDSS); (ii) quantitative mobility and leg function (Timed 25 Foot Walk Test-T25FWT); (iii) quantitative finger dexterity (9-Hole Peg Test-9HPT); (iv) cognitive efficiency and speed performance (Symbol Digit Modalities Test-SDMT). Differences in disability outcomes were assessed employing multivariable linear regression models. Based on their association with MS or disability, covariates included age, gender, race, years of education, total income, body mass index, comorbidities. The interaction between MS and race on disability outcomes was estimated via relative excess risk of interaction and attributable proportion.

RESULTS

Accounting for age, gender, total income, education, body mass index and comorbidities, African American pwMS showed significantly worse performances in manual dexterity and cognition than White pwMS (White pwMS coeff. 3.24, 95% CI 1.55, 4.92 vs African American pwMS coeff. 5.52, 95% CI 3.55, 7.48 and White pwMS coeff. -5.87, 95% CI -8.86, -2.87 vs African American pwMS coeff. -7.99, 95% CI -11.58,-4.38). MS and race independently contributed to the observed gradient in disability severity.

CONCLUSIONS

Complex social disparities and systemic racism might contribute to clinical heterogeneity in MS.

Early remission in multiple sclerosis is linked to altered coherence of the Cerebellar Network

BACKGROUND

The development of permanent disability in multiple sclerosis (MS) is highly variable among patients, and the exact mechanisms that contribute to this disability remain unknown.

METHODS

Following the idea that the brain has intrinsic network organization, we investigated changes of functional networks in MS patients to identify possible links between network reorganization and remission from clinical episodes in MS. Eighteen relapsing-remitting MS patients (RRMS) in their first clinical manifestation underwent resting-state functional MRI and again during remission. We used ten template networks, identified from independent component analysis, to compare changes in network coherence for each patient compared to those of 44 healthy controls from the Human Connectome Project test-retest dataset (two-sample t-test of pre-post differences). Combining a binomial test with Monte Carlo procedures, we tested four models of how functional coherence might change between the first clinical episode and remission: a network can change its coherence (a) with itself ("one-with-self"), (b) with another network ("one-with-other"), or (c) with a set of other networks ("one-with-many"), or (d) multiple networks can change their coherence with respect to one common network ("many-with-one").

RESULTS

We found evidence supporting two of these hypotheses: coherence decreased between the Executive Control Network and several other networks ("one-with-many" hypothesis), and a set of networks altered their coherence with the Cerebellar Network ("many-with-one" hypothesis).

CONCLUSION

Given the unexpected commonality of the Cerebellar Network's altered coherence with other networks (a finding present in more than 70% of the patients, despite their clinical heterogeneity), we conclude that remission in MS may result from learning processes mediated by the Cerebellar Network.

Magnetic Resonance Imaging in Primary Progressive Multiple Sclerosis Patients : Review

The recently developed effective treatment of primary progressive multiple sclerosis (PPMS) requires the accurate diagnosis of patients with this type of disease. Currently, the diagnosis of PPMS is based on the 2017 McDonald criteria, although the contribution of magnetic resonance imaging (MRI) to this process is fundamental. PPMS, one of the clinical types of MS, represents 10%-15% of all MS patients. Compared to relapsing-remitting MS (RRMS), PPMS differs in terms of pathology, clinical presentation and MRI features. Regarding conventional MRI, focal lesions on T2-weighted images and acute inflammatory lesions with contrast enhancement are less common in PPMS than in RRMS. On the other hand, MRI features of chronic inflammation, such as slowly evolving/expanding lesions (SELs) and leptomeningeal enhancement (LME), and brain and spinal cord atrophy are more common MRI characteristics in PPMS than RRMS. Nonconventional MRI also shows differences in subtle white and grey matter damage between PPMS and other clinical types of disease. In this review, we present separate diagnostic criteria, conventional and nonconventional MRI specificity for PPMS, which may support and simplify the diagnosis of this type of MS in daily clinical practice.

Task- and resting-state fMRI studies in multiple sclerosis: From regions to systems and time-varying analysis. Current status and future perspective

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Functional MRI is able to detect adaptive and maladaptive abnormalities at different MS stages.

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Increased fMRI activity is a feature of early MS, while progressive exhaustion of adaptive mechanisms is detected later on in the disease.

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Collapse of long-range connections and impaired hub integration characterize MS network reorganization.

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Time-varying connectivity analysis provides useful and complementary pieces of information to static functional connectivity.

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New perspectives might be the use of multimodal MRI and artificial intelligence.

Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.

Cerebellar pathology and disability worsening in relapsing-remitting multiple sclerosis: A retrospective analysis from the CombiRx trial

BACKGROUND AND PURPOSE

Cerebellar damage is a valuable predictor of disability, particularly in progressive multiple sclerosis. It is not clear if it could be an equally useful predictor of motor disability worsening in the relapsing-remitting phenotype.

AIM

We aimed to determine whether cerebellar damage is an equally useful predictor of motor disability worsening in the relapsing-remitting phenotype.

METHODS

Cerebellar lesion loads and volumes were estimated using baseline magnetic resonance imaging from the CombiRx trial (n = 838). The relationship between cerebellar damage and time to disability worsening (confirmed disability progression [CDP], timed 25-foot walk test [T25FWT] score worsening, nine-hole peg test [9HPT] score worsening) was tested in stagewise and stepwise Cox proportional hazards models, accounting for demographics and supratentorial damage.

RESULTS

Shorter time to 9HPT score worsening was associated with higher baseline Expanded Disability Status Scale (EDSS) score (hazard ratio [HR] 1.408, p = 0.0042) and higher volume of supratentorial and cerebellar T2 lesions (HR 1.005 p = 0.0196 and HR 2.211, p = 0.0002, respectively). Shorter time to T25FWT score worsening was associated with higher baseline EDSS (HR 1.232, p = 0.0006). Shorter time to CDP was associated with older age (HR 1.026, p = 0.0010), lower baseline EDSS score (HR 0.428, p < 0.0001) and higher volume of supratentorial T2 lesions (HR 1.024, p < 0.0001).

CONCLUSION

Among the explored outcomes, single time-point evaluation of cerebellar damage only allows the prediction of manual dexterity worsening. In clinical studies the selection of imaging biomarkers should be informed by the outcome of interest.

Stratification of multiple sclerosis patients using unsupervised machine learning: a single-visit MRI-driven approach

OBJECTIVES

To stratify patients with multiple sclerosis (pwMS) based on brain MRI-derived volumetric features using unsupervised machine learning.

METHODS

The 3-T brain MRIs of relapsing-remitting pwMS including 3D-T1w and FLAIR-T2w sequences were retrospectively collected, along with Expanded Disability Status Scale (EDSS) scores and long-term (10 ± 2 years) clinical outcomes (EDSS, cognition, and progressive course). From the MRIs, volumes of demyelinating lesions and 116 atlas-defined gray matter regions were automatically segmented and expressed as z-scores referenced to external populations. Following feature selection, baseline MRI-derived biomarkers entered the Subtype and Stage Inference (SuStaIn) algorithm, which estimates subgroups characterized by distinct patterns of biomarker evolution and stages within subgroups. The trained model was then applied to longitudinal MRIs. Stability of subtypes and stage change over time were assessed via Krippendorf's α and multilevel linear regression models, respectively. The prognostic relevance of SuStaIn classification was assessed with ordinal/logistic regression analyses.

RESULTS

We selected 425 pwMS (35.9 ± 9.9 years; F/M: 301/124), corresponding to 1129 MRI scans, along with healthy controls (N = 148; 35.9 ± 13.0 years; F/M: 77/71) and external pwMS (N = 80; 40.4 ± 11.9 years; F/M: 56/24) as reference populations. Based on 11 biomarkers surviving feature selection, two subtypes were identified, designated as "deep gray matter (DGM)-first" subtype (N = 238) and "cortex-first" subtype (N = 187) according to the atrophy pattern. Subtypes were consistent over time (α = 0.806), with significant annual stage increase (b = 0.20; p < 0.001). EDSS was associated with stage and DGM-first subtype (p ≤ 0.02). Baseline stage predicted long-term disability, transition to progressive course, and cognitive impairment (p ≤ 0.03), with the latter also associated with DGM-first subtype (p = 0.005).

CONCLUSIONS

Unsupervised learning modelling of brain MRI-derived volumetric features provides a biologically reliable and prognostically meaningful stratification of pwMS.

KEY POINTS

• The unsupervised modelling of brain MRI-derived volumetric features can provide a single-visit stratification of multiple sclerosis patients. • The so-obtained classification tends to be consistent over time and captures disease-related brain damage progression, supporting the biological reliability of the model. • Baseline stratification predicts long-term clinical disability, cognition, and transition to secondary progressive course.

Regional Cerebellar Volume Loss Predicts Future Disability in Multiple Sclerosis Patients

Cerebellar symptoms in multiple sclerosis (MS) are well described; however, the exact contribution of cerebellar damage to MS disability has not been fully explored. Longer-term observational periods are necessary to better understand the dynamics of pathological changes within the cerebellum and their clinical consequences. Cerebellar lobe and single lobule volumes were automatically segmented on 664 3D-T1-weighted MPRAGE scans (acquired at a single 1.5 T scanner) of 163 MS patients (111 women; mean age: 47.1 years; 125 relapsing–remitting (RR) and 38 secondary progressive (SP) MS, median EDSS: 3.0) imaged annually over 4 years. Clinical scores (EDSS, 9HPT, 25FWT, PASAT, SDMT) were determined per patient per year with a maximum clinical follow-up of 11 years. Linear mixed-effect models were applied to assess the association between cerebellar volumes and clinical scores and whether cerebellar atrophy measures may predict future disability progression. SPMS patients exhibited faster posterior superior lobe volume loss over time compared to RRMS, which was related to increase of EDSS over time. In RRMS, cerebellar volumes were significant predictors of motor scores (e.g. average EDSS, T25FWT and 9HPT) and SDMT. Atrophy of motor-associated lobules (IV-VI + VIII) was a significant predictor of future deterioration of the 9HPT of the non-dominant hand. In SPMS, the atrophy rate of the posterior superior lobe (VI + Crus I) was a significant predictor of future PASAT performance deterioration. Regional cerebellar volume reduction is associated with motor and cognitive disability in MS and may serve as a predictor for future disease progression, especially of dexterity and impaired processing speed.

A systematic review of resting state functional MRI connectivity changes and cognitive impairment in multiple sclerosis

INTRODUCTION

Cognitive impairment in multiple sclerosis (MS) is increasingly being investigated with resting state functional MRI (rs-fMRI) functional connectivity (FC) . However, results remain difficult to interpret, showing both high and low FC associated with cognitive impairment. We conducted a systematic review of rs-fMRI studies in MS to understand whether the direction of FC change relates to cognitive dysfunction, and how this may be influenced by the choice of methodology.

METHODS

Embase, Medline and PsycINFO were searched for studies assessing cognitive function and rs-fMRI FC in adults with MS.

RESULTS

Fifty-seven studies were included in a narrative synthesis. Of these, 50 found an association between cognitive impairment and FC abnormalities. Worse cognition was linked to high FC in 18 studies, and to low FC in 17 studies. Nine studies found patterns of both high and low FC related to poor cognitive performance, in different regions or for different MR metrics. There was no clear link to increased FC during early stages of MS and reduced FC in later stages, as predicted by common models of MS pathology. Throughout, we found substantial heterogeneity in study methodology, and carefully consider how this may impact on the observed findings.

DISCUSSION

These results indicate an urgent need for greater standardisation in the field - in terms of the choice of MRI analysis and the definition of cognitive impairment. This will allow us to use rs-fMRI FC as a biomarker in future clinical studies, and as a tool to understand mechanisms underpinning cognitive symptoms in MS.

Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis

Cognitive impairment (CI) occurs in 43 to 70% of multiple sclerosis (MS) patients at both early and later disease stages. Cognitive domains typically involved in MS include attention, information processing speed, memory, and executive control. The growing use of advanced magnetic resonance imaging (MRI) techniques is furthering our understanding on the altered structural connectivity (SC) and functional connectivity (FC) substrates of CI in MS. Regarding SC, different diffusion tensor imaging (DTI) measures (e.g., fractional anisotropy, diffusivities) along tractography-derived white matter (WM) tracts showed relevance toward CI. Novel diffusion MRI techniques, including diffusion kurtosis imaging, diffusion spectrum imaging, high angular resolution diffusion imaging, and neurite orientation dispersion and density imaging, showed more pathological specificity compared to the traditional DTI but require longer scan time and mathematical complexities for their interpretation. As for FC, task-based functional MRI (fMRI) has been traditionally used in MS to brain mapping the neural activity during various cognitive tasks. Analysis methods of resting fMRI (seed-based, independent component analysis, graph analysis) have been applied to uncover the functional substrates of CI in MS by revealing adaptive or maladaptive mechanisms of functional reorganization. The relevance for CI in MS of SC–FC relationships, reflecting common pathogenic mechanisms in WM and gray matter, has been recently explored by novel MRI analysis methods. This review summarizes recent advances on MRI techniques of SC and FC and their potential to provide a deeper understanding of the pathological substrates of CI in MS.

The cerebellum and its network: Disrupted static and dynamic functional connectivity patterns and cognitive impairment in multiple sclerosis

Background:

The impact of cerebellar damage and (dys)function on cognition remains understudied in multiple sclerosis.

Objective:

To assess the cognitive relevance of cerebellar structural damage and functional connectivity (FC) in relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS).

Methods:

This study included 149 patients with early RRMS, 81 late RRMS, 48 SPMS and 82 controls. Cerebellar cortical imaging included fractional anisotropy, grey matter volume and resting-state functional magnetic resonance imaging (MRI). Cerebellar FC was assessed with literature-based resting-state networks, using static connectivity (that is, conventional correlations), and dynamic connectivity (that is, fluctuations in FC strength). Measures were compared between groups and related to disability and cognition.

Results:

Cognitive impairment (CI) and cerebellar damage were worst in SPMS. Only SPMS showed cerebellar connectivity changes, compared to early RRMS and controls. Lower static FC was seen in fronto-parietal and default-mode networks. Higher dynamic FC was seen in dorsal and ventral attention, default-mode and deep grey matter networks. Cerebellar atrophy and higher dynamic FC together explained 32% of disability and 24% of cognitive variance. Higher dynamic FC was related to working and verbal memory and to information processing speed.

Conclusion:

Cerebellar damage and cerebellar connectivity changes were most prominent in SPMS and related to worse CI.

Neuroimaging Correlates of Cognitive Dysfunction in Adults with Multiple Sclerosis

Cognitive impairment is a frequent and meaningful symptom in multiple sclerosis (MS), caused by the accrual of brain structural damage only partially counteracted by effective functional reorganization. As both these aspects can be successfully investigated through the application of advanced neuroimaging, here, we offer an up-to-date overview of the latest findings on structural, functional and metabolic correlates of cognitive impairment in adults with MS, focusing on the mechanisms sustaining damage accrual and on the identification of useful imaging markers of cognitive decline.

A Comprehensive Approach to Disentangle the Effect of Cerebellar Damage on Physical Disability in Multiple Sclerosis

Cerebellar damage occurs frequently in multiple sclerosis (MS) patients, with a wide exhibition of symptoms particularly as impairments of balance and gait. Recent studies implementing new postprocessing magnetic resonance imaging (MRI) techniques showed how cerebellar subregional atrophy provides an explanation of disability in MS. The aim of this work was to evaluate the relationship between quantitative measures of physical disability, cerebellar subregional atrophy, and cerebellar peduncle disruption. Forty-nine MS patients and 32 healthy subjects as controls (HS) underwent a 3-Tesla MRI including 3D T1-weighted and diffusion tensor imaging. Patients underwent static posturography to calculate the body's center of pressure (COP) displacement, Expanded Disability Status Scale (EDSS), and 25-ft walking test (25-FWT). Cerebellar lobular volumes were automatically calculated using the Spatially Unbiased Infratentorial Toolbox. Tract-based spatial statistics (TBSS) in FSL was used to process diffusion tensor imaging (DTI) Fit-generated fractional anisotropy (FA) maps to assess structural connectivity of cerebellar peduncles. Stepwise multivariate linear regression analyses were used to explore relationships between variables. Cerebellar volumes (anterior and posterior, as well as lobular volumes from I to X) were significantly lower in patients with MS than HS (p < 0.05). FA in all cerebellar peduncles was lower in MS patients than in HS (p < 0.05). EDSS and 25-FWT showed an association with atrophy of lobule VIIIb (β = −0.37, p < 0.01, and β = −0.45, p < 0.001, respectively) COP measures inversely correlated with volume of lobules I–IV (β = −0.37, p < 0.01, and β = −0.36, p < 0.01). Lower FA in the three cerebellar peduncles of MS patients positively correlated with cerebellar lobular volumes. Our findings show how sensorimotor cerebellum atrophy and disruption of both afferent and efferent cerebellar connections contribute to physical disability in MS patients.

Resting-state functional connectivity of anterior and posterior cerebellar lobes is altered in multiple sclerosis

BACKGROUND

Damage to the cerebellar sensorimotor and cognitive domains may underlie physical and cognitive disability.

OBJECTIVE

To investigate resting-state functional connectivity (FC) of sensorimotor and cognitive cerebellum, and clinical correlates in multiple sclerosis (MS).

METHODS

A total of 119 patients with MS and 42 healthy subjects underwent multimodal 3T-magnetic resonance imaging (MRI). Patients were evaluated using the Expanded Disability Status Scale and Multiple Sclerosis Functional Composite Scale. After parcellation of sensorimotor (lobules I-V + VIII) and cognitive cerebellum (lobules VI, VII, IX, X), we calculated cerebellar resting-state FC using a seed-based approach.

RESULTS

In patients with MS, the sensorimotor cerebellum showed increased FC mainly with cerebellar, thalamic, and cortical (frontal, parietal, temporal) areas and decreased FC with insular areas; the cognitive cerebellum showed increased FC mainly with thalamic and cortical (temporal-occipital) areas, and decreased FC with frontal-insular areas. Both sensorimotor and cognitive cerebellar FC negatively correlated with disability, and positively with cognitive scores. Cerebellar structural damage only partially influenced results.

CONCLUSION

The two neocerebellar circuits showed altered FC with subcortical and cortical areas. The association between increased sensorimotor and cognitive cerebellar FC and low levels of physical and cognitive disability suggests that altered FC might modulate the effects of cerebellar structural damage on clinical condition.

The Relationship Between Zebrin Expression and Cerebellar Functions: Insights From Neuroimaging Studies

The cerebellum has long been known to play an important role in motor and balance control, and accumulating evidence has revealed that it is also involved in multiple cognitive functions. However, the evidence from neuroimaging studies and clinical observations is not well-integrated at the anatomical or molecular level. The goal of this review is to summarize and link different aspects of the cerebellum, including molecular patterning, functional topography images, and clinical cerebellar disorders. More specifically, we explored the potential relationships between the cerebrocerebellar connections and the expression of particular molecules and, in particular, zebrin stripe (a Purkinje cell-specific antibody molecular marker, which is a glycolytic enzyme expressed in cerebellar Purkinje cells). We hypothesized that the zebrin patterns contribute to cerebellar functional maps—especially when cerebrocerebellar circuit changes exist in cerebellar-related diseases. The zebrin stripe receives input from climbing fibers and project to different parts of the cerebral cortex through its cerebrocerebellar connection. Since zebrin-positive cerebellar Purkinje cells are resistant to excitotoxicity and cell injury while zebrin-negative zones are more prone to damage, we suggest that motor control dysfunction symptoms such as ataxia and dysmetria present earlier and are easier to observe than non-ataxia symptoms due to zebrin-negative cell damage by cerebrocerebellar connections. In summary, we emphasize that the molecular zebrin patterns provide the basis for a new viewpoint from which to investigate cerebellar functions and clinico-neuroanatomic correlations.