Abnormal regional homogeneity in patients with essential tremor revealed by resting-state functional MRI

Differential patterns of functional connectivity in tremor dominant Parkinson's disease and essential tremor plus

Tremor dominant Parkinson's disease (TDPD) and essential tremor plus (ETP) syndrome are commonly encountered tremor dominant neurological disorders. Although the basal ganglia thalamocortical (BGTC) and cerebello thalamocortical (CTC) networks are implicated in tremorogenesis, the extent of functional connectivity alterations across disorders is uncertain. This study aims to evaluate functional connectivity of the BGTC and CTC in TDPD and ETP. Resting state functional MRI was acquired for 25 patients with TDPD, ETP and 22 healthy controls (HC). Following pre-processing and denoising, seed-to-voxel based connectivity was carried out at FDR < 0.05 using ROIs belonging to the BGTC and CTC. Fahn-Tolosa-Marin tremor rating scale (FTMRS) was correlated with the average connectivity values at FDR < 0.05. Compared to HC, TDPD showed decreased connectivity between cerebellum and pre, post central gyrus. While, ETP showed decreased connectivity between pallidum and occipital cortex, precuneus, cuneus compared to HC. In comparison to ETP, TDPD showed increased connectivity between precentral gyrus, pallidum, SNc with the default mode network (DMN), and decreased connectivity between cerebellum with superior, middle frontal gyrus was observed. Tremor severity positively correlated with connectivity between SNc and DMN in TDPD, and negatively correlated with pallidal connectivity in ETP. Pattern of BGTC, CTC involvement is differential i.e., higher connectivity of the BGTC nodes in TDPD, and higher connectivity of cerebellar nodes in ETP. The interesting observation of pallidal involvement in ETP suggests the role of BGTC in the pathogenesis of ETP, and indicated similarities in concepts of tremor genesis in TDPD and ETP.

Evaluating functional connectivity differences between DBS ON/OFF states in essential tremor

Deep brain stimulation (DBS) targeting the ventral intermediate (Vim) nucleus of the thalamus is an effective treatment for essential tremor (ET). We studied 15 ​ET patients undergoing DBS to a major input/output tract of the Vim, the dentato-rubro-thalamic tract (DRTt), using resting state functional MRI (rsfMRI) to evaluate connectivity differences between DBS ON and OFF and elucidate significant regions most influential in impacting tremor control and/or concomitant gait ataxia. Anatomical/functional 1.5T MRIs were acquired and replicated for each DBS state. Tremor severity and gait ataxia severity were scored with DBS ON at optimal stimulation parameters and immediately upon DBS OFF. Whole brain analysis was performed using dual regression analysis followed by randomized permutation testing for multiple correction comparison. Regions of interest (ROI) analysis was also performed. All 15 patients had tremor improvement between DBS ON/OFF (p ​< ​0.001). Whole brain analysis revealed significant connectivity changes between states in the left pre-central gyrus and left supplemental motor area. Group analysis of ROIs revealed that, with threshold p ​< ​0.05, in DBS ON vs. OFF both tremor duration and tremor improvement were significantly correlated to changes in connectivity. A sub-group analysis of patients with greater ataxia had significantly decreased functional connectivity between multiple ROIs in the cortex and cerebellum when DBS was ON compared to OFF. Stimulation of the DRTt and concordant improvement of tremor resulted in connectivity changes seen in multiple regions outside the motor network; when combined with both structural and electrophysiologic connectivity, this may help to serve as a biomarker to improve DBS targeting and possibly predict outcome.

Combined brain topological metrics with machine learning to distinguish essential tremor and tremor-dominant Parkinson's disease

BACKGROUND

Essential tremor (ET) and Parkinson's disease (PD) are the two most prevalent movement disorders, sharing several overlapping tremor clinical features. Although growing evidence pointed out that changes in similar brain network nodes are associated with these two diseases, the brain network topological properties are still not very clear.

OBJECTIVE

The combination of graph theory analysis with machine learning (ML) algorithms provides a promising way to reveal the topological pathogenesis in ET and tremor-dominant PD (tPD).

METHODS

Topological metrics were extracted from Resting-state functional images of 86 ET patients, 86 tPD patients, and 86 age- and sex-matched healthy controls (HCs). Three steps were conducted to feature dimensionality reduction and four frequently used classifiers were adopted to discriminate ET, tPD, and HCs.

RESULTS

A support vector machine classifier achieved the best classification performance of four classifiers for discriminating ET, tPD, and HCs with 89.0% mean accuracy (mACC) and was used for binary classification. Particularly, the binary classification performances among ET vs. tPD, ET vs. HCs, and tPD vs. HCs were with 94.2% mACC, 86.0% mACC, and 86.3% mACC, respectively. The most power discriminative features were mainly located in the default, frontal-parietal, cingulo-opercular, sensorimotor, and cerebellum networks. Correlation analysis results showed that 2 topological features negatively and 1 positively correlated with clinical characteristics.

CONCLUSIONS

These results demonstrated that combining topological metrics with ML algorithms could not only achieve high classification accuracy for discrimination ET, tPD, and HCs but also help to reveal the potential brain topological network pathogenesis in ET and tPD.

Differences in Olivo-Cerebellar Circuit and Cerebellar Network Connectivity in Essential Tremor: a Resting State fMRI Study

The olivo-cerebellar circuit is thought to play a crucial role in the pathophysiology of essential tremor (ET). Whether olivo-cerebellar circuit dysfunction is also present at rest, in the absence of clinical tremor and linked voluntary movement, remains unclear. Assessing this network in detail with fMRI is challenging, considering the brainstem is close to major arteries and pulsatile cerebrospinal fluid-filled spaces obscuring signals of interest. Here, we used methods tailored to the analysis of infratentorial structures. We hypothesize that the olivo-cerebellar circuit shows altered intra-network connectivity at rest and decreased functional coupling with other parts of the motor network in ET. In 17 ET patients and 19 healthy controls, we investigated using resting state fMRI intracerebellar functional and effective connectivity on a dedicated cerebellar atlas. With independent component analysis, we investigated data-driven cerebellar motor network activations during rest. Finally, whole-brain connectivity of cerebellar motor structures was investigated using identified components. In ET, olivo-cerebellar pathways show decreased functional connectivity compared with healthy controls. Effective connectivity analysis showed an increased inhibitory influence of the dentate nucleus towards the inferior olive. Cerebellar independent component analyses showed motor resting state networks are less strongly connected to the cerebral cortex compared to controls. Our results indicate the olivo-cerebellar circuit to be affected at rest. Also, the cerebellum is "disconnected" from the rest of the motor network. Aberrant activity, generated within the olivo-cerebellar circuit could, during action, spread towards other parts of the motor circuit and potentially underlie the characteristic tremor of this patient group.

Large-scale networks changes in Wilson's disease associated with neuropsychiatric impairments: a resting-state functional magnetic resonance imaging study

BACKGROUND

In Wilson's disease (WD) patients, network connections across the brain are disrupted, affecting multidomain function. However, the details of this neuropathophysiological mechanism remain unclear due to the rarity of WD. In this study, we aimed to investigate alterations in brain network connectivity at the whole-brain level (both intra- and inter-network) in WD patients through independent component analysis (ICA) and the relationship between alterations in these brain network functional connections (FCs) and clinical neuropsychiatric features to understand the underlying pathophysiological and central compensatory mechanisms.

METHODS

Eighty-five patients with WD and age- and sex-matched 85 healthy control (HC) were recruited for resting-state functional magnetic resonance imaging (rs-fMRI) scanning. We extracted the resting-state networks (RSNs) using the ICA method, analyzed the changes of FC in these networks and the correlation between alterations in FCs and clinical neuropsychiatric features.

RESULTS

Compared with HC, WD showed widespread lower connectivity within RSNs, involving default mode network (DMN), frontoparietal network (FPN), somatomotor network (SMN), dorsal attention network (DAN), especially in patients with abnormal UWDRS scores. Furthermore, the decreased FCs in the left medial prefrontal cortex (L_ MPFC), left anterior cingulate gyrus (L_ACC), precuneus (PCUN)within DMN were negatively correlated with the Unified Wilson's Disease Rating Scale-neurological characteristic examination (UWDRS-N), and the decreased FCs in the L_MPFC, PCUN within DMN were negatively correlated with the Unified Wilson's Disease Rating Scale-psychiatric symptoms examination (UWDRS-P). We additionally discovered that the patients with WD exhibited significantly stronger FC between the FPN and DMN, between the DAN and DMN, and between the FPN and DAN compared to HC.

CONCLUSIONS

We have provided evidence that WD is a disease with widespread dysfunctional connectivity in resting networks in brain, leading to neurological features and psychiatric symptoms (e.g. higher-order cognitive control and motor control impairments). The alter intra- and inter-network in the brain may be the neural underpinnings for the neuropathological symptoms and the process of injury compensation in WD patients.

MRgFUS of the nucleus ventralis intermedius in essential tremor modulates functional connectivity within the classical tremor network and beyond

BACKGROUND

Magnetic resonance-guided focused ultrasound (MRgFUS) of the thalamic ventral intermediate nucleus is an incisionless lesional treatment for essential tremor.

OBJECTIVE

To examine relationships between tremor severity and functional connectivity in patients with essential tremor and to assess long-term changes in the tremor network after sonication of the ventral intermediate nucleus.

METHODS

Twenty-one patients with essential tremor (70.33 ± 11.32 years) were included in the final analysis and underwent resting state functional magnetic resonance imaging at 3 T before and 6 months after treatment. Tremor severity (Fahn-Tolosa-Marin Clinical Rating Scale) was evaluated and functional connectivity was investigated using independent component analysis.

RESULTS

MRgFUS of the thalamic ventral intermediate nucleus reduced contralateral tremor effectively. Multiple regression analysis revealed exclusively negative correlations between FC and tremor severity, notably in the right cerebellar lobe VI and the left cerebellar lobe VIIIa (cerebellar network), in the left occipital fusiform gyrus (lateral visual network), the anterior division of the left superior temporal gyrus (fronto-parieto-temporal network), and in the posterior division of the left parahippocampal gyrus and the bilateral lingual gyri (default mode network). Six months after treatment, increased functional connectivity was observed in almost all tremor-associated clusters, except the cluster localized in the left cerebellum.

CONCLUSIONS

Our findings suggest that tremor-related activity in essential tremor extends beyond the classical cerebellar network, additionally involving areas related to visual processing. Functional restoration of network activity after sonication of the ventral intermediate nucleus is observed within the classical tremor network (cerebellum) and notably also in visual processing areas.

Structural brain differences in essential tremor and Parkinson's disease deep brain stimulation patients

BACKGROUND

Essential tremor (ET) and Parkinson's disease (PD) are the most common tremor disorders and are common indications for deep brain stimulation (DBS). In some patients, PD and ET symptoms overlap and diagnosis can be challenging based on clinical criteria alone. The objective of this study was to identify structural brain differences between PD and ET DBS patients to help differentiate these disorders and improve our understanding of the different brain regions involved in these pathologic processes.

METHODS

We included ET and PD patients scheduled to undergo DBS surgery in this observational study. Patients underwent 3T brain MRI while under general anesthesia as part of their procedure. Cortical thicknesses and subcortical volumes were quantified from T1-weighted images using automated multi-atlas segmentation. We used logistic regression analysis to identify brain regions associated with diagnosis of ET or PD.

RESULTS

149 ET and 265 PD patients were included. Smaller volumes in the pallidum and thalamus and reduced thickness in the anterior orbital gyrus, lateral orbital gyrus, and medial precentral gyrus were associated with greater odds of ET diagnosis. Conversely, reduced volumes in the caudate, amygdala, putamen, and basal forebrain, and reduced thickness in the orbital part of the inferior frontal gyrus, supramarginal gyrus, and posterior cingulate were associated with greater odds of PD diagnosis.

CONCLUSIONS

These findings identify structural brain differences between PD and ET patients. These results expand our understanding of the different brain regions involved in these disorders and suggest that structural MRI may help to differentiate patients with these two disorders.

Cortical mean diffusivity is reliable in measuring brain abnormalities in drug-naïve essential tremor patients

OBJECTIVE

Essential tremor (ET) is a common movement disorder, but the pathogenesis is poorly understood. Several associated brain areas were reported with inconsistent results due to heterogeneous populations. It is necessary to analyze a more homogeneous patient group.

METHODS

We recruited 25 drug-naïve ET patients and 36 age- and sex-matched controls. All participants were right-handed. ET. ET was defined according to diagnostic criteria of the Consensus Statement of the Movement Disorder Society on Tremor. ET patients were divided into sporadic (SET) and familial ET (FET). We assessed tremor severity in ET. The cortical microstructural changes were compared between ET patients and controls using mean diffusivity (MD) of diffusion tensor imaging, and cortical thickness. The correlation of tremor severity with the cortical MD and thickness were respectively analyzed.

RESULTS

MD values were increased in the insular, precuneus, medial orbitofrontal, posterior, and isthmus cingulate and temporo-occipital areas in ET. In comparison between SET and FET, MD values were higher in the superior and caudal middle frontal, postcentral, and temporo-occipital regions in FET. The cortical thickness of ET patients was more increased in the left lingual gyrus and lower in the right bankssts gyrus. We could not find any correlation of tremor severity with the MD values in ET patients. Still, there was a positive correlation with the cortical thickness of the frontal and parietal areas.

CONCLUSIONS

Our results support the idea that ET is a disorder that disrupts widespread brain regions and indicates that cortical MD may be more sensitive to measure brain abnormalities than cortical thickness.

Elevated Levels of Serum Biomarkers Associated with Damage to the CNS Neurons and Endothelial Cells Are Linked with Changes in Brain Connectivity in Breast Cancer Patients with Vestibulo-Atactic Syndrome

Vestibulo-atactic syndrome (VAS), which represents a combination of motor and vestibular disorders, can be manifested as a clinical complication of breast cancer treatment and has a significant impact on patients' quality of life. The identification of novel potential biomarkers that might help to predict the onset of VAS and its progression could improve the management of this group of patients. In the current study, the levels of intercellular cell adhesion molecule 1 (ICAM-1), platelet/endothelial cell adhesion molecule 1 (PECAM-1), NSE (neuron-specific enolase), and the antibodies recognizing NR-2 subunit of NMDA receptor (NR-2-ab) were measured in the blood serum of BC survivor patients with vestibulo-atactic syndrome (VAS) and associated with the brain connectome data obtained via functional magnetic resonance imaging (fMRI) studies. A total of 21 patients were registered in this open, single-center trial and compared to age-matched healthy female volunteers (control group) (n = 17). BC patients with VAS demonstrated higher serum levels of ICAM-1, PECAM-1, and NSE and a lower value of NR-2-ab, with values of 654.7 ± 184.8, 115.3 ± 37.03, 49.9 ± 103.9, and 0.5 ± 0.3 pg/mL, respectively, as compared to the healthy volunteers, with 230.2 ± 44.8, 62.8 ± 15.6, 15.5 ± 6.4, and 1.4 ± 0.7 pg/mL. According to the fMRI data (employing seed-to-voxel and ROI-to-ROI methods), in BC patients with VAS, significant changes were detected in the functional connectivity in the areas involved in the regulation of postural-tonic reflexes, the coordination of movements, and the regulation of balance. In conclusion, the detected elevated levels of serum biomarkers may reveal damage to the CNS neurons and endothelial cells that is, in turn, associated with the change in the brain connectivity in this group of patients.

Identification of essential tremor based on resting-state functional connectivity

Currently, machine-learning algorithms have been considered the most promising approach to reach a clinical diagnosis at the individual level. This study aimed to investigate whether the whole-brain resting-state functional connectivity (RSFC) metrics combined with machine-learning algorithms could be used to identify essential tremor (ET) patients from healthy controls (HCs) and further revealed ET-related brain network pathogenesis to establish the potential diagnostic biomarkers. The RSFC metrics obtained from 127 ET patients and 120 HCs were used as input features, then the Mann-Whitney U test and the least absolute shrinkage and selection operator (LASSO) methods were applied to reduce feature dimensionality. Four machine-learning algorithms were adopted to identify ET from HCs. The accuracy, sensitivity, specificity and the area under the curve (AUC) were used to evaluate the classification performances. The support vector machine, gradient boosting decision tree, random forest and Gaussian naïve Bayes algorithms could achieve good classification performances with accuracy at 82.8%, 79.4%, 78.9% and 72.4%, respectively. The most discriminative features were primarily located in the cerebello-thalamo-motor and non-motor circuits. Correlation analysis showed that two RSFC features were positively correlated with tremor frequency and four RSFC features were negatively correlated with tremor severity. The present study demonstrated that combining the RSFC matrices with multiple machine-learning algorithms could not only achieve high classification accuracy for discriminating ET patients from HCs but also help us to reveal the potential brain network pathogenesis in ET.

Challenging functional connectivity data: machine learning application on essential tremor recognition

BACKGROUND AND AIMS

This paper aimed to investigate the usefulness of applying machine learning on resting-state fMRI connectivity data to recognize the pattern of functional changes in essential tremor (ET), a disease characterized by slight brain abnormalities, often difficult to detect using univariate analysis.

METHODS

We trained a support vector machine with a radial kernel on the mean signals extracted by 14 brain networks obtained from resting-state fMRI scans of 18 ET and 19 healthy control (CTRL) subjects. Classification performance between pathological and control subjects was evaluated using a tenfold cross-validation. Recursive feature elimination was performed to rank the importance of the extracted features. Moreover, univariate analysis using Mann-Whitney U test was also performed.

RESULTS

The machine learning algorithm achieved an AUC of 0.75, with four networks (language, primary visual, cerebellum, and attention), which have an essential role in ET pathophysiology, being selected as the most important features for classification. By contrast, the univariate analysis was not able to find significant results among these two conditions.

CONCLUSION

The machine learning approach identifies the changes in functional connectivity of ET patients, representing a promising instrument to discriminate specific pathological conditions and find novel functional biomarkers in resting-state fMRI studies.

Postmortem Cerebellar Volume Is Not Reduced in Essential Tremor: A Comparison with Multiple System Atrophy and Controls

BACKGROUND

Essential tremor (ET) is a common movement disorder in which cerebellar microscopic and volume alterations have been repeatedly reported although with disagreement between studies. However, pronounced heterogeneity was found with regard to cerebellar volume alterations.

OBJECTIVE

This study aimed to assess postmortem cerebellar volume in subjects with or without ET, as compared with subjects with multiple system atrophy (MSA), a well-established cerebellar neurodegeneration.

METHODS

Cases with ET (n = 29), MSA (n = 7), and non-demented control cases without any movement disorder (n = 22) were selected from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND), a longitudinal clinicopathological study with annual research-dedicated clinical assessments by neuropsychologists, subspecialist movement disorders, and cognitive/behavioral neurologists, with comprehensive neuropathological examinations after death. Group comparisons were controlled for common age-related neurodegenerative and cerebrovascular pathologies. Cerebellar volumes were calculated using digital images of slices taken at the time of autopsy, immediately after brain removal and before fixation.

RESULTS

Cerebellar volume was not reduced in ET subjects compared to controls. The two groups did not differ in terms of incidental cerebrovascular and Alzheimer's disease neuropathology. In contrast, cerebellar volume was significantly reduced in subjects with MSA when compared to ET and control subjects.

CONCLUSION

In a well-characterized cohort, postmortem cerebellar volume measurements suggest that there are no volume alterations in ET when compared to controls, in contrast to significant cerebellar atrophy in subjects with MSA.

Exploring the heterogeneous morphometric data in essential tremor with probabilistic modelling

Essential tremor (ET) is a prevalent movement disorder characterized by marked clinical heterogeneity. Here, we explored the morphometric underpinnings of this cross-subject variability on a cohort of 34 patients with right-dominant drug-resistant ET and 29 matched healthy controls (HCs). For each brain region, group-wise morphometric data was modelled by a multivariate Gaussian to account for morphometric features' (co)variance. No group differences were found in terms of mean values, highlighting the limits of more basic group comparison approaches. Variance in surface area was higher in ET in the left lingual and caudal anterior cingulate cortices, while variance in mean curvature was lower in the right superior temporal cortex and pars triangularis, left supramarginal gyrus and bilateral paracentral gyrus. Heterogeneity further extended to the right putamen, for which a mixture of two Gaussians fitted the ET data better than a single one. Partial Least Squares analysis revealed the rich clinical relevance of the ET population's heterogeneity: first, increased head tremor and longer symptoms' duration were accompanied by broadly lower cortical gyrification. Second, more severe upper limb tremor and impairments in daily life activities characterized the patients whose morphometric profiles were more atypical compared to the average ET population, irrespective of the exact nature of the alterations. Our results provide candidate morphometric substrates for two different types of clinical variability in ET. They also demonstrate the importance of relying on analytical approaches that can efficiently handle multivariate data and enable to test more sophisticated hypotheses regarding its organization.

Altered brain connectivity in hyperkinetic movement disorders: A review of resting-state fMRI

BACKGROUND

Hyperkinetic movement disorders (HMD) manifest as abnormal and uncontrollable movements. Despite reported involvement of several neural circuits, exact connectivity profiles remain elusive.

OBJECTIVES

Providing a comprehensive literature review of resting-state brain connectivity alterations using resting-state fMRI (rs-fMRI). We additionally discuss alterations from the perspective of brain networks, as well as correlations between connectivity and clinical measures.

METHODS

A systematic review was performed according to PRISMA guidelines and searching PubMed until October 2022. Rs-fMRI studies addressing ataxia, chorea, dystonia, myoclonus, tics, tremor, and functional movement disorders (FMD) were included. The standardized mean difference was used to summarize findings per region in the Automated Anatomical Labeling atlas for each phenotype. Furthermore, the activation likelihood estimation meta-analytic method was used to analyze convergence of significant between-group differences per phenotype. Finally, we conducted hierarchical cluster analysis to provide additional insights into commonalities and differences across HMD phenotypes.

RESULTS

Most articles concerned tremor (51), followed by dystonia (46), tics (19), chorea (12), myoclonus (11), FMD (11), and ataxia (8). Altered resting-state connectivity was found in several brain regions: in ataxia mainly cerebellar areas; for chorea, the caudate nucleus; for dystonia, sensorimotor and basal ganglia regions; for myoclonus, the thalamus and cingulate cortex; in tics, the basal ganglia, cerebellum, insula, and frontal cortex; for tremor, the cerebello-thalamo-cortical circuit; finally, in FMD, frontal, parietal, and cerebellar regions. Both decreased and increased connectivity were found for all HMD. Significant spatial convergence was found for dystonia, FMD, myoclonus, and tremor. Correlations between clinical measures and resting-state connectivity were frequently described.

CONCLUSION

Key brain regions contributing to functional connectivity changes across HMD often overlap. Possible increases and decreases of functional connections of a specific region emphasize that HMD should be viewed as a network disorder. Despite the complex interplay of physiological and methodological factors, this review serves to gain insight in brain connectivity profiles across HMD phenotypes.

Assessing the impact of MR-guided focused ultrasound thalamotomy on brain activity and connectivity in patients with essential tremor

OBJECTIVE

Although magnetic resonance-guided focused ultrasound (MRgFUS) at the ventral intermediate (VIM) thalamic nucleus is a novel and effective treatment for medication-refractory essential tremor (ET), it is unclear how the ablation lesion affects functional activity. The current study sought to evaluate the functional impact of MRgFUS thalamotomy in patients with ET, as well as to investigate the relationship between neuronal activity changes and tremor control.

METHODS

This study included 30 patients with ET who underwent MRgFUS thalamotomy with a 6-month follow-up involving MRI and clinical tremor rating. Additional sex- and age-matched healthy people were recruited for the healthy control group. The fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity were used to identify functional alteration regions of interest (ROIs). To investigate changes after treatment, ROI- and seed-based functional connectivity (FC) analyses were performed.

RESULTS

Patients with ET had significantly increased fALFF in the right postcentral gyrus (PoCG; ROI 1), regional homogeneity in the left PoCG (ROI 2), and regional homogeneity in the right PoCG (ROI 3, cluster-level p value family-wise error [pFWE] < 0.05), which were recovered and normalized at 6 months after MRgFUS thalamotomy. FCs between ROI 2 and the right supramarginal gyrus, ROI 2 and the right superior parietal gyrus, and ROI 3 and the left precentral gyrus were also found to be increased after treatment (cluster-level pFWE < 0.05). Furthermore, changes in fALFF, regional homogeneity, and FC values were significantly correlated with tremor relief (p < 0.05). Preoperative FC strengths were found to be inversely related to the postoperative tremor control ratio (p < 0.05).

CONCLUSIONS

In patients with ET, the VIM lesion of MRgFUS thalamotomy resulted in symptom-related regional functional recovery associated with sensorimotor and attention networks. Preoperative FC strengths may reflect the postoperative tremor control ratio, implying that this metric could be a useful neuroimaging biomarker for predicting symptom relief in patients with ET following thalamotomy.

Identifying and distinguishing of essential tremor and Parkinson's disease with grouped stability analysis based on searchlight-based MVPA

BACKGROUND

Since both essential tremor (ET) and Parkinson's disease (PD) are movement disorders and share similar clinical symptoms, it is very difficult to recognize the differences in the presentation, course, and treatment of ET and PD, which leads to misdiagnosed commonly.

PURPOSE

Although neuroimaging biomarker of ET and PD has been investigated based on statistical analysis, it is unable to assist the clinical diagnosis of ET and PD and ensure the efficiency of these biomarkers. The aim of the study was to identify the neuroimaging biomarkers of ET and PD based on structural magnetic resonance imaging (MRI). Moreover, the study also distinguished ET from PD via these biomarkers to validate their classification performance.

METHODS

This study has developed and implemented a three-level machine learning framework to identify and distinguish ET and PD. First of all, at the model-level assessment, the searchlight-based machine learning method has been used to identify the group differences of patients (ET/PD) with normal controls (NCs). And then, at the feature-level assessment, the stability of group differences has been tested based on structural brain atlas separately using the permutation test to identify the robust neuroimaging biomarkers. Furthermore, the identified biomarkers of ET and PD have been applied to classify ET from PD based on machine learning techniques. Finally, the identified biomarkers have been compared with the previous findings of the biology-level assessment.

RESULTS

According to the biomarkers identified by machine learning, this study has found widespread alterations of gray matter (GM) for ET and large overlap between ET and PD and achieved superior classification performance (PCA + SVM, accuracy = 100%).

CONCLUSIONS

This study has demonstrated the significance of a machine learning framework to identify and distinguish ET and PD. Future studies using a large data set are needed to confirm the potential clinical application of machine learning techniques to discern between PD and ET.

Combined brain network topological metrics with machine learning algorithms to identify essential tremor

BACKGROUND AND OBJECTIVE

Essential tremor (ET) is a common movement syndrome, and the pathogenesis mechanisms, especially the brain network topological changes in ET are still unclear. The combination of graph theory (GT) analysis with machine learning (ML) algorithms provides a promising way to identify ET from healthy controls (HCs) at the individual level, and further help to reveal the topological pathogenesis in ET.

METHODS

Resting-state functional magnetic resonance imaging (fMRI) data were obtained from 101 ET and 105 HCs. The topological properties were analyzed by using GT analysis, and the topological metrics under every single threshold and the area under the curve (AUC) of all thresholds were used as features. Then a Mann-Whitney U-test and least absolute shrinkage and selection operator (LASSO) were conducted to feature dimensionality reduction. Four ML algorithms were adopted to identify ET from HCs. The mean accuracy, mean balanced accuracy, mean sensitivity, mean specificity, and mean AUC were used to evaluate the classification performance. In addition, correlation analysis was carried out between selected topological features and clinical tremor characteristics.

RESULTS

All classifiers achieved good classification performance. The mean accuracy of Support vector machine (SVM), logistic regression (LR), random forest (RF), and naïve bayes (NB) was 84.65, 85.03, 84.85, and 76.31%, respectively. LR classifier achieved the best classification performance with 85.03% mean accuracy, 83.97% sensitivity, and an AUC of 0.924. Correlation analysis results showed that 2 topological features negatively and 1 positively correlated with tremor severity.

CONCLUSION

These results demonstrated that combining topological metrics with ML algorithms could not only achieve high classification accuracy for discrimination ET from HCs but also help us to reveal the potential topological pathogenesis of ET.

Combined Intrinsic Local Functional Connectivity With Multivariate Pattern Analysis to Identify Depressed Essential Tremor

Background

Although depression is one of the most common neuropsychiatric symptoms in essential tremor (ET), the diagnosis biomarker and intrinsic brain activity remain unclear. We aimed to combine multivariate pattern analysis (MVPA) with local brain functional connectivity to identify depressed ET.

Methods

Based on individual voxel-level local brain functional connectivity (regional homogeneity, ReHo) mapping from 41 depressed ET, 43 non-depressed ET, and 45 healthy controls (HCs), the binary support vector machine (BSVM) and multiclass Gaussian Process Classification (MGPC) algorithms were used to identify depressed ET patients from non-depressed ET and HCs, the accuracy and permutations test were used to assess the classification performance.

Results

The MGPC algorithm was able to classify the three groups (depressed ET, non-depressed ET, and HCs) with a total accuracy of 84.5%. The BSVM algorithm achieved a better classification performance with total accuracy of 90.7, 88.64, and 90.48% for depressed ET vs. HCs, non-depressed ET vs. HCs, and depressed ET vs. non-depressed ET, and the sensitivity for them at 80.49, 76.64, and 80.49%, respectively. The significant discriminative features of depressed ET vs. HCs were primarily located in the cerebellar-motor-prefrontal gyrus-anterior cingulate cortex pathway, and for depressed ET vs. non-depressed ET located in the cerebellar-prefrontal gyrus-anterior cingulate cortex circuits. The partial correlation showed that the ReHo values in the bilateral middle prefrontal gyrus (positive) and the bilateral cerebellum XI (negative) were significantly correlated with clinical depression severity.

Conclusion

Our findings suggested that combined individual ReHo maps with MVPA not only could be used to identify depressed ET but also help to reveal the intrinsic brain activity changes and further act as the potential diagnosis biomarker in depressed ET patients.

Brain Structure Alterations in Hemifacial Spasm: A Diffusion Tensor Imaging Study

This study examined white matter integrity in patients with left-sided hemifacial spasm (HFS) using diffusion tensor imaging (DTI). Thirty-six patients with left-sided HFS (mean age 53.24 ± 8.16 years) and 36 healthy volunteers (mean age 53.92 ± 7.73 years) were recruited. Tract-based spatial statistics (TBSS) analysis revealed significantly increased fractional anisotropy (FA) of bilateral superior longitudinal fasciculus in HFS patients (P < 0.05, family-wise error corrected), with trends for radial diffusivity to decrease. We inferred that the results may be associated with poor sleep quality, impairment in visuospatial construction, and activity-dependent increases in myelination in HFS patients. Furthermore, the FA value of left superior longitudinal fasciculus showed a positive correlation with HFS duration (r = 0.352, P = .041) and spasm severity (r = 0.416, P = .014). However, the alteration of medial diffusivity and axial diffusivity were not found in bilateral superior longitudinal fasciculus between groups. These findings suggest FA changes of superior longitudinal fasciculus reflected by TBSS analysis may provide valuable insights into the diagnosis of HFS.

Morphological and morphometric changes in the Purkinje cells of patients with essential tremor

Essential tremor (ET) is a progressive neurological syndrome characterised by involuntary tremors of the hands or arms, head, jaw and voice. The pathophysiology of ET is not clearly understood yet. However, previous studies have reported several changes in the brain of patients with ET. One of the brain areas extensively investigated is the cerebellum. In the present study, a morphometric analysis of Purkinje cells in patients with ET and ET-plus was performed, and subsequently compared with normal controls using the Golgi silver staining method and 3D neuronal reconstruction. Substantial morphological changes were uncovered in the Purkinje cells of patients with ET compared with normal controls, including a decreased dendritic length and field density, an overall loss of terminal branches and a decreased density of dendritic spines.

The Pathophysiology and Treatment of Essential Tremor: The Role of Adenosine and Dopamine Receptors in Animal Models

Essential tremor (ET) is one of the most common neurological disorders that often affects people in the prime of their lives, leading to a significant reduction in their quality of life, gradually making them unable to independently perform the simplest activities. Here we show that current ET pharmacotherapy often does not sufficiently alleviate disease symptoms and is completely ineffective in more than 30% of patients. At present, deep brain stimulation of the motor thalamus is the most effective ET treatment. However, like any brain surgery, it can cause many undesirable side effects; thus, it is only performed in patients with an advanced disease who are not responsive to drugs. Therefore, it seems extremely important to look for new strategies for treating ET. The purpose of this review is to summarize the current knowledge on the pathomechanism of ET based on studies in animal models of the disease, as well as to present and discuss the results of research available to date on various substances affecting dopamine (mainly D3) or adenosine A1 receptors, which, due to their ability to modulate harmaline-induced tremor, may provide the basis for the development of new potential therapies for ET in the future.

The Role of the Cerebellum in Tremor - Evidence from Neuroimaging

Background

Neuroimaging research has played a key role in identifying which cerebral changes are associated with tremor. Here we will focus on the cerebellum, which may drive tremor oscillations, process tremor-related afferents, modulate activity in remote brain regions, or a combination.

Methods

On the 6th of October 2021, we conducted a PubMed search to select articles providing neuroimaging evidence for cerebellar involvement in essential tremor (ET), Parkinson's disease (PD) tremor, and dystonic tremor (DT).

Results

In ET, tremor-related activity is found in motor areas of the bilateral cerebellum, and altered functional connectivity within and outside the cerebellum correlates with tremor severity. Furthermore, ET is associated with cerebellar atrophy, but also with compensatory structural changes outside the cerebellum (e.g. supplementary motor area). In PD, tremor-related cerebellar activity and increased cerebello-thalamic coupling has been found. Emerging evidence suggests that the cerebellum plays a key role in dopamine-resistant rest tremor and in postural tremor. Cerebellar structural alterations have been identified in PD, but only some relate to tremor. DT is associated with more widespread cerebral networks than other tremor types.

Discussion

In ET, the cerebellum likely acts as an oscillator, potentially due to loss of inhibitory mechanisms. In contrast, in PD the cerebellum may be a modulator, which contributes to tremor oscillations by influencing the thalamo-cortical system. The precise role of the cerebellum in DT remains unclear. We recommend that future research measures tremor-related activity directly by combining electrophysiology with neuroimaging, while brain stimulation techniques may be used to establish causality.

Highlights

This review of neuroimaging studies has provided convincing evidence that the cerebellum plays a key role in the pathophysiology of ET, PD tremor, and dystonic tremor syndromes. This contribution may consist of driving tremor oscillations, processing tremor-related afferents, modulating activity in remote brain regions, or all the above.

Essential tremor

Essential tremor (ET) is one of the most common movement disorders, with a reported >60 million affected individuals worldwide. The definition and underlying pathophysiology of ET are contentious. Patients present primarily with motor features such as postural and action tremors, but may also have other non-motor features, including cognitive impairment and neuropsychiatric symptoms. Genetics account for most of the ET risk but environmental factors may also be involved. However, the variable penetrance and challenges in validating data make gene-environment analysis difficult. Structural changes in cerebellar Purkinje cells and neighbouring neuronal populations have been observed in post-mortem studies, and other studies have found GABAergic dysfunction and dysregulation of the cerebellar-thalamic-cortical circuitry. Commonly prescribed medications include propranolol and primidone. Deep brain stimulation and ultrasound thalamotomy are surgical options in patients with medically intractable ET. Further research in post-mortem studies, and animal and cell-based models may help identify new pathophysiological clues and therapeutic targets and, together with advances in omics and machine learning, may facilitate the development of precision medicine for patients with ET.

Identifying Depressed Essential Tremor Using Resting-State Voxel-Wise Global Brain Connectivity: A Multivariate Pattern Analysis

Background and Objective: Although depression is one of the most common non-motor symptoms in essential tremor (ET), its pathogenesis and diagnosis biomarker are still unknown. Recently, machine learning multivariate pattern analysis (MVPA) combined with connectivity mapping of resting-state fMRI has provided a promising way to identify patients with depressed ET at the individual level and help to reveal the brain network pathogenesis of depression in patients with ET.

Methods: Based on global brain connectivity (GBC) mapping from 41 depressed ET, 49 non-depressed ET, 45 primary depression, and 43 healthy controls (HCs), multiclass Gaussian process classification (GPC) and binary support vector machine (SVM) algorithms were used to identify patients with depressed ET from non-depressed ET, primary depression, and HCs, and the accuracy and permutation tests were used to assess the classification performance.

Results: While the total accuracy (40.45%) of four-class GPC was poor, the four-class GPC could discriminate depressed ET from non-depressed ET, primary depression, and HCs with a sensitivity of 70.73% (P < 0.001). At the same time, the sensitivity of using binary SVM to discriminate depressed ET from non-depressed ET, primary depression, and HCs was 73.17, 80.49, and 75.61%, respectively (P < 0.001). The significant discriminative features were mainly located in cerebellar-motor-prefrontal cortex circuits (P < 0.001), and a further correlation analysis showed that the GBC values of significant discriminative features in the right middle prefrontal gyrus, bilateral cerebellum VI, and Crus 1 were correlated with clinical depression severity in patients with depressed ET.

Conclusion: Our findings demonstrated that GBC mapping combined with machine learning MVPA could be used to identify patients with depressed ET, and the GBC changes in cerebellar-prefrontal cortex circuits not only posed as the significant discriminative features but also helped to understand the network pathogenesis underlying depression in patients with ET.

The Contribution of Neuroimaging to the Understanding of Essential Tremor Pathophysiology: a Systematic Review

Essential tremor (ET) is one of the most common movement disorders. Over the last 10 years, magnetic resonance imaging (MRI) has shed light on the structural and functional abnormalities possibly involved in ET pathophysiology. In this systematic review, we aimed to identify the cortical and subcortical structures involved and the role that different brain areas play in the pathophysiology of motor and non-motor ET features. We found that structural (grey and white matter) cerebellar damage and connectivity alterations between the cerebellum and various cortical areas play a role in both motor and non-motor symptoms of ET. In particular, many studies found an association between MRI findings and non-motor symptoms.

Combination of structural MRI, functional MRI and brain PET-CT provide more diagnostic and prognostic value in patients of cerebellar ataxia associated with anti-Tr/DNER: a case report

Background

Brain magnetic resonance imaging (MRI) rarely reveals structural changes in patients with suspected anti-Tr/DNER encephalitis and thus provides very limited information. Here, we combined structural MRI, functional MRI, and positron emission tomography-computed tomography (PET-CT) findings to characterize this rare disorder in a patient.

Case presentation

A 43-year-old woman presented with progressive cerebellar ataxia, memory impairment, anxiety, and depression. Anti-Tr antibodies were detected in both her serum (1:10) and cerebrospinal fluid (1:10). A diagnosis of anti-Tr-positive autoimmune cerebellar ataxia was established. The patient’s symptoms were worse, but her brain MRI was normal. Meanwhile, voxel-based morphometry analysis showed bilateral reduced cerebellar volume, especially in the posterior lobe and uvula of the cerebellum and the middle of the left temporal lobe compared with 6 sex- and age-matched healthy subjects (6 females, 43 ± 2 years; p < 0.05). Using seed-based functional connectivity analysis, decreased connectivity between the posterior cingulate cortex/precuneus and left frontal lobe compared to the control group (p < 0.05) was detected. PET-CT revealed bilateral hypometabolism in the cerebellum and relative hypermetabolism in the cerebellar vermis and bilateral frontal lobe, but no malignant changes.

Conclusions

A combination of structural MRI, functional MRI, and brain PET-CT has higher diagnostic and prognostic value than conventional MRI in patients with suspected anti-Tr/DNER encephalitis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02403-5.

Postural tremor in L-2-hydroxyglutaric aciduria is associated with cerebellar atrophy

OBJECTIVE

In this study, we performed analysis of brainstem reflexes and movement disorders using surface polymyogram in L-2-hydroxyglutaric aciduria (L2HGA). We also reviewed all cases in the literature with detailed clinical and radiological description to analyze the anatomical correlates of involuntary movements.

PATIENTS AND METHOD

We performed surface electromyography of appropriate muscles, long-loop reflexes, and somatosensory evoked potentials and analyzed the neuroimaging findings in patients with L2HGA and recorded blink reflex (BR), auditory startle response (ASR), and startle response after somatosensory stimuli (SSS) in patients and healthy subjects. We also performed a systematic literature search to identify the association of neuroimaging findings and movements disorders in previous patients with L2HGA.

RESULTS

Thirteen patients were enrolled in the study. Among them, ten had low-amplitude postural tremor with a frequency between 4 and 7 Hz. The tremor was predominant on distal parts of the upper extremities. Postural tremor was accompanied by negative myoclonus in one-third. The BR, ASR, and SSS, all, were hypoactive. There was a close association of postural tremor with cerebellar atrophy in patients who participated in this study and by the analysis of the previously reported patients.

CONCLUSIONS

Low-amplitude postural tremor is common in L2HGA. It is related with cerebellar atrophy. Although the neuroimaging shows no overt lesions at the brainstem, there is a functional inhibition at this level.

Imaging the Pathophysiology of Essential Tremor-A Systematic Review

Background: The pathophysiology underlying essential tremor (ET) still is poorly understood. Recent research suggests a pivotal role of the cerebellum in tremor genesis, and an ongoing controversy remains as to whether ET constitutes a neurodegenerative disorder. In addition, mounting evidence indicates that alterations in the gamma-aminobutyric acid neurotransmitter system are involved in ET pathophysiology. Here, we systematically review structural, functional, and metabolic neuroimaging studies and discuss current concepts of ET pathophysiology from an imaging perspective.

Methods: We conducted a PubMed and Scopus search from 1966 up to December 2020, entering essential tremor in combination with any of the following search terms and their corresponding abbreviations: positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and gamma-aminobutyric acid (GABA).

Results: Altered functional connectivity in the cerebellum and cerebello-thalamico-cortical circuitry is a prevalent finding in functional imaging studies. Reports from structural imaging studies are less consistent, and there is no clear evidence for cerebellar neurodegeneration. However, diffusion tensor imaging robustly points toward microstructural cerebellar changes. Radiotracer imaging suggests that the dopaminergic axis is largely preserved in ET. Similarly, measurements of nigral iron content and neuromelanin are unremarkable in most studies; this is in contrast to Parkinson's disease (PD). PET and MRS studies provide limited evidence for cerebellar and thalamic GABAergic dysfunction.

Conclusions: There is robust evidence indicating that the cerebellum plays a key role within a multiple oscillator tremor network which underlies tremor genesis. However, whether cerebellar dysfunction relies on a neurodegenerative process remains unclear. Dopaminergic and iron imaging do not suggest a substantial overlap of ET with PD pathophysiology. There is limited evidence for alterations of the GABAergic neurotransmitter system in ET. The clinical, demographical, and genetic heterogeneity of ET translates into neuroimaging and likely explains the various inconsistencies reported.

Voxel-Based Morphometry of Cerebellar Lobules in Essential Tremor

BACKGROUND

The extent of neurodegeneration underlying essential tremor (ET) remains a matter of debate. Despite various extents of cerebellar atrophy on structural magnetic resonance imaging (MRI), previous studies have shown substantial heterogeneity and included a limited number of patients. Novel automated pipelines allow detailed segmentation of cerebellar lobules based on structural MRI.

OBJECTIVE

To compare the volumes of cerebellar lobules in ET patients with those in healthy controls (HCs) using an automated segmentation pipeline.

METHODS

Structural MRI scans of ET patients eligible for deep brain stimulation (n = 55) and of age-matched and gender-matched HCs (n = 55, from the IXI database) were segmented using the automated CEREbellum Segmentation pipeline. Lobule-specific volume differences between the ET and HC groups were evaluated using a general linear model corrected for multiple tests.

RESULTS

Total brain tissue volumes did not differ between the ET and HC groups. ET patients demonstrated reduced volumes of lobules I-II, left Crus II, left VIIB, and an increased volume of right X when compared with the HC group.

CONCLUSION

A large cohort of ET patients demonstrated subtle signs of decreased cerebellar lobule volumes. These findings oppose the hypothesis of localized atrophy in cerebellar motor areas in ET, but not the possibility of cerebellar pathophysiology in ET. Prospective investigations using alternative neuroimaging modalities may further elucidate the pathophysiology of ET and provide insights into diagnostic and therapeutic approaches.

Abnormalities of intrinsic brain activity in essential tremor: A meta-analysis of resting-state functional imaging

Neuroimaging studies using a variety of techniques have demonstrated abnormal patterns of spontaneous brain activity in patients with essential tremor (ET). However, the findings are variable and inconsistent, hindering understanding of underlying neuropathology. We conducted a meta‐analysis of whole‐brain resting‐state functional neuroimaging studies in ET compared to healthy controls (HC), using anisotropic effect‐size seed‐based d mapping, to identify the most consistent brain activity alterations and their relation to clinical features. After systematic literature search, we included 13 studies reporting 14 comparisons, describing 286 ET patients and 254 HC. Subgroup analyses were conducted considering medication status, head tremor status, and methodological factors. Brain activity in ET is altered not only in the cerebellum and cerebral motor cortex, but also in nonmotor cortical regions including prefrontal cortex and insula. Most of the results remained unchanged in subgroup analyses of patients with head tremor, medication‐naive patients, studies with statistical threshold correction, and the large subgroup of studies using functional magnetic resonance imaging. These findings not only show consistent and robust abnormalities in specific brain regions but also provide new information on the biology of patient heterogeneity, and thus help to elucidate the pathophysiology of ET.

Patterns of intrinsic brain activity in essential tremor with resting tremor and tremor-dominant Parkinson's disease

The clinical pictures of essential tremor (ET) with resting tremor (rET) and tremor-dominant Parkinson's disease (tPD) are often quite mimic at the early stage, current approaches to the diagnosis and treatment therefore remain challenging. The regional homogeneity (ReHo) method under resting-state functional magnetic resonance imaging (rs-fMRI) would help exhibit the patterns in neural activity, which further contribute to differentiate these disorders and explore the relationship between symptoms and regional functional abnormalities. Sixty-eight Chinese participants were recruited, including 19 rET patients, 24 tPD patients and 25 age- and gender-matched healthy controls (HCs). All participants underwent clinical assessment and rs-fMRI with a ReHo method to investigate the alterations of neural activity, and the correlation between them. Differences were compared by two-sample t-test (corrected with AlphaSim, p < 0.05). Compared with HCs, patients' groups both displayed decreased ReHo in the default mode network (DMN), bilateral putamen and bilateral cerebellum. While tPD patients specifically exihibited decreased ReHo in the bilateral supplementary motor area (SMA) and precentral gyrus (M1). The correlation analysis revealed that ReHo in the bilateral putamen, right SMA and left cerebellum_crus I were negatively correlated with the UPDRS-III score, respectively, in tPD group. Our results indicated the rET patients may share part of the pathophysiological mechanism of tPD patients. In addition, we found disorder-specific involvement of the SMA and M1 in tPD. Such a distinction may lend itself to use as a potential biomarker for differentiating between these two diseases.

A Voxel-Wise Meta-Analysis on the Cerebellum in Essential Tremor

Background and Objectives: Essential tremor is a chronic progressive neurological condition. The clinical presentation of essential tremor is heterogeneous and includes involuntary tremor on hands or arms and progressively on head, jaw, and voice. More extensive and complex symptoms may also be noticed in several patients. Many studies have been carried out to identify biomarkers to help the diagnosis, however, all the efforts have not shown any substantial results yet. Materials and Methods: Here, we aimed to perform a voxel-based meta-analysis using a dedicated cerebellar mask to clarify whether the results from the previous studies are robust and have any clinical significance. We included studies with a total of 377 essential tremor patients and 338 healthy control individuals. Results: A significant regional decrease in the volume of the gray matter was detected in the right cerebellar hemispheric lobule IV/V, and in the cerebellar vermic lobule IV/V. Conclusions: This is the first study focused on the cerebellum and using a specific cerebellar mask, which increases the sensitivity. It showed regional statistically significant changes that could not be seen in the whole-brain analysis.

Disrupted Brain Network Topology in Drug-naïve Essential Tremor Patients with and Without Depression : A Resting State Functional Magnetic Resonance Imaging Study

PURPOSE

This study was carried out to investigate brain functional connectome and its potential relationships with the disease severity and emotion function in patients with essential tremor with and without depressive symptoms by using resting-state functional magnetic resonance imaging and graph theory approaches.

METHODS

In this study 33 essential tremor patients with depression, 45 essential tremor patients without depression and 79 age and gender-matched healthy controls were recruited to undergo a 3.0‑T imaging scan. The whole brain functional connectome was constructed by thresholding the partial correlation matrices of 116 brain regions, and the topologic properties were analyzed by using graph theory approaches and network-based statistic approaches. Nonparametric permutation test was also used for group comparisons of topological metrics. Correlation analyses between topographic features and the clinical characteristics were performed.

RESULTS

The functional connectome in both essential tremor patients with and without depression showed abnormalities at the global level (decrease in clustering coefficient, global efficiency, and local efficiency but increase in characteristic path length) and at the nodal level (decrease nodal centralities in the cerebellum, motor cortex, prefrontal-limbic regions, default mode network) (p < 0.05, false discovery rate corrected). Moreover, essential tremor patients with depression showed higher node efficiency in superior frontal gyrus and posterior cingulate gyrus compared to essential tremor without depression.

CONCLUSION

Our results may provide insights into the underlying pathophysiology of essential tremor patients with and without depression and aid the development of some potential biomarkers of the depressive symptoms in patients with essential tremor.

Altered local and matrix functional connectivity in depressed essential tremor patients

BACKGROUND

Depression in essential tremor (ET) has been constantly studied and reported, while the associated brain activity changes remain unclear. Recently, regional homogeneity (ReHo), a voxel-wise local functional connectivity (FC) analysis of resting-state functional magnetic resonance imaging, has provided a promising way to observe spontaneous brain activity.

METHODS

Local FC analyses were performed in forty-one depressed ET patients, 49 non-depressed ET patients and 43 healthy controls (HCs), and then matrix FC and clinical depression severity correlation analyses were further performed to reveal spontaneous neural activity changes in depressed ET patients.

RESULTS

Compared with the non-depressed ET patients, the depressed ET patients showed decreased ReHo in the bilateral cerebellum lobules IX, and increased ReHo in the bilateral anterior cingulate cortices and middle prefrontal cortices. Twenty-five significant changes of ReHo clusters were observed in the depressed ET patients compared with the HCs, and matrix FC analysis further revealed that inter-ROI FC differences were also observed in the frontal-cerebellar-anterior cingulate cortex pathway. Correlation analyses showed that clinical depression severity was positively correlated with the inter-ROI FC values between the anterior cingulate cortex and bilateral middle prefrontal cortices and was negatively correlated with the inter-ROI FC values of the anterior cingulate cortex and bilateral cerebellum lobules IX.

CONCLUSION

Our findings revealed local and inter-ROI FC differences in frontal-cerebellar-anterior cingulate cortex circuits in depressed ET patients, and among these regions, the cerebellum lobules IX, middle prefrontal cortices and anterior cingulate cortices could function as pathogenic structures underlying depression in ET patients.

Voxel-based morphometry and task functional magnetic resonance imaging in essential tremor: evidence for a disrupted brain network

The pathophysiology of essential tremor (ET) is controversial and might be further elucidated by advanced neuroimaging. Focusing on homogenous ET patients diagnosed according to the 2018 consensus criteria, this study aimed to: (1) investigate whether task functional MRI (fMRI) can identify networks of activated and deactivated brain areas, (2) characterize morphometric and functional modulations, relative to healthy controls (HC). Ten ET patients and ten HC underwent fMRI while performing two motor tasks with their upper limb: (1) maintaining a posture (both groups); (2) simulating tremor (HC only). Activations/deactivations were obtained from General Linear Model and compared across groups/tasks. Voxel-based morphometry and linear regressions between clinical and fMRI data were also performed. Few cerebellar clusters of gray matter loss were found in ET. Conversely, widespread fMRI alterations were shown. Tremor in ET (task 1) was associated with extensive deactivations mainly involving the cerebellum, sensory-motor cortex, and basal ganglia compared to both tasks in HC, and was negatively correlated with clinical tremor scales. Homogeneous ET patients demonstrated deactivation patterns during tasks triggering tremor, encompassing a network of cortical and subcortical regions. Our results point towards a marked cerebellar involvement in ET pathophysiology and the presence of an impaired cerebello-thalamo-cortical tremor network.

Essential tremor: the most common form of cerebellar degeneration?

Background

The degenerative cerebellar ataxias comprise a large and heterogeneous group of neurological diseases whose hallmark clinical feature is ataxia, and which are accompanied, to variable degrees, by other features that are attributable to cerebellar dysfunction. Essential tremor (ET) is an exceptionally common neurological disease whose primary motor feature is action tremor, although patients often manifest intention tremor, mild gait ataxia and several other features of cerebellar dysfunction.

Main Body

In this paper, we review the abundant evidence derived from clinical, neuroimaging and postmortem studies, linking ET to cerebellar dysfunction. Furthermore, we review the combination of clinical, natural history and postmortem features suggesting that ET is neurodegenerative. We then compare the prevalence of ET (400 – 900 cases per 100,000) to that of the other cerebellar degenerations (ranging from <0.5 – 9 cases per 100,000, and in composite likely to be on the order of 20 cases per 100,000) and conclude that ET is 20 to 45 times more prevalent than all other forms of cerebellar degeneration combined.

Conclusion

Given the data we present, it is logical to conclude that ET is, by far, the most common form of cerebellar degeneration.

Altered spontaneous brain activity in essential tremor with and without resting tremor: a resting-state fMRI study

OBJECTIVES

Essential tremor with resting tremor (rET) often exhibits severer clinical features and more extensive functional impairment than essential tremor without resting tremor (ETwr). However, the pathophysiology of rET is still unclear. This study aims to use resting-state functional magnetic resonance imaging (rs-fMRI) to explore the alterations of brain activity between the drug-naïve patients of rET and ETwr.

METHODS

We recruited 19 patients with rET, 31 patients with ETwr and 25 healthy controls (HCs) to undergo a 3.0-T rs-fMRI examination. The differences of regional brain spontaneous activity between the rET, ETwr and HCs, as well as between total ET (rET + ETwr) and HCs were measured by amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF). The relationships between the altered brain measurements and the clinical scores were analyzed.

RESULTS

Compared with HCs, both ET subgroups showed significantly decreased ALFF or fALFF values in the basal ganglia, inferior orbitofrontal gyrus and insula. The rET group specifically showed decreased ALFF values in the hippocampus and motor cortices, while the ETwr group specifically evidenced increased ALFF and fALFF values in the cerebellum.

DISCUSSION

Regional spontaneous activity in rET and ETwr share common changes and have differences, which may suggest that the functional activities in the limbic system and cerebellum are different between the two subtypes. Improved insights into rET and ETwr subtypes and the different brain spontaneous activity will be valuable for improving our understanding of the pathophysiology of the disease.

Quantitative Separation of Tremor and Ataxia in Essential Tremor

OBJECTIVE

This study addresses an important problem in neurology, distinguishing tremor and ataxia using quantitative methods. Specifically, we aimed to quantitatively separate dysmetria, a cardinal sign of ataxia, from tremor in essential tremor (ET).

METHODS

In Experiment 1, we compared 19 participants diagnosed with ET undergoing thalamic deep brain stimulation (DBS; ET_DBS ) to 19 healthy controls (HC). We quantified tremor during postural tasks using accelerometry and dysmetria with fast, reverse-at-target goal-directed movements. To ensure that endpoint accuracy was unaffected by tremor, we quantified dysmetria in selected trials manifesting a smooth trajectory to the endpoint. Finally, we manipulated tremor amplitude by switching DBS ON and OFF to examine its effect on dysmetria. In Experiment 2, we compared 10 ET participants with 10 HC to determine whether we could identify and distinguish dysmetria from tremor in non-DBS ET.

RESULTS

Three findings suggest that we can quantify dysmetria independently of tremor in ET. First, ET_DBS and ET exhibited greater dysmetria than HC and dysmetria did not correlate with tremor (R²  < 0.01). Second, even for trials with tremor-free trajectories to the target, ET exhibited greater dysmetria than HC (p < 0.01). Third, activating DBS reduced tremor (p < 0.01) but had no effect on dysmetria (p > 0.2).

INTERPRETATION

We demonstrate that dysmetria can be quantified independently of tremor using fast, reverse-at-target goal-directed movements. These results have important implications for the understanding of ET and other cerebellar and tremor disorders. Future research should examine the neurophysiological mechanisms underlying each symptom and characterize their independent contribution to disability. ANN NEUROL 2020;88:375-387.

Connectivity profile of thalamic deep brain stimulation to effectively treat essential tremor

Essential tremor is the most prevalent movement disorder and is often refractory to medical treatment. Deep brain stimulation offers a therapeutic approach that can efficiently control tremor symptoms. Several deep brain stimulation targets (ventral intermediate nucleus, zona incerta, posterior subthalamic area) have been discussed for tremor treatment. Effective deep brain stimulation therapy for tremor critically involves optimal targeting to modulate the tremor network. This could potentially become more robust and precise by using state-of-the-art brain connectivity measurements. In the current study, we used two normative brain connectomes (structural and functional) to show the pattern of effective deep brain stimulation electrode connectivity in 36 patients with essential tremor. Our structural and functional connectivity models were significantly predictive of postoperative tremor improvement in out-of-sample data (P < 0.001 for both structural and functional leave-one-out cross-validation). Additionally, we segregated the somatotopic brain network based on head and hand tremor scores. These resulted in segregations that mapped onto the well-known somatotopic maps of both motor cortex and cerebellum. Crucially, this shows that slightly distinct networks need to be modulated to ameliorate head versus hand tremor and that those networks could be identified based on somatotopic zones in motor cortex and cerebellum. Finally, we propose a multi-modal connectomic deep brain stimulation sweet spot that may serve as a reference to enhance clinical care, in the future. This spot resided in the posterior subthalamic area, encroaching on the inferior borders of ventral intermediate nucleus and sensory thalamus. Our results underscore the importance of integrating brain connectivity in optimizing deep brain stimulation targeting for essential tremor.

Individual Resting-State Brain Networks Enabled by Massive Multivariate Conditional Mutual Information

Individual-level resting-state networks (RSNs) based on resting-state fMRI (rs-fMRI) are of great interest due to evidence that network dysfunction may underlie some diseases. Most current rs-fMRI analyses use linear correlation. Since correlation is a bivariate measure of association, it discards most of the information contained in the spatial variation of the thousands of hemodynamic signals within the voxels in a given brain region. Subject-specific functional RSNs using typical rs-fMRI data, are therefore dominated by indirect connections and loss of spatial information and can only deliver reliable connectivity after group averaging. While bivariate partial correlation can rule out indirect connections, it results in connectivity that is too sparse due to lack of sensitivity. We have developed a method that uses all the spatial variation information in a given parcel by employing a multivariate information-theoretic association measure based on canonical correlations. Our method, multivariate conditional mutual information (mvCMI) reliably constructs single-subject connectivity estimates showing mostly direct connections. Averaging across subjects is not needed. The method is applied to Human Connectome Project data and compared to diffusion MRI. The results are far superior to those obtained by correlation and partial correlation.

Network-level connectivity is a critical feature distinguishing dystonic tremor and essential tremor

Dystonia is a movement disorder characterized by involuntary muscle co-contractions that give rise to disabling movements and postures. A recent expert consensus labelled the incidence of tremor as a core feature of dystonia that can affect body regions both symptomatic and asymptomatic to dystonic features. We are only beginning to understand the neural network-level signatures that relate to clinical features of dystonic tremor. At the same time, clinical features of dystonic tremor can resemble that of essential tremor and present a diagnostic confound for clinicians. Here, we examined network-level functional activation and connectivity in patients with dystonic tremor and essential tremor. The dystonic tremor group included primarily cervical dystonia patients with dystonic head tremor and the majority had additional upper-limb tremor. The experimental paradigm included a precision grip-force task wherein online visual feedback related to force was manipulated across high and low spatial feedback levels. Prior work using this paradigm in essential tremor patients produced exacerbation of grip-force tremor and associated changes in functional activation. As such, we directly compared the effect of visual feedback on grip-force tremor and associated functional network-level activation and connectivity between dystonic tremor and essential tremor patient cohorts to better understand disease-specific mechanisms. Increased visual feedback similarly exacerbated force tremor during the grip-force task in dystonic tremor and essential tremor cohorts. Patients with dystonic tremor and essential tremor were characterized by distinct functional activation abnormalities in cortical regions but not in the cerebellum. We examined seed-based functional connectivity from the sensorimotor cortex, globus pallidus internus, ventral intermediate thalamic nucleus, and dentate nucleus, and observed abnormal functional connectivity networks in dystonic tremor and essential tremor groups relative to controls. However, the effects were far more widespread in the dystonic tremor group as changes in functional connectivity were revealed across cortical, subcortical, and cerebellar regions independent of the seed location. A unique pattern for dystonic tremor included widespread reductions in functional connectivity compared to essential tremor within higher-level cortical, basal ganglia, and cerebellar regions. Importantly, a receiver operating characteristic determined that functional connectivity z-scores were able to classify dystonic tremor and essential tremor with 89% area under the curve, whereas combining functional connectivity with force tremor yielded 94%. These findings point to network-level connectivity as an important feature that differs substantially between dystonic tremor and essential tremor and should be further explored in implementing appropriate diagnostic and therapeutic strategies.

Functional disconnection of the dentate nucleus in essential tremor

Despite previous functional MRI studies on alterations within the cerebello-thalamo-cortical circuit in patients with essential tremor (ET), the specific role of disconnection of the dentate nucleus (DN), the main output cerebellar pathway, still needs clarification. In this study, we evaluated DN functional connectivity (FC) changes and their relationship with motor and non-motor symptoms in ET. We studied 25 ET patients and 26 healthy controls. Tremor severity was assessed using the Fahn-Tolosa-Marin tremor rating scale (FTM-TRS) and tremor amplitude and frequency were evaluated using kinematic techniques. Cognitive profile was assessed by montreal cognitive assessment (MoCA) and frontal assessment battery (FAB). All participants underwent a 3 T MRI protocol including resting-state blood oxygenation level dependent and diffusion tensor sequences. We used a seed-based approach to investigate DN FC and to explore the diffusion properties of cerebellar peduncles. There was significantly decreased DN FC with cortical, subcortical, and cerebellar areas in ET patients compared with healthy controls. Correlation analysis showed that: (1) the DN FC with the supplementary motor area, pre and postcentral gyri, and prefrontal cortex negatively correlated with FTM-TRS score and disease duration; (2) DN FC changes in the thalamus and caudate negatively correlated with peak tremor frequency, changes in the cerebellum positively correlated with tremor amplitude, and changes in the bilateral thalamus negatively correlated with tremor amplitude, and (3) DN FC with the associative prefrontal and parietal cortices, basal ganglia, and thalamus positively correlated with the MoCA score. Diffusion abnormalities were found in the three cerebellar peduncles, which did not correlate with clinical scores.

A widespread visually-sensitive functional network relates to symptoms in essential tremor

Essential tremor is a neurological syndrome of heterogeneous pathology and aetiology that is characterized by tremor primarily in the upper extremities. This tremor is commonly hypothesized to be driven by a single or multiple neural oscillator(s) within the cerebello-thalamo-cortical pathway. Several studies have found an association of blood-oxygen level-dependent (BOLD) signal in the cerebello-thalamo-cortical pathway with essential tremor, but there is behavioural evidence that also points to the possibility that the severity of tremor could be influenced by visual feedback. Here, we directly manipulated visual feedback during a functional MRI grip force task in patients with essential tremor and control participants, and hypothesized that an increase in visual feedback would exacerbate tremor in the 4-12 Hz range in essential tremor patients. Further, we hypothesized that this exacerbation of tremor would be associated with dysfunctional changes in BOLD signal and entropy within, and beyond, the cerebello-thalamo-cortical pathway. We found that increases in visual feedback increased tremor in the 4-12 Hz range in essential tremor patients, and this increase in tremor was associated with abnormal changes in BOLD amplitude and entropy in regions within the cerebello-thalamo-motor cortical pathway, and extended to visual and parietal areas. To determine if the tremor severity was associated with single or multiple brain region(s), we conducted a birectional stepwise multiple regression analysis, and found that a widespread functional network extending beyond the cerebello-thalamo-motor cortical pathway was associated with changes in tremor severity measured during the imaging protocol. Further, this same network was associated with clinical tremor severity measured with the Fahn, Tolosa, Marin Tremor Rating Scale, suggesting this network is clinically relevant. Since increased visual feedback also reduced force error, this network was evaluated in relation to force error but the model was not significant, indicating it is associated with force tremor but not force error. This study therefore provides new evidence that a widespread functional network is associated with the severity of tremor in patients with essential tremor measured simultaneously at the hand during functional imaging, and is also associated with the clinical severity of tremor. These findings support the idea that the severity of tremor is exacerbated by increased visual feedback, suggesting that designers of new computing technologies should consider using lower visual feedback levels to reduce tremor in essential tremor.

No reliable gray matter changes in essential tremor

BACKGROUND

Voxel-based morphometry (VBM) has been used to study human brain gray matter (GM) alterations in essential tremor (ET) for over one decade. However, the literature revealed heterogeneous findings.

METHODS

We therefore conducted a coordinate-based meta-analysis to synthesize the VBM studies to examine which brain regions show the most reliable GM alterations in patients with ET relative to healthy controls.

RESULTS

A total of 16 original VBM studies, comprising 387 patients with ET and 355 healthy controls, were included in this meta-analysis. This quantitative meta-analysis revealed no evidence of robust and reliable alterations in regional brain GM structures in ET. Meta-regression analyses indicate that many moderators (e.g., MR field strength, statistical methodology, age, onset age, gender, illness severity, illness duration, and family history) account for some of the heterogeneity in GM across studies.

CONCLUSIONS

High heterogeneity in GM alterations across studies may reflect true heterogeneity in ET regarding the clinic, etiology, and pathology, as well as possibly the VBM methodological variations. Currently, this heterogeneity limits the use of VBM as a reliable tool to distinguish ET from healthy controls. In order to improve reproducibility of VBM results in ET, future research may benefit from increasing the sample size, comprehensively subtyping ET phenotypes, and using well-designed and standardized imaging acquisition and analytical protocols. Furthermore, data sharing should be considered as a high priority.

Hybrid PET-MRI Applications in Movement Disorders

Even before the success of combined positron emission tomography and computed tomography (PET/CT), the neuroimaging community was conceiving the idea to integrate the positron emission tomography (PET), with very high molecular quantitative data but low spatial resolution, and magnetic resonance imaging (MRI), with high spatial resolution. Several technical limitations have delayed the use of a hybrid scanner in neuroimaging studies, including the full integration of the PET detector ring within the MRI system, the optimization of data acquisition, and the implementation of reliable methods for PET attenuation, motion correction, and joint image reconstruction. To be valid and useful in clinical and research settings, this instrument should be able to simultaneously acquire PET and MRI, and generate quantitative parametric PET images comparable to PET-CT. While post hoc co-registration of combined PET and MRI data acquired separately became the most reliable technique for the generation of "fused" PET-MRI images, only hybrid PET-MRI approach allows merging these measurements naturally and correlating them in a temporal manner. Furthermore, hybrid PET-MRI represents the most accurate tool to investigate in vivo the interplay between molecular and functional aspects of brain pathophysiology. Hybrid PET-MRI technology is still in the early stages in the movement disorders field, due to the limited availability of scanners with integrated optimized methodological models. This technology is ideally suited to investigate interactions between resting-state functional/arterial spin labeling MRI and [¹⁸F]FDG PET glucose metabolism in the evaluation of the brain "hubs" particularly vulnerable to neurodegeneration, areas with a high degree of connectivity and associated with an efficient synaptic neurotransmission. In Parkinson's disease, hybrid PET-MRI is also the ideal instrument to deeper explore the relationship between resting-state functional MRI and dopamine release at [¹¹C]raclopride PET challenge, in the identification of early drug-naïve Parkinson's disease patients at higher risk of motor complications and in the evaluation of the efficacy of novel neuroprotective treatment able to restore at the same time the altered resting state and the release of dopamine. In this chapter, we discuss the key methodological aspects of hybrid PET-MRI; the evidence in movement disorders of the key resting-state functional and perfusion MRI; [¹⁸F]FDG PET and [¹¹C]raclopride PET challenge studies; the potential advantages of using hybrid PET-MRI to investigate the pathophysiology of movement disorders and neurodegenerative diseases. Future directions of hybrid PET-MRI will be discussed alongside with up-to-date technological innovations on hybrid systems.

Resting-state fMRI study on drug-naive patients of essential tremor with and without head tremor

This study used resting-state functional MRI (r-fMRI) to evaluate intrinsic brain activity in drug-naive patients with essential tremor (ET) with and without head tremor. We enrolled 20 patients with ET with hand and head tremor (h-ET), 27 patients with ET without head tremor (a-ET), and 27 healthy controls (HCs). All participants underwent r-fMRI scans on a 3-T MR system. The amplitude of low-frequency fluctuation (ALFF) of blood oxygen level-dependent signals was used to characterize regional cerebral function. We identified increased ALFF value in the bilateral posterior lobe of cerebellum in the h-ET patients relative to a-ET and HCs and demonstrated that h-ET is related to abnormalities in the cerebello-cortical areas, while the a-ET is related to abnormalities in the thalamo-cortical areas. In addition, we observed the ALFF abnormality in the cerebellum (left cerebellum VIII and right cerebellum VI) correlated with the tremor score in h-ET patients and abnormal ALFF in the left precentral gyrus correlated with the age at onset and disease duration in h-ET patients. These findings may be helpful for facilitating further understanding of the potential mechanisms underlying different subtypes of ET.

Resting state fMRI reveals the altered synchronization of BOLD signals in essential tremor

Essential tremor (ET) is one of the most common movement disorders in humans. Nevertheless, there remain several controversies surrounding ET, such as whether it is a disorder of abnormal neuronal oscillations within the tremor network. In this work, the resting-state fMRI data were collected from 17 ET patients and 17 age- and gender-matched healthy controls. First, using FOur-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA) the abnormal synchronization of fMRI signals in ET patients were investigated. Then, global functional connectivity intensity (gFCI) and density (gFCD) were analyzed in the regions exhibiting significant FOCA differences. Compared with healthy controls, patients with ET showed the increased FOCA values found in the bilateral cuneus, the left lingual gyrus, the left paracentral lobule, the right middle temporal gyrus, the bilateral precentral gyrus, the right postcentral gyrus, the pallidum and putamen. Decreased FOCA values in ET patients were located in the frontal gyrus, the bilateral anterior cingulate and the medial dorsal nucleus of right thalamus. In ET patients, significant changes in gFCI and gFCD were located in the cuneus, the middle temporal gyrus and the middle frontal gyrus. Changes in gFCI were also found in the medial frontal gyrus and thalamus in addition to changes in gFCD in the precentral gyrus. Our results provided further evidence that ET might present with abnormal spontaneous activity in the tremor network, including motor-related cotex, basal ganglia and thalamus, as well as distributed non-motor areas. This work also demonstrated that FOCA and functional connectivity have the potential to provide important insight into the pathophysiological mechanism of ET.

A Voxel-Based Magnetic Resonance Imaging Morphometric Study of Cerebral and Cerebellar Gray Matter in Patients Under 65 Years with Essential Tremor

BACKGROUND The aim of this study was to compare the morphological changes in cerebral and cerebellar gray matter in patients with essential tremor under 60-years-of-age, with age-matched and gender-matched normal healthy volunteer control subjects, using functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM) analysis. MATERIAL AND METHODS A retrospective, controlled, comparative clinical study included 17 patients with essential tremor, <60 years-of-age, and 17 age-matched and gender-matched healthy volunteer control subjects, recruited between June 2010-July 2012. MRI and VBM analysis were used to compare cerebral and cerebellar gray matter density between groups. The Washington Heights-Inwood Genetic Study of Essential Tremor (WHIGET) rating scale was used to assess tremor severity in the patient group. Clinical and demographic characteristics were recorded for all study participants. RESULTS MRI and VBM analysis showed significant bilateral expansion of the cerebellum, occipital fusiform cortices, right inferior temporal gyrus, and precentral lobes in patients with essential tremor (P<0.005); reduction in gray matter was found in the left parietal lobe. The region of interest (ROI) analysis showed volume enlargement in the thalamus, midbrain, and the precuneus (P<0.005). No significant correlation between changes in gray matter and changes in clinical variables, including age, gender, tremor duration, the activity of daily living (ADL) scale, the mini-mental state examination (MMSE) scale, family history, and tremor severity were found. CONCLUSIONS Predominantly cerebellar gray matter expansion in patients less than 60 years-of-age with essential tremor might be the result of compensation for the decline in cerebellar function.

Clinical response to Vim's thalamic stereotactic radiosurgery for essential tremor is associated with distinctive functional connectivity patterns

INTRODUCTION

Essential tremor (ET) is the most common movement disorder. Drug-resistant ET can benefit from standard surgical stereotactic procedures (deep brain stimulation, thalamotomy) or minimally invasive high-intensity focused ultrasound (HIFU) or stereotactic radiosurgical thalamotomy (SRS-T). Resting-state fMRI (rs-fMRI) is a non-invasive imaging method acquired in absence of a task. We examined whether rs-fMRI correlates with tremor score on the treated hand (TSTH) improvement 1 year after SRS-T.

METHODS

We included 17 consecutive patients treated with left unilateral SRS-T in Marseille, France. Tremor score evaluation and rs-fMRI were acquired at baseline and 1 year after SRS-T. Resting-state data (34 scans) were analyzed without a priori hypothesis, in Lausanne, Switzerland. Based on degree of improvement in TSTH, to consider SRS-T at least as effective as medication, we separated two groups: 1, ≤ 50% (n = 6, 35.3%); 2, > 50% (n = 11, 64.7%). They did not differ statistically by age (p = 0.86), duration of symptoms (p = 0.41), or lesion volume at 1 year (p = 0.06).

RESULTS

We report TSTH improvement correlated with interconnectivity strength between salience network with the left claustrum and putamen, as well as between bilateral motor cortices, frontal eye fields and left cerebellum lobule VI with right visual association area (the former also with lesion volume). Longitudinal changes showed additional associations in interconnectivity strength between right dorsal attention network with ventro-lateral prefrontal cortex and a reminiscent salience network with fusiform gyrus.

CONCLUSIONS

Brain connectivity measured by resting-state fMRI relates to clinical response after SRS-T. Relevant networks are visual, motor, and attention. Interconnectivity between visual and motor areas is a novel finding, revealing implication in movement sensory guidance.