The role of the inferior parietal lobule in writer's cramp

Motor network reorganization associated with rTMS-induced writing improvement in writer's cramp dystonia

Background

Writer's cramp (WC) dystonia is an involuntary movement disorder with distributed abnormalities in the brain's motor network. Prior studies established the potential for repetitive transcranial magnetic stimulation (rTMS) to either premotor cortex (PMC) or primary somatosensory cortex (PSC) to modify symptoms. However, clinical effects have been modest with limited understanding of the neural mechanisms hindering therapeutic advancement of this promising approach.

Objective

This study aimed to understand the motor network effects of rTMS in WC that correspond with behavioral efficacy. We hypothesized that behavioral efficacy is associated with modulation of cortical and subcortical regions of the motor network.

Methods

In a double-blind, cross-over design, twelve WC participants underwent rTMS in one of three conditions (Sham-TMS, 10 Hz PSC-rTMS, 10 Hz PMC-rTMS) while engaged in a writing task to activate dystonic movements and measure writing fluency. Brain connectivity was evaluated using task-based fMRI after each TMS session.

Results

10 Hz rTMS to PSC, but not PMC, significantly improved writing dysfluency. PSC-TMS also significantly weakened cortico-basal ganglia, cortico-cerebellum, and intra-cerebellum functional connectivity (FC), and strengthened striatal FC relative to Sham. Changes in PSC and SPC BOLD activity were associated with reduced dysfluent writing behavior.

Conclusions

10 Hz rTMS to PSC improved writing dysfluency by redistributing motor network connectivity and strengthening somatosensory-parietal connectivity. A key signature for effective stimulation at PSC and improvement in writing dysfluency may be strengthening of intra-cortical connectivity between primary somatosensory and superior parietal cortices. These findings offer mechanistic hypotheses to advance the therapeutic application of TMS for dystonia.

Highlights

10 Hz repetitive TMS to somatosensory cortex reduces writing dysfluency in dystoniaIncreased somatosensory cortex activity correlates with reduced writing dysfluencyIn dystonia + sham-TMS, writing dysfluency correlates with cerebellar connectivity.10 Hz rTMS to somatosensory cortex induces reorganization of the motor network.

Long-term motor learning in focal hand dystonia

OBJECTIVE

Because focal hand dystonia usually occurs in the over-learned stage, it would be valuable to know long-term motor learning characteristics and underlying pathophysiological features that might predispose to dystonia.

METHODS

We conducted a case-control exploratory study of 15 visits over 12 weeks in the non-affected hand of a 4-finger sequence of 8 key presses in eight patients with FHD compared with eight age- and sex-matched, healthy volunteers (HVs). We studied the behavioral data and the physiological changes of the brain, including motor cortical excitability and cortical oscillations.

RESULTS

There was no significant difference in the time to reach 100 % accuracy between FHD and HV during the 80-day follow-up period. There was a statistically significant difference in the accuracy of sequential finger movement tasks between patients with FHD compared with HVs over 12 weeks, but post-hoc analysis with multiple comparion correction did not show difference. There were no significant differences in recruitment curve changes and task-related power changes of alpha and beta bands.

CONCLUSION

Over 12 weeks, FHD have motor learning capacity comparable to HVs and do not show pathophysiological abnormalities.

SIGNIFICANCE

Further studies would be valuable with more patients, more extended periods of practice, and more detailed electrophysiological explorations.

The left primary motor cortex and cerebellar vermis are critical hubs in bimanual sequential learning

We conducted an fMRI study to investigate the neural basis of bimanual coordination, which is fundamental to upper extremity control. Considering bimanual movement as a combination of bimanual chord formation and sequence control, we hypothesized that the areas with the learning effect of both chord formation and sequence learning are critical in bimanual coordination. We adopted the serial reaction time task (SRTT) to test this hypothesis. Thirty-five healthy right-handed volunteers practiced visually cued bimanual SRTT, including the "mirror" and more complex "parallel" modes of random movements or repeating fixed sequences to separately depict the neural substrates of bimanual posture control for chord formation and those of sequence. Random movements' reaction time (RT) continuously declined, indicating learning of bimanual chord formation. The RT in the sequential condition declined more rapidly than in the random condition, confirming sequence learning. The parallel random conditions evoked a more prominent learning-related decrease of task-related activation in the left M1 and cerebellar vermis than the less difficult mirror random conditions. The left M1 showed learning-related enhancement of functional connectivity with the anterior cingulate cortex during the parallel random conditions compared with the mirror random conditions. Thus, the left M1, anterior cingulate cortex, and cerebellar vermis are related to learning bimanual chord formation. The left M1 and cerebellar vermis also showed sequence-specific learning-related activity increments more prominent in the parallel mode than in the mirror mode. Thus, the left M1 and cerebellar vermis are critical in the bimanual motor learning network.

Zolpidem improves task-specific dystonia: A randomized clinical trial integrating exploratory transcranial magnetic stimulation and [18F] FDG-PET imaging

BACKGROUND

Task-specific dystonia (TSFD) is a disabling movement disorder. Effective treatment options are currently limited. Zolpidem was reported to improve primary focal and generalized dystonia in a proportion of patients. The mechanisms underlying its therapeutic effects have not yet been investigated.

METHODS

We conducted a randomized, double-blind, placebo-controlled, crossover trial of single-dose zolpidem in 24 patients with TSFD. Patients were clinically assessed using Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS), Writers' Cramp Rating Scale (WCRS), and Visual Analogue Scale (VAS), before and after receiving placebo and zolpidem. Transcranial magnetic stimulation was conducted on placebo and zolpidem to compare corticospinal excitability - active and resting motor thresholds (AMT and RMT), resting and active input/output curves and intracortical excitability - cortical silent period (CSP), short-interval intracortical inhibition curve (SICI), long-interval intracortical inhibition (LICI) and intracortical facilitation (ICF). Eight patients underwent brain FDG-PET imaging on zolpidem and placebo.

RESULTS

Zolpidem treatment improved TSFD. Zolpidem compared to placebo flattened rest and active input/output curves, reduced ICF and was associated with hypometabolism in the right cerebellum and hypermetabolism in the left inferior parietal lobule and left cingulum. Correlations were found between changes in dystonia severity on WCRS and changes in active input/output curve and in brain metabolism, respectively. Patients with lower RMT, and higher rest and active input/output curves exhibited better response to zolpidem compared to placebo.

CONCLUSIONS

Zolpidem improved TSFD by reducing corticomotor output and influencing crucial nodes in higher-order sensory and motor networks.

Basis of movement control in dystonia and why botulinum toxin should influence it?

Dystonia is a network disorder involving multiple brain regions, such as the motor cortex, sensory cortex, basal ganglia, and cerebellum. Botulinum toxin (BoNT) is the first-line therapy for treating focal dystonia and is a potent molecule that blocks the release of acetylcholine at the peripheral neuromuscular junction. However, the clinical benefits of BoNT are not solely related to peripheral muscle relaxation or modulation of afferent input from the muscle spindle. An increasing body of evidence, albeit in smaller cohorts, has shown that BoNT leads to distant modulation of the pathological brain substrates implicated in dystonia. A single treatment session of BoNT has been observed to reduce excessive motor excitability and improve sensory processing. Furthermore, owing to plasticity effects that are induced by botulinum, neural reorganization of pathological networks occurs, presumably leading to defective motor programs of dystonia replaced with normal movement patterns. However, longitudinal studies investigating the effects of multiple treatment sessions in large, well-characterized homogenous cohorts of dystonia will provide further compelling evidence supporting central botulinum mechanisms.

Aberrant spontaneous static and dynamic amplitude of low-frequency fluctuations in cerebral small vessel disease with or without mild cognitive impairment

BACKGROUND

Cerebral small vessel disease (CSVD) is considered an age-related degenerative neurological disorder and the most common risk factor for vascular cognitive impairment (VCI). The amplitude of fluctuation of low frequency (ALFF) can detect altered intrinsic brain activity in CSVD. This study explored the static and dynamic ALFFs in the early stage of CSVD with (CSVD-M) or without (CSVD-W) mild cognitive impairment (MCI) in these patients and how these changes contribute to cognitive deterioration.

METHODS

Thirty consecutive CSVD cases and 18 healthy controls (HC) were included in this study. All the participants underwent a 3D magnetization-prepared rapid gradient-echo (MPRAGE) sequence to obtain structural T1-weighted images. Simultaneous multislice imaging 5(SMS5) was used for resting-state functional MRI (rs-fMRI), and Data Processing and Analysis of Brain Imaging software helped determine static ALFF (sALFF). The dynamic ALFF (dALFF) was calculated using the sliding window method of DynamicBC software. Analysis of Covariance (ANCOVA) and two-sample t-test were used to evaluate the sALFF and temporal variability of dALFF among the three groups. The subjects were rated on a broad standard neuropsychological scale. Partial correlation analysis was used to evaluate the correlation between sALFF and dALFF variability and cognition (Bonferroni correction, statistical threshold set at p < .05).

RESULTS

Compared with HCs, the CSVD-M group indicated decreased sALFF values in the bilateral cerebellum posterior lobe (CPL) and the left inferior Parietal Lobule (IPL), with increased sALFF values in the right SFG. For dALFF analysis, the CSVD-W group had significant dALFF variability in the right fusiform gyrus compared with HC. Moreover, the postcentral gyrus (PoCG) was significantly high in the CSVD-W group. While in the CSVD-M group, the bilateral paracentral lobules (PL) revealed significantly elevated dALFF variability and low dALFF variability in the left CPL and right IPL compared with HCs. The CSVD-M group had high dALFF variability in the bilateral PL but low dALFF variability in the left middle temporal gyrus (MTG) and right PoCG compared with the CSVD-W group. The partial correlation analysis indicated that dALFF variability in the left MTG was positively associated with EM (r = 0.713, p = .002) in CSVD-W and CSVD-M groups. In the groups with CSVD-M and HC, altered dALFF variability in the bilateral PL was negatively correlated with EM (r = -0.560, p = .002).

CONCLUSION

There were significant changes in sALFF and dALFF variability in CSVD patients. Abnormal spontaneous static and dynamic ALFFs may provide new insights into cognitive dysfunction in CSVD with MCI and may be valuable biomarkers for early diagnosis.

Physiology of dystonia: Human studies

In this chapter, we discuss neurophysiological techniques that have been used in the study of dystonia. We examine traditional disease models such as inhibition and excessive plasticity and review the evidence that these play a causal role in pathophysiology. We then review the evidence for sensory and peripheral influences within pathophysiology and look at an emergent literature that tries to probe how oscillatory brain activity may be linked to dystonia pathophysiology.

Fixel-Based Analysis Reveals Whole-Brain White Matter Abnormalities in Cervical Dystonia

BACKGROUND

Cervical dystonia (CD) is a form of isolated focal dystonia typically associated to abnormal head, neck, and shoulder movements and postures. The complexity of the clinical presentation limits the investigation of its pathophysiological mechanisms, and the neural networks associated to specific motor manifestations are still the object of debate.

OBJECTIVES

We investigated the morphometric properties of white matter fibers in CD and explored the networks associated with motor symptoms, while regressing out nonmotor scores.

METHODS

Nineteen patients affected by CD and 21 healthy controls underwent diffusion-weighted magnetic resonance imaging. We performed fixel-based analysis, a novel method evaluating fiber orientation within specific fiber bundles, and compared fiber morphometric properties between groups. Moreover, we correlated fiber morphometry with the severity of motor symptoms in patients.

RESULTS

Compared to controls, patients exhibited decreased white matter fibers in the right striatum. Motor symptom severity negatively correlated with white matter fibers passing through inferior parietal areas and the head representation area of the motor cortex.

CONCLUSIONS

Abnormal white matter integrity at the basal ganglia level may affect several functional networks involved, for instance, in motor preparation and execution, visuomotor coordination, and multimodal integration. This may result in progressive maladaptive plasticity, culminating in overt symptoms of dystonia. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Altered spontaneous brain activity as a potential imaging biomarker for generalized and focal to bilateral tonic-clonic seizures: A resting-state fMRI study

OBJECTIVE

We aimed to determine whether alterations in spontaneous regional brain activity in those with generalized tonic-clonic seizures (GTCS) and focal to bilateral tonic-clonic seizures (FBTCS) and explore whether the alterations could be used as biomarkers to classify disease subtypes through support vector machine analysis (SVM).

METHODS

The fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo) from resting-state functional magnetic resonance imaging (rs-fMRI) data were extracted from 57 patients with GTCS, 35 patients with FBTCS, and 50 age-matched and sex-matched normal controls (NCs) using the DPARSF 5.0 toolbox. Between-group comparisons were adjusted for covariates (age, sex, and equipment). Correlation analyses between imaging biomarkers and the frequency or duration of seizure activity were calculated using partial correlations. The differential imaging indicators, age, and sex were considered as the discriminative features in the SVM to evaluate classification performance.

RESULTS

The patients with GTCS showed lower fALFF values (voxel p < 0.001, cluster p < 0.05, Gaussian random field corrected, GRF corrected) in the right postcentral gyrus and precentral gyrus and lower ReHo values (GRF corrected) in the middle temporal gyrus than the NCs. The patients with FBTCS showed higher fALFF (GRF corrected) values in the right postcentral and precentral gyrus and higher ReHo (GRF corrected) values in the right postcentral gyrus. Both fALFF (GRF corrected) and ReHo (GRF corrected) values were lower in the right postcentral gyrus and precentral gyrus in the GTCS group than in the FBTCS group. In patients with FBTCS, fALFF values in the right postcentral and precentral gyrus were positively correlated with duration (r = 0.655, p = 0.008, Bonferroni corrected) in the low-duration group, and ReHo values in the right postcentral gyrus were positively correlated with frequency (r = 0.486, p = 0.022, uncorrected) in the low-frequency group. SVM results showed receiver operating characteristic curves of 0.89, 0.87, and 0.76 for the classification between GTCS and NC, between FBTCS and NC, and GTCS and FBTCS, respectively.

SIGNIFICANCE

This study detected alterations in fALFF and ReHo in the postcentral gyrus and precentral gyrus in patients with GTCS and FBTCS, which might contribute to understanding the pathogenesis, disease classification, and clinical targeted therapy.

Cortical mechanisms of sensory trick in cervical dystonia

Patients with cervical dystonia (CD) often show an improvement in dystonic posture after sensory trick (ST), though the mechanisms underlying ST remain unclear. In this study, we aimed to investigate the effects of ST on cortical activity in patients with CD and to explore the contribution of motor and sensory components to ST mechanisms. To this purpose, we studied 15 CD patients with clinically effective ST, 17 without ST, and 14 healthy controls (HCs) who mimicked the ST. We used electroencephalographic (EEG) recordings and electromyography (EMG) data from bilateral sternocleidomastoid (SCM) muscles. We compared ST-related EEG spectral changes from sensorimotor and posterior parietal areas and EMG power changes between groups. To better understand the contribution of motor and sensory components to ST, we tested EEG and EMG correlates of three different conditions mimicking ST, the first without skin touch ("no touch" condition), the second without voluntary movements ("passive" condition), and finally without arm movements ("examiner touch" condition). Results showed ST-related alpha desynchronization in the sensorimotor cortex and theta desynchronization in the sensorimotor and posterior parietal cortex. Both spectral changes were more significant during maneuver execution in CD patients with ST than in CD patients without ST and HCs who mimicked the ST. Differently, the "no touch", "passive", or "examiner touch" conditions did not show significant differences in EEG or EMG changes determined by ST execution/mimicking between CD patients with or without ST. A higher desynchronization within alpha and theta bands in the sensorimotor and posterior parietal areas correlated with a more significant activity decrease in the contralateral SCM muscle, Findings from this study suggest that ST-related changes in the activity of sensorimotor and posterior parietal areas may restore dystonic posture and that both motor and sensory components contribute to the ST effect.

Clinical Implications of Dystonia as a Neural Network Disorder

Isolated dystonia is a neurological disorder of diverse etiology, multifactorial pathophysiology, and wide spectrum of clinical presentations. We review the recent neuroimaging advances that led to the conceptualization of dystonia as a neural network disorder and discuss how current knowledge is shaping the identification of biomarkers of dystonia and the development of novel pharmacological therapies.

Role of supplementary motor area in cervical dystonia and sensory tricks

Sensory trick is a characteristic feature of cervical dystonia (CD), where a light touch on the area adjacent to the dystonia temporarily improves symptoms. Clinical benefit from sensory tricks can be observed before tactile contact is made or even by imagination. The supplementary motor area (SMA) may dynamically interact with the sensorimotor network and other brain regions during sensory tricks in patients with CD. In this study, we examined the functional connectivity of the SMA at rest and during sensory trick performance and imagination in CD patients compared to healthy controls using functional magnetic resonance imaging. The functional connectivity between the SMA and left intraparietal sulcus (IPS) region was lower in CD patients at rest and it increased with sensory trick imagination and performance. SMA-right cerebellum connectivity also increased with sensory trick imagination in CD patients, while it decreased in healthy controls. In CD patients, SMA connectivity increased in the brain regions involved in sensorimotor integration during sensory trick performance and imagination. Our study results showed a crucial role of SMA in sensorimotor processing during sensory trick performance and imagination and suggest the IPS as a novel potential therapeutic target for brain modulation.

Structural magnetic resonance imaging in dystonia: A systematic review of methodological approaches and findings

BACKGROUND AND PURPOSE

Structural magnetic resonance techniques have been widely applied in neurological disorders to better understand tissue changes, probing characteristics such as volume, iron deposition and diffusion. Dystonia is a hyperkinetic movement disorder, resulting in abnormal postures and pain. Its pathophysiology is poorly understood, with normal routine clinical imaging in idiopathic forms. More advanced tools provide an opportunity to identify smaller scale structural changes which may underpin pathophysiology. This review aims to provide an overview of methodological approaches undertaken in structural brain imaging of dystonia cohorts, and to identify commonly identified pathways, networks or regions that are implicated in pathogenesis.

METHODS

Structural magnetic resonance imaging studies of idiopathic and genetic forms of dystonia were systematically reviewed. Adhering to strict inclusion and exclusion criteria, PubMed and Embase databases were searched up to January 2022, with studies reviewed for methodological quality and key findings.

RESULTS

Seventy-seven studies were included, involving 1945 participants. The majority of studies employed diffusion tensor imaging (DTI) (n = 45) or volumetric analyses (n = 37), with frequently implicated areas of abnormality in the brainstem, cerebellum, basal ganglia and sensorimotor cortex and their interconnecting white matter pathways. Genotypic and motor phenotypic variation emerged, for example fewer cerebello-thalamic tractography streamlines in genetic forms than idiopathic and higher grey matter volumes in task-specific than non-task-specific dystonias.

DISCUSSION

Work to date suggests microstructural brain changes in those diagnosed with dystonia, although the underlying nature of these changes remains undetermined. Employment of techniques such as multiple diffusion weightings or multi-exponential relaxometry has the potential to enhance understanding of these differences.

Investigation of the posterior parietal cortex to ventral premotor connection in writer's cramp using transcranial magnetic stimulation

The posterior parietal, premotor and motor cortices are brain regions relevant in the planning of movement. Previous transcranial magnetic stimulation (TMS) studies have shown ipsilateral premotor-to-motor inhibition in healthy subjects at rest. This premotor-to-motor inhibition has been found to be altered in patients with writer's cramp (WC), a common type of focal hand dystonia. We aimed to investigate the influence of the posterior parietal cortex on the ipsilateral ventral premotor cortex using a three single-pulse TMS paradigm. Nineteen right-handed subjects (eleven healthy volunteers and eight WC patients) completed the study. A three single-pulse TMS paradigm (preconditioning, conditioning, and test stimuli) was used to sequentially stimulate the left posterior parietal, ventral premotor, and primary motor cortices. We found that in both healthy subjects and patients, stimulating the ipsilateral posterior parietal cortex resulted in reversal of the resting premotor-to-motor inhibition. Resting premotor-to-motor inhibition was also found, with no statistically significant group difference. Furthermore, a facilitatory effect of the posterior parietal cortex on the primary motor cortex was found in both groups. Our results suggest that in the resting state, the inhibitory effect of the left posterior parietal cortex on the ipsilateral ventral premotor cortex found in healthy subjects is also intact in WC patients. While we are unable to identify any parietal-to-premotor connectivity abnormality in the resting state, an abnormality during a specific task cannot be excluded. Previously reported conductivity abnormalities in resting fMRI do not appear to translate into a TMS physiological abnormality.

Diagnostic Neurophysiologic Biomarkers for Task‐Specific Dystonia

Background

Task-specific dystonia (TSD) is a challenging clinical diagnosis with no objective diagnostic biomarkers.

Objective

The objective of this study was to test 2 neurophysiologic variables using transcranial magnetic stimulation as potential diagnostic biomarkers for TSD.

Methods

We tested (1) cortical silent period (CSP) and (2) dorsal inferior parietal lobule-motor cortex (dIPL-M1) physiologic connectivity in 9 patients with the writer's cramp form of TSD and 12 healthy volunteers on 2 separate sessions.

Results

CSP was significantly prolonged (P < 0.0001) in TSD and could classify TSD with high sensitivity and specificity with areas under the receiver operating characteristic curve (AUCs) = 0.94 and 0.90, respectively, for 2 separate sessions with an intraclass correlation = 0.79. dIPL-M1 interaction was notable for significant motor cortical inhibition in TSD compared with facilitation in healthy subjects (P < 0.0001) and could classify TSD with high sensitivity and specificity with AUCs = 0.96 and 0.86, respectively.

Conclusion

CSP and dIPL-M1 physiologic connectivity can classify TSD with high sensitivity, specificity, reproducibility, and reliability.

Tools to explore neuroplasticity in humans: Combining interventional neurophysiology with functional and structural magnetic resonance imaging and spectroscopy

This chapter summarizes how brain imaging can be used in combination with non-invasive transcranial stimulation to probe and induce neuroplasticity in the human brain. We aim to give a conceptual account and highlight exemplary studies. We showcase the scientific and clinical potentials of studies focusing on the combination of transcranial magnetic stimulation (TMS) with Magnetic Resonance Imaging (MRI) or Magnetic Resonance Spectroscopy (MRS). MRI and MRS can be used before brain stimulation to identify target networks and loci but also to inform individual dosing. After a brain stimulation session, MRI and MRS can be used to pinpoint how the stimulation protocol alters brain function, structure, or metabolism and relate these after-effects to behavioral and clinical outcomes. Complementing these "offline" approaches, TMS can also be applied "online" during MRI or MRS to delineate how stimulation acutely engages the stimulated brain regions and networks. In this case, it is critical to account for confounds introduced by off-target stimulation of peripheral structures of the nervous system that may not only confound MR-based readouts but also induce neuroplastic phenomena.

The roles of the LpSTS and DLPFC in self-prioritization: A transcranial magnetic stimulation study

The Self‐Attention Network (SAN) has been proposed to describe the underlying neural mechanism of the self‐prioritization effect, yet the roles of the key nodes in the SAN—the left posterior superior temporal sulcus (LpSTS) and the dorsolateral prefrontal cortex (DLPFC)—still need to be clarified. One hundred and nine participants were randomly assigned into the LpSTS group, the DLPFC group, or the sham group. We used the transcranial magnetic stimulation (TMS) technique to selectively disrupt the functions of the corresponding targeted region, and observed its impacts on self‐prioritization effect based on the difference between the performance of the self‐matching task before and after the targeted stimulation. We analyzed both model‐free performance measures and HDDM‐based performance measures for the self‐matching task. The results showed that the inhibition of LpSTS could lead to reduced performance in processing self‐related stimuli, which establishes a causal role for the LpSTS in self‐related processing and provide direct evidence to support the SAN framework. However, the results of the DLPFC group from HDDM analysis were distinct from the results based on response efficiency. Our investigation further the understanding of the differentiated roles of key nodes in the SAN in supporting the self‐salience in information processing.

Cognitive control affects motor learning through local variations in GABA within the primary motor cortex

The primary motor cortex (M1) is crucial for motor learning; however, its interaction with other brain areas during motor learning remains unclear. We hypothesized that the fronto-parietal execution network (FPN) provides learning-related information critical for the flexible cognitive control that is required for practice. We assessed network-level changes during sequential finger tapping learning under speed pressure by combining magnetic resonance spectroscopy and task and resting-state functional magnetic resonance imaging. There was a motor learning-related increase in preparatory activity in the fronto-parietal regions, including the right M1, overlapping the FPN and sensorimotor network (SMN). Learning-related increases in M1-seeded functional connectivity with the FPN, but not the SMN, were associated with decreased GABA/glutamate ratio in the M1, which were more prominent in the parietal than the frontal region. A decrease in the GABA/glutamate ratio in the right M1 was positively correlated with improvements in task performance (p = 0.042). Our findings indicate that motor learning driven by cognitive control is associated with local variations in the GABA/glutamate ratio in the M1 that reflects remote connectivity with the FPN, representing network-level motor sequence learning formations.

The integrative role of the M1 in motor sequence learning

The primary motor cortex (M1) is crucial in motor learning. Whether the M1 encodes the motor engram for sequential finger tapping formed by an emphasis on speed is still inconclusive. The active states of engrams are hard to discriminate from the motor execution per se. As preparatory activity reflects the upcoming movement parameters, we hypothesized that the retrieval of motor engrams generated by different learning modes is reflected as a learning-related increase in the preparatory activity of the M1. To test this hypothesis, we evaluated the preparatory activity during the learning of sequential finger-tapping with the non-dominant left hand using a 7T functional MRI. Participants alternated between performing a tapping sequence as quickly as possible (maximum mode) or at a constant speed of 2 Hz paced by a sequence-specifying visual cue (constant mode). We found a training-related increase in preparatory activity in the network covering the bilateral anterior intraparietal sulcus and inferior parietal lobule extending to the right M1 during the maximum mode and the right M1 during the constant mode. These findings indicate that the M1, as the last effector of the motor output, integrates the motor engram distributed through the networks despite training mode differences.

Tapping the Potential of Multimodal Non-invasive Brain Stimulation to Elucidate the Pathophysiology of Movement Disorders

This mini-review provides a detailed outline of studies that have used multimodal approaches in non-invasive brain stimulation to investigate the pathophysiology of the three common movement disorders, namely, essential tremor, Parkinson’s disease, and dystonia. Using specific search terms and filters in the PubMed^® database, we finally shortlisted 27 studies in total that were relevant to this review. While two-thirds (Brittain et al., 2013) of these studies were performed on Parkinson’s disease patients, we could find only three studies that were conducted in patients with essential tremor. We clearly show that although multimodal non-invasive brain stimulation holds immense potential in unraveling the physiological mechanisms that are disrupted in movement disorders, the technical challenges and pitfalls of combining these methods may hinder their widespread application by movement disorder specialists. A multidisciplinary team with clinical and technical expertise may be crucial in reaping the fullest benefits from such novel multimodal approaches.

A microstructural neural network biomarker for dystonia diagnosis identified by a DystoniaNet deep learning platform

This research identified a microstructural neural network biomarker for objective and accurate diagnosis of isolated dystonia based on the disorder pathophysiology using an advanced deep learning algorithm, DystoniaNet, and raw structural brain images of large cohorts of patients with isolated focal dystonia and healthy controls. DystoniaNet significantly outperformed shallow machine-learning pipelines and substantially exceeded the current agreement rates between clinicians, reaching an overall accuracy of 98.8% in diagnosing different forms of isolated focal dystonia. These results suggest that DystoniaNet could serve as an objective, robust, and generalizable algorithmic platform of dystonia diagnosis for enhanced clinical decision-making. Implementation of the identified biomarker for objective and accurate diagnosis of dystonia may be transformative for clinical management of this disorder.

Isolated dystonia is a neurological disorder of heterogeneous pathophysiology, which causes involuntary muscle contractions leading to abnormal movements and postures. Its diagnosis is remarkably challenging due to the absence of a biomarker or gold standard diagnostic test. This leads to a low agreement between clinicians, with up to 50% of cases being misdiagnosed and diagnostic delays extending up to 10.1 y. We developed a deep learning algorithmic platform, DystoniaNet, to automatically identify and validate a microstructural neural network biomarker for dystonia diagnosis from raw structural brain MRIs of 612 subjects, including 392 patients with three different forms of isolated focal dystonia and 220 healthy controls. DystoniaNet identified clusters in corpus callosum, anterior and posterior thalamic radiations, inferior fronto-occipital fasciculus, and inferior temporal and superior orbital gyri as the biomarker components. These regions are known to contribute to abnormal interhemispheric information transfer, heteromodal sensorimotor processing, and executive control of motor commands in dystonia pathophysiology. The DystoniaNet-based biomarker showed an overall accuracy of 98.8% in diagnosing dystonia, with a referral of 3.5% of cases due to diagnostic uncertainty. The diagnostic decision by DystoniaNet was computed in 0.36 s per subject. DystoniaNet significantly outperformed shallow machine-learning algorithms in benchmark comparisons, showing nearly a 20% increase in its diagnostic performance. Importantly, the microstructural neural network biomarker and its DystoniaNet platform showed substantial improvement over the current 34% agreement on dystonia diagnosis between clinicians. The translational potential of this biomarker is in its highly accurate, interpretable, and generalizable performance for enhanced clinical decision-making.