The cerebellum computes frequency dynamics for motions with numerical precision and cross-individual uniformity.

Cross-individual variability is considered the essence of biology, preventing precise mathematical descriptions of biological motion1-7 like the physics law of motion. Here we report that the cerebellum shapes motor kinematics by encoding dynamic motor frequencies with remarkable numerical precision and cross-individual uniformity. Using in-vivo electrophysiology and optogenetics in mice, we confirmed that deep cerebellar neurons encoded frequencies via populational tuning of neuronal firing probabilities, creating cerebellar oscillations and motions with matched frequencies. The mechanism was consistently presented in self-generated rhythmic and non-rhythmic motions triggered by a vibrational platform, or skilled tongue movements of licking in all tested mice with cross-individual uniformity. The precision and uniformity allowed us to engineer complex motor kinematics with designed frequencies. We further validated the frequency-coding function of the human cerebellum using cerebellar electroencephalography recordings and alternating-current stimulation during voluntary tapping tasks. Our findings reveal a cerebellar algorithm for motor kinematics with precision and uniformity, the mathematical foundation for brain-computer interface for motor control.

Effects of Low-Frequency Deep Brain Stimulation in Bilateral Zona Incerta for a Patient With Tremor and Cerebellar Ataxia.

Background: Whether low-frequency deep brain stimulation (DBS) in the caudal zona incerta (cZi) can improve cerebellar ataxia symptoms remains unexplored. Case Report: We report a 66-year-old man initially diagnosed with essential tremor and subsequently developed cerebellar ataxia after bilateral cZi DBS implantation. We tested the effects of low-frequency DBS stimulations (sham, 10 Hz, 15 Hz, 30 Hz) on ataxia severity. Discussion: Low-frequency cZi DBS improves ataxic speech at 30 Hz, but not at 10 Hz or 15 Hz in this patient. Low-frequency DBS did not improve gait or stance. Therefore, low-frequency stimulation may play a role in treating ataxic speech. Highlights: The finding of this case study suggests that bilateral low-frequency DBS at 30 Hz in the caudal zona incerta has the potential to improve ataxic speech but has limited impact on gait and stance. The involvement of zona incerta in speech warrants further investigation.

Neuronal population activity in the olivocerebellum encodes the frequency of essential tremor in mice and patients.

Essential tremor (ET) is the most prevalent movement disorder, characterized primarily by action tremor, an involuntary rhythmic movement with a specific frequency. However, the neuronal mechanism underlying the coding of tremor frequency remains unexplored. Here, we used in vivo electrophysiology, optogenetics, and simultaneous motion tracking in the Grid2dupE3 mouse model to investigate whether and how neuronal activity in the olivocerebellum determines the frequency of essential tremor. We report that tremor frequency was encoded by the temporal coherence of population neuronal firing within the olivocerebellums of these mice, leading to frequency-dependent cerebellar oscillations and tremors. This mechanism was precise and generalizable, enabling us to use optogenetic stimulation of the deep cerebellar nuclei to induce frequency-specific tremors in wild-type mice or alter tremor frequencies in tremor mice. In patients with ET, we showed that deep brain stimulation of the thalamus suppressed tremor symptoms but did not eliminate cerebellar oscillations measured by electroencephalgraphy, indicating that tremor-related oscillations in the cerebellum do not require the reciprocal interactions with the thalamus. Frequency-disrupting transcranial alternating current stimulation of the cerebellum could suppress tremor amplitudes, confirming the frequency modulatory role of the cerebellum in patients with ET. These findings offer a neurodynamic basis for the frequency-dependent stimulation of the cerebellum to treat essential tremor.

Neuronal networks underlying ictal and subclinical discharges in childhood absence epilepsy.

Childhood absence epilepsy (CAE), involves 3 Hz generalized spikes and waves discharges (GSWDs) on the electroencephalogram (EEG), associated with ictal discharges (seizures) with clinical symptoms and impairment of consciousness and subclinical discharges without any objective clinical symptoms or impairment of consciousness. This study aims to comparatively characterize neuronal networks underlying absence seizures and subclinical discharges, using source localization and functional connectivity (FC), to better understand the pathophysiological mechanism of these discharges. Routine EEG data from 12 CAE patients, consisting of 45 ictal and 42 subclinical discharges were selected. Source localization was performed using the exact low-resolution electromagnetic tomography (eLORETA) algorithm, followed by FC based on the imaginary part of coherency. FC based on the thalamus as the seed of interest showed significant differences between ictal and subclinical GSWDs (p < 0.05). For delta (1-3 Hz) and alpha bands (8-12 Hz), the thalamus displayed stronger connectivity towards other brain regions for ictal GSWDs as compared to subclinical GSWDs. For delta band, the thalamus was strongly connected to the posterior cingulate cortex (PCC), precuneus, angular gyrus, supramarginal gyrus, parietal superior, and occipital mid-region for ictal GSWDs. The strong connections of the thalamus with other brain regions that are important for consciousness, and with components of the default mode network (DMN) suggest the severe impairment of consciousness in ictal GSWDs. However, for subclinical discharges, weaker connectivity between the thalamus and these brain regions may suggest the prevention of impairment of consciousness. This may benefit future therapeutic targets and improve the management of CAE patients.

Physiological Recordings of the Cerebellum in Movement Disorders.

The cerebellum plays an important role in movement disorders, specifically in symptoms of ataxia, tremor, and dystonia. Understanding the physiological signals of the cerebellum contributes to insights into the pathophysiology of these movement disorders and holds promise in advancing therapeutic development. Non-invasive techniques such as electroencephalogram and magnetoencephalogram can record neural signals with high temporal resolution at the millisecond level, which is uniquely suitable to interrogate cerebellar physiology. These techniques have recently been implemented to study cerebellar physiology in healthy subjects as well as individuals with movement disorders. In the present review, we focus on the current understanding of cerebellar physiology using these techniques to study movement disorders.

Differentiating ictal/subclinical spikes and waves in childhood absence epilepsy by spectral and network analyses: A pilot study.

OBJECTIVE: Childhood absence epilepsy (CAE) is a disease with distinct seizure semiology and electroencephalographic (EEG) features. Differentiating ictal and subclinical generalized spikes and waves discharges (GSWDs) in the EEG is challenging, since they appear to be identical upon visual inspection. Here, spectral and functional connectivity (FC) analyses were applied to routine EEG data of CAE patients, to differentiate ictal and subclinical GSWDs. METHODS: Twelve CAE patients with both ictal and subclinical GSWDs were retrospectively selected for this study. The selected EEG epochs were subjected to frequency analysis in the range of 1-30 Hz. Further, FC analysis based on the imaginary part of coherency was used to determine sensor level networks. RESULTS: Delta, alpha and beta band frequencies during ictal GSWDs showed significantly higher power compared to subclinical GSWDs. FC showed significant network differences for all frequency bands, demonstrating weaker connectivity between channels during ictal GSWDs. CONCLUSION: Using spectral and FC analyses significant differences between ictal and subclinical GSWDs in CAE patients were detected, suggesting that these features could be used for machine learning classification purposes to improve EEG monitoring. SIGNIFICANCE: Identifying differences between ictal and subclinical GSWDs using routine EEG, may improve understanding of this syndrome and the management of patients with CAE.