Nonlinear interactions in the thalamocortical loop in essential tremor: A model-based frequency domain analysis.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Movement Disorders

Background:

• Essential tremor (ET) is increasingly recognized as having a central nervous system origin.
• The motor cortex, thalamus, and cerebellum form a potential central tremorogenic network.
• Previous studies show linear associations between motor cortex and EMG, and thalamic LFP and EMG, but thalamocortical functional links during tremor are unclear.

Purpose of the Study:

• To investigate the functional association between the thalamus and motor cortex during active tremor periods in essential tremor.
• To explore nonlinear interactions within the central motor network of essential tremor.
• To assess the potential for developing an on-demand closed-loop deep brain stimulation (DBS) device for ET.

Main Methods:

• Recorded thalamic (Vim) local field potentials (LFPs), sensorimotor cortex EEG, and contralateral tremor arm EMG from two ET patients undergoing DBS surgery.
• Utilized coherence analysis to assess linear associations between recorded signals.
• Developed and applied a novel parametric nonlinear autoregressive with exogenous input (NARX) model for analyzing cross-frequency interactions.

Main Results:

• Coherence analysis revealed strong thalamo-muscular association but unclear EEG-thalamus relationships.
• The NARX model identified two distinct, non-overlapping frequency channels of communication between the thalamus and motor cortex, differentiating tremor-on and tremor-off states.
• Nonlinear time lags exceeded 50ms during tremor-on states, suggesting involvement of indirect multisynaptic pathways.

Conclusions:

• Nonlinear interactions, particularly cross-frequency nonlinear interactions, between the cortex and thalamus are crucial in the central motor network of essential tremor.
• This study demonstrates that functional interrelationships in ET should be analyzed beyond individual frequencies.
• The findings support the potential for a closed-loop DBS system for essential tremor based on automatic tremor detection.