Abhinav Sharma

Device-embedded accelerometry complements neural signals for tracking parkinsonian motor states

This study shows that device-embedded accelerometry better tracks Parkinsonian motor states than neural signals during deep brain stimulation.

Spontaneous network transitions predict somatosensory perception

The paper shows that spontaneous brain network transitions during the pre-stimulus period predict correct or incorrect somatosensory perception in an ambiguous tactile task.

Dynamic neural states underpin bradykinesia severity in Parkinsons disease

This study identifies neural states in Parkinson's disease patients using Hidden Markov Models and links them to bradykinesia severity through spectral and temporal features.

Context-Dependent Modulations of Subthalamo-Cortical Synchronization during Rapid Reversals of Movement Direction in Parkinson's Disease

This study examines beta oscillations in Parkinson's disease patients during movement direction reversals, finding context-dependent changes in subthalamo-cortical synchronization and beta power modulations.

Beta burst characteristics and coupling within the sensorimotor cortical-subthalamic nucleus circuit in Parkinson's disease

The paper analyzes beta burst characteristics and coupling between sensorimotor cortical and subthalamic nucleus (STN) regions in Parkinson's disease patients during naturalistic behaviors.

Prediction of pathological subthalamic nucleus beta burst occurrence in Parkinson's disease

This paper predicts subthalamic nucleus beta bursts in Parkinson's disease using deep learning, identifying a predictive biomarker for burst onset.

Differential dopaminergic modulation of spontaneous cortico-subthalamic activity in Parkinson's disease

This study examines how dopaminergic medication affects oscillatory brain networks in Parkinson's disease using combined STN and MEG recordings.

Evaluation of data-driven MEG analysis approaches for the extraction of fMRI resting state networks

This study compares two MEG analysis methods for extracting resting state networks and finds that phase-amplitude coupling provides better alignment with fMRI results than Hilbert envelope ICA.