Muthuraman Muthuraman

OTTER maps mouse and human brain regions using optimal transport, revealing evolutionary differences in association cortex and enabling cross-species predictions.

This study uses high-density electrospinography to examine frequency-specific spinal activity and cortico-spinal connectivity during pincer-grip, revealing distinct spatial patterns and beta-band activation.

The paper introduces a high-density electrode system for recording spinal cord neural activity, demonstrating its ability to capture evoked potentials and validate its design through topographic mapping.

This study investigates the aperiodic exponent of subthalamic field potentials in Parkinsonism across species, finding it reflects excitation/inhibition balance and could be a biomarker for adaptive deep brain stimulation.

This study investigates how subthalamic nucleus activity modulates action adaptation in Parkinson's patients during a force adaptation task, finding that reduced beta activity correlates with better adaptation.

This paper introduces non-parametric rank statistics for robust spectral power and coherence analysis in neural signals, showing improved robustness against artefacts and enabling new testing scenarios.

This study uses cortical network analysis to predict deep brain stimulation outcomes in dystonia patients, finding that grey matter atrophy patterns can predict response with 88% accuracy.

This study uses TMS-EEG to examine dmPFC excitability during fear processing and links it to structural brain properties.