Philip A. Starr

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

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.

This study investigates how motor learning in Parkinson's Disease patients involves coordinated low-frequency cortico-basal ganglia activity to optimize preplanning of motor sequences.

The paper shows that REM sleep duration and delta activity in Parkinson's disease patients correlate with reduced daytime basal ganglia-cortical network pathology and improved alertness.

This study shows that therapeutic DBS for OCD suppresses BOLD activity in the default mode network compared to non-therapeutic configurations.

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

The paper examines neural oscillations in human basal ganglia and prefrontal cortex during decision-making tasks, finding distinct roles for beta and theta oscillations in tracking effort and previous reward.

This study uses multi-night recordings to show that Parkinson's disease affects NREM sleep by altering cortico-basal slow wave activity and subcortical beta power, with DBS enhancing these changes and predicting spontaneous awakenings.

This study develops a model to predict cortical gamma oscillation entrainment to DBS in Parkinson's patients and validates it in three subjects.

This paper identifies artifacts in neural signals from a DBS device during stimulation and presents an offline removal method using template subtraction.

This study uses wrist-worn accelerometers to classify bradykinesia fluctuations in Parkinson's patients at the single-minute timescale using individual and group models.

The paper introduces an open-source Matlab toolbox for processing and analyzing data from the Medtronic Summit RC+S neurostimulation system.

The paper investigates how implant location affects ECG contamination in neurostimulation systems, finding higher contamination in left-sided subclavicular implants compared to right-sided ones.

This paper describes a wireless neural interface for long-term home monitoring of neural activity in Parkinson's disease patients, enabling adaptive stimulation and behavioral state decoding.

This paper introduces PARRM, a method to remove stimulation artifacts from neural recordings, improving biomarker detection in neuromodulation.