Patrick L. Purdon

This paper introduces a dynamic generative model to extract interpretable oscillatory components from multichannel neurophysiological recordings, improving component selection and interpretation.

This paper develops a switching state-space model for analyzing time-varying neural data, showing improved performance in detecting transient sleep spindles from EEG recordings.

The paper analyzes longitudinal EEG data from infants to identify age-related changes in periodic and aperiodic power, linking these changes to thalamocortical network development.

This paper constructs a biophysical thalamocortical model to simulate propofol-induced EEG changes, revealing two dynamic states linked to cortical synchronization and brainstem influence.

The paper shows propofol causes alpha rhythms to shift from posterior to anterior in two distinct thalamocortical networks, disrupting sensory and cognitive function during loss of consciousness.

This paper introduces an iterative algorithm to identify oscillatory dynamics in neural data, outperforming existing methods in accuracy and adaptability.

This paper introduces a state space model for phase amplitude coupling analysis that improves statistical efficiency and reduces errors from frequency band selection and signal non-linearities.

This study examines ketamine-induced brain dynamics in humans using intracranial recordings, identifying oscillatory changes linked to antidepressant and dissociative effects.

This study assesses the relationship between behavioral and autonomic dynamics during propofol-induced unconsciousness using statistical models and physiological data from nine volunteers.

The paper models EDA pulse amplitudes as differences of inverse Gaussian distributions, showing they outperform other models in describing physiological sweat production.

This study develops an automated EEG-based method to monitor sedation levels during office-based anesthesia using spectral features and achieves an AUC of 0.85.

The paper investigates broadband slow-wave modulation in posterior and anterior cortex during propofol-induced unconsciousness, finding distinct brain state shifts associated with different depths of anesthesia.

This study identifies age-related changes in electroencephalographic oscillations during sevoflurane anesthesia in children, revealing developmental milestones in GABAergic circuit activity.