Angelique Christine Paulk

This paper presents a functional atlas of the human central nervous system using high-resolution surface electrophysiology from 70 patients, revealing conserved electrophysiological patterns and enabling neuroprosthetic applications.

The paper investigates how motor cortex activity changes during observation of different anthropomorphic effectors, finding increased neural modulation with greater human-likeness of the observed agents.

The paper determines optimal electrode spacing for maximizing single unit yield in neural recordings across species and brain regions.

This study uses deep learning models to analyze neural activity during conversation, showing distributed and context-dependent patterns for speech production and comprehension.

This study shows that the human hippocampus can process oddball tones and language stimuli, including semantic and grammatical features, even under general anesthesia.

DREDge improves motion correction in high-density extracellular recordings across species, enhancing reliability and reducing errors in electrophysiological data.

This study decodes lexical semantic information from natural speech using intracranial EEG in participants during spontaneous conversation, achieving 21% accuracy.

The paper examines how a history of depressive symptoms in individuals with epilepsy affects fronto-temporo-limbic connectivity during cognitive conflict encoding using sEEG and DCM.

This study investigates how theta-burst stimulation affects neural activity in human brain networks using intracranial EEG during direct electrical stimulation.

The paper identifies modular organization in human superior temporal gyrus for phoneme processing using high-density micro-arrays.

The paper introduces a high-channel-count flexible electrode for deep brain recording, capable of capturing single-unit activity from up to 128 channels.

This study uses intracranial EEG and machine learning to show dynamic, activity-silent mechanisms maintain auditory working memory in humans.

The paper introduces a Brain-iEEG-microdisplay that measures and displays real-time brain activity during surgery, improving precision and efficiency in neurosurgical procedures.

This paper introduces DREDge, an algorithm for robust online drift estimation in electrophysiology data, improving scalability and temporal resolution for human and mouse recordings.

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

This paper describes a new high-density Neuropixels probe enabling single-cell resolution recordings from over 200 cortical neurons in humans during surgery, identifying eight distinct single unit classes.

The paper examines how stimulation location relative to grey and white matter affects single pulse electrical stimulation responses in the human brain, finding location and parameter-specific effects.

The paper identifies three distinct classes of cortical activity using high-density microelectrodes, showing they are modulated by stimuli and present across species.

This study uses state-space modeling and intracranial stimulation to modulate hidden emotional states during conflict resolution, showing bidirectional effects on behavior.