Daniel Friedman

The paper shows that divisive normalization models better capture temporal dynamics in human somatosensory cortex compared to linear models, mirroring visual cortex findings.

The paper identifies a modality-specific gradient in the frontal cortex during naturalistic audiovisual processing, showing dynamic adaptation to different contexts.

The paper decodes behavioral states during speech production and perception using functional connectivity from ECoG data, achieving 73.9% accuracy in classifying states.

The paper creates a probabilistic functional atlas of brain regions using extraoperative electrocortical stimulation data, revealing variability in functional organization and highlighting key areas for language and motor functions.

The paper identifies the source and timing of a corollary discharge signal in human speech using ECoG recordings and Granger-causality analysis.

This study analyzes intracranial EEG power changes in frontal lobe seizures to determine how they relate to impaired consciousness, finding distinct patterns across seizure types.