Kyle Rupp

The paper uses deep neural networks to model neural responses in human auditory cortex and finds gradients of processing complexity and integration timescales across brain regions.

The paper investigates functional heterogeneity in voice-encoding cortex using electrophysiological and clinical stimulation mapping in patients with sEEG, finding overlapping roles in voice encoding and language.

This study uses intracranial recordings to map speech processing latencies and task effects across the human forebrain, revealing hierarchical and parallel information flow and task-related neural responses.

The paper uses human intracerebral recordings to show that voice is encoded categorically in STG and STS, not by acoustic features, and this selectivity increases along the auditory hierarchy.

This study investigates cortical sources of frequency following responses (FFRs) to speech across species, finding robust FFRs in auditory cortex and their contribution to scalp-recorded signals.