Transformer-based neural speech decoding from surface and depth electrode signals.

This study investigates speech decoding from neural signals captured by intracranial electrodes. Most prior works can only work with electrodes on a 2D grid (i.e.

A corollary discharge circuit in human speech.

When we vocalize, our brain distinguishes self-generated sounds from external ones. A corollary discharge signal supports this function in animals; however, in humans, its exact origin and temporal dynamics remain unknown. We report electrocorticographic recordings in neurosurgical patients and a connectivity analysis framework based on Granger causality that reveals major neural communications.

From Single Words to Sentence Production: Shared Cortical Representations but Distinct Temporal Dynamics.

Sentence production is the uniquely human ability to transform complex thoughts into strings of words. Despite the importance of this process, language production research has primarily focused on single words. It remains an untested assumption that insights from this literature generalize to more naturalistic utterances like sentences.

Temporal integration in human auditory cortex is predominantly yoked to absolute time, not structure duration.

Sound structures such as phonemes and words have highly variable durations. Thus, there is a fundamental difference between integrating across absolute time (e.g.