Cogan, G. B. | bioRxiv Science

bioRxiv2024

Neural mechanisms of the transition from planning to execution in speech production

Speaking is the primary way that humans communicate. This communication is enabled by a production system that can plan and execute unique combinations of speech sounds. Although a distributed network of brain regions has been implicated in speaking, it is unclear how planning and execution of speech are coordinated to produce meaningful sounds. Leveraging the high spatio-temporal resolution of intracranial recordings at different spatial scales, we show distinct neural mechanisms that facilitate speech planning and execution. During planning, different levels of speech units are coded discretely at distinct prefrontal sites. These planned units are then dynamically integrated at various cortical levels to guide subsequent execution. During speech execution, speech motor regions generate continuous sequences that reflect both discrete speech sound units and their transitional properties between units. This rapid neural transition from discrete speech units to motor sequences links speech planning with execution and enables our effortless ability to speak.

neuroscience↗

bioRxiv2022

Accurate speech decoding requires high-resolution neural interfaces

Patients suffering from debilitating neurodegenerative diseases often lose the ability to communicate, detrimentally affecting their quality of life. One promising solution to restore communication is to decode signals directly from the brain to enable neural speech prostheses. However, decoding has been limited by coarse neural recordings which inadequately capture the rich spatio-temporal structure of human brain signals. To resolve this limitation, we performed novel, high-resolution, micro-electrocorticographic (ECoG) neural recordings during intra-operative speech production. We obtained neural signals with 57x higher spatial resolution and 48% higher signal-to-noise ratio compared to standard invasive recordings. This increased signal quality improved phoneme decoding by 35% compared to standard intracranial signals. Accurate decoding was dependent on the high-spatial resolution of the neural interface. Non-linear decoding models designed to utilize enhanced spatio-temporal neural information produced better results than linear techniques. We show for the first time that ECoG can enable high-quality speech decoding, demonstrating its ability to improve neural interfaces for neural speech prostheses.

neuroscience↗