Distributed feedforward and feedback cortical processing supports human speech production.

ABSTRACT: Speech production is a complex human function requiring continuous feedforward commands together with reafferent feedback processing. These processes are carried out by distinct frontal and temporal cortical networks, but the degree and timing of their recruitment and dynamics remain poorly understood. We present a deep learning architecture that translates neural signals recorded directly from the cortex to an interpretable representational space that can reconstruct speech. We leverage learned decoding networks to disentangle feedforward vs. feedback processing. Unlike prevailing models, we find a mixed cortical architecture in which frontal and temporal networks each process both feedforward and feedback information in tandem. We elucidate the timing of feedforward and feedback-related

SUBMITTER: Wang R 

PROVIDER: S-EPMC10589651 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature