Decoding semantics from natural speech using human intracranial EEG.

ABSTRACT: Brain-computer interfaces (BCIs) hold promise for restoring natural language production capabilities in patients with speech impairments, potentially enabling smooth conversation that conveys meaningful information via synthesized words. While considerable progress has been made in decoding phonetic features of speech, our ability to extract lexical semantic information (i.e. the meaning of individual words) from neural activity remains largely unexplored. Moreover, most existing BCI research has relied on controlled experimental paradigms rather than natural conversation, limiting our understanding of semantic decoding in ecological contexts. Here, we investigated the feasibility of decoding lexical semantic information from stereo-electroencephalography (sEEG) recordings in 14 participan

SUBMITTER: Pescatore CRC 

PROVIDER: S-EPMC11844374 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature