All spectral frequencies of neural activity reveal semantic representation in the human anterior ventral temporal cortex

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Abstract

Intracranial electrophysiology offers a unique insight into the nature of information representation in the brain – it can be used to disentangle information encoded in local neuronal activity (gamma and high gamma frequencies) from information encoded via long-range interactions (lower frequencies). We used regularised logistic regression to decode animacy from time-frequency power and phase extracted from electrocorticography (ECoG) grid electrode data recorded on the surface of human vATL. Power in gamma (30 – 60 Hz) and high gamma (60 – 200 Hz) produced reliable decoding, indicating that semantic information is indeed expressed by local populations in vATL. However, power from a wide range of frequencies (4 – 200 Hz) produced significantly higher decoding accuracy and also exhibited the same rapidly-changing dynamic code previously observed when decoding voltage. These findings support the theory that semantic information is encoded by a local vATL “hub” that interacts with distributed cortical “spokes”.

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