Evidence for a deep, distributed and dynamic semantic code in human ventral anterior temporal cortex

How does the human brain encode the meanings of words and objects? Most theories propose that local neural populations independently encode various semantic features. Alternatively, meanings may arise as distributed neural patterns that change radically in real time as a stimulus is processed. We introduce a technique for revealing a dynamically-changing distributed code in simulated neural data, then apply it to neural signals collected from human cortex while participants named line drawings of common items. The data reveal a dynamic semantic code along ventral temporal cortex possessing stable elements posteriorly and rapidly-changing elements anteriorly. The results challenge the established view of semantic representation, resolve conflicting findings from past research, and provide a new framework for understanding the time-course of distributed representation in the brain.