Searching through functional space reveals distributed visual, auditory, and semantic coding in the human brain
Name
journal.pcbi.1008457.pdf
Description
Published version
Size
1.67 MB
Format
Adobe PDF
Checksum (MD5)
b397878f0fe6bdb8b6f4d01ad002d917
Author(s)
Kumar, Sreejan
Ellis, Cameron T
O’Connell, Thomas P
Chun, Marvin M
Turk-Browne, Nicholas B
Date Issued
December 3, 2020
Journal
PLOS Computational Biology
Publisher
Public Library of Science (PLoS)
Citation
Kumar S, Ellis CT, O’Connell TP, Chun MM, Turk-Browne NB (2020) Searching through functional space reveals distributed visual, auditory, and semantic coding in the human brain. PLOS Computational Biology 16(12): e1008457.
Version
Final published version
Abstract
The extent to which brain functions are localized or distributed is a foundational question in neuroscience. In the human brain, common fMRI methods such as cluster correction, atlas parcellation, and anatomical searchlight are biased by design toward finding localized representations. Here we introduce the functional searchlight approach as an alternative to anatomical searchlight analysis, the most commonly used exploratory multivariate fMRI technique. Functional searchlight removes any anatomical bias by grouping voxels based only on functional similarity and ignoring anatomical proximity. We report evidence that visual and auditory features from deep neural networks and semantic features from a natural language processing model, as well as object representations, are more widely distributed across the brain than previously acknowledged and that functional searchlight can improve model-based similarity and decoding accuracy. This approach provides a new way to evaluate and constrain computational models with brain activity and pushes our understanding of human brain function further along the spectrum from strict modularity toward distributed representation.
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DOI of Published Version
https://doi.org/10.1371/journal.pcbi.1008457
