DOAJ Open Access 2024

Flexible encoding of multiple task dimensions in human cerebral cortex

Benjamin J. Tamber-Rosenau Benjamin J. Tamber-Rosenau Benjamin J. Tamber-Rosenau Allen T. Newton Allen T. Newton +3 lainnya

Abstrak

IntroductionCognitive models have proposed that behavioral tasks can be categorized along at least three dimensions: the sensory-motor modality of the information, its representational format (e.g., location vs. identity), and the cognitive processes that transform it (e.g., response selection). Moreover, we can quickly and flexibly encode, represent, or manipulate information along any of these dimensions. How is this flexibility in encoding such information implemented in the cerebral cortex?MethodsTo address this question, we devised a series of functional magnetic resonance imaging (fMRI) experiments in each of which participants performed two distinct tasks that differed along one of the three dimensions.ResultsUsing multivariate pattern analysis of the fMRI data, we were able to decode between tasks along at least one task dimension within each of the cortical regions activated by these tasks. Moreover, the multiple demand network, a system of brain regions previously associated with flexible task encoding, was largely composed of closely juxtaposed sets of voxels that were specialized along each of the three tested task dimensions.DiscussionThese results suggest that flexible task encoding is primarily achieved by the juxtaposition of specialized representations processing each task dimension in the multiple demand network.

Topik & Kata Kunci

Penulis (8)

B

Benjamin J. Tamber-Rosenau

B

Benjamin J. Tamber-Rosenau

B

Benjamin J. Tamber-Rosenau

A

Allen T. Newton

A

Allen T. Newton

R

René Marois

R

René Marois

R

René Marois

Format Sitasi

Tamber-Rosenau, B.J., Tamber-Rosenau, B.J., Tamber-Rosenau, B.J., Newton, A.T., Newton, A.T., Marois, R. et al. (2024). Flexible encoding of multiple task dimensions in human cerebral cortex. https://doi.org/10.3389/fcogn.2024.1438390

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Informasi Jurnal
Tahun Terbit
2024
Sumber Database
DOAJ
DOI
10.3389/fcogn.2024.1438390
Akses
Open Access ✓