0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessAbstract Contextual cues and prior evidence guide human goal-directed behavior. To date, the neurophysiological mechanisms that implement contextual priors to guide subsequent actions remain unclear. Here we demonstrate that increasing behavioral uncertainty introduces a shift from an oscillatory to a continuous processing mode in human prefrontal cortex. At the population level, we found that oscillatory and continuous dynamics reflect dissociable signatures that support distinct aspects of encoding, transmission and execution of context-dependent action plans. We show that prefrontal population activity encodes predictive context and action plans in serially unfolding orthogonal subspaces, while prefrontal-motor theta oscillations synchronize action-encoding population subspaces to mediate the hand-off of action plans. Collectively, our results reveal how two key features of large-scale population activity, namely continuous population trajectories and oscillatory synchrony, operate in concert to guide context-dependent human behavior.
Jan Weber, Anne‐Kristin Solbakk, Alejandro O. Blenkmann, Anaïs Llorens, Ingrid Funderud, Sabine Leske, Pål G. Larsson, Jugoslav Ivanović, Robert T. Knight, Tor Endestad, Robert Thomas Knight (2021). Population coding and oscillatory subspace synchronization integrate context into actions. , DOI: https://doi.org/10.1101/2021.12.17.473118.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Preprint
Year
2021
Authors
11
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1101/2021.12.17.473118
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access