Reversed functional gradient in primate prefrontal cortex: posterior dominance and frontopolar deactivation
Watanabe, K.; Hirata, M.; Suzuki, T.
Show abstract
The frontopolar cortex (FPC) is thought to coordinate the more posterior lateral prefrontal cortex (LPFC) during complex, non-routine behaviors through high-level functions such as management of multiple goals, exploration, and self-generated decision-making. However, direct neurophysiological comparisons with other prefrontal regions are lacking, leaving the FPCs putative dominance untested. Contrary to this view, our comparison of neuronal activity across the full anteroposterior LPFC in macaques during six distinct tasks probing these functions revealed a posterior-to-mid LPFC dominance, with resource-allocation, novelty-detection (including reward prediction error), and modality invariant decision-monitoring signals all showing a common posterior bias. In contrast, regardless of task demands, the FPCs strongest encoding was about the most recently executed action, and it displayed minimal object selectivity, even when objects were task-critical. We identified a turning point in this graded posterior-to-anterior transition from task-positive to task-negative regions around the border between the anterior and middle thirds of the LPFC. These findings challenge the prevailing notion that the LPFC is anterior-dominant across primate species, and provide evolutionary constraints on theories of human prefrontal organization.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Prospective and retrospective representations of saccadic movements in primate prefrontal cortex 98%
- Stimulus information guides the emergence of behavior related signals in primary somatosensory cortex during learning 98%
- Prefrontal projections modulate recurrent circuitry in insular cortex to support short-term memory 97%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.