ArticleProceedings of the National Academy of Sciences of the United States of America2024
Dynamic tuning of neural stability for cognitive control.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Prefrontal Mechanisms of Rule Learning.bioRxiv : the preprint server for biology · 2026Article
- Dynamic tuning of neural stability for cognitive control.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
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Authors and funding
4 authors.
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Abstract
The brain is thought to execute cognitive control by actively maintaining and flexibly updating patterns of neural activity that represent goals and rules. However, while actively maintaining patterns of activity requires robustness against noise and distractors, updating the activity requires sensitivity to task-relevant inputs. How these conflicting demands can be reconciled in a single neural system remains unclear. Here, we study the prefrontal cortex of monkeys maintaining a covert rule and integrating sensory inputs toward a choice. Following the onset of neural responses, sensory integration evolves with a 70 ms delay. Using a stability analysis and a recurrent neural network model trained to perform the task, we show that this delay enables a transient, system-level destabilization, opening a temporal window to selectively incorporate new information. This mechanism allows robustness and sensitivity to coexist in a neural system and hierarchically updates patterns of neural activity, providing a general framework for cognitive control. Furthermore, it reveals a learned, explicit rule representation, suggesting a reconciliation between the symbolic and connectionist approaches for building intelligent machines.
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