Neural dynamics of cognitive control: Current tensions and future promise
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866917057839235072 |
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| author | Zhou, Dale Cosme, Danielle Kang, Yoona Stanoi, Ovidia Lydon-Staley, David M. Mucha, Peter J. Falk, Emily B. Ochsner, Kevin N. Bassett, Dani S. |
| author_facet | Zhou, Dale Cosme, Danielle Kang, Yoona Stanoi, Ovidia Lydon-Staley, David M. Mucha, Peter J. Falk, Emily B. Ochsner, Kevin N. Bassett, Dani S. |
| contents | Cognitive control is a suite of processes that helps individuals pursue goals despite resistance or uncertainty about what to do. Although cognitive control has been extensively studied as a dynamic feedback loop of perception, valuation, and action, it remains incompletely understood as a cohesive dynamic and distributed neural process. Here, we critically examine the history of and advances in the study of cognitive control, including how metaphors and cultural norms of power, morality, and rationality are intertwined with definitions of control, to consider holistically how different models explain which brain regions act as controllers. Controllers, the source of top-down signals, are typically localized in regions whose neural activations implement elementary component processes of control, including conflict monitoring and behavioral inhibition. Top-down signals from these regions guide the activation of other task-specific regions, biasing them towards task-specific activity patterns. A relatively new approach, network control theory, has roots in dynamical systems theory and systems engineering. This approach can mathematically show that controllers are regions with strongly nested and recurrent anatomical connectivity that efficiently propagate top-down signals, and precisely estimate the amount, location, and timing of signaling required to bias global activity to task-specific patterns. The theory converges with prior evidence, offers new mathematical tools and intuitions for understanding control loops across levels of analysis, and naturally produces graded predictions of control across brain regions and modules of psychological function that have been unconsidered or marginalized. We describe how prior approaches converge and diverge, noting directions for future integration to improve understanding of how the brain instantiates cognitive control. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_02063 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Neural dynamics of cognitive control: Current tensions and future promise Zhou, Dale Cosme, Danielle Kang, Yoona Stanoi, Ovidia Lydon-Staley, David M. Mucha, Peter J. Falk, Emily B. Ochsner, Kevin N. Bassett, Dani S. Neurons and Cognition Cognitive control is a suite of processes that helps individuals pursue goals despite resistance or uncertainty about what to do. Although cognitive control has been extensively studied as a dynamic feedback loop of perception, valuation, and action, it remains incompletely understood as a cohesive dynamic and distributed neural process. Here, we critically examine the history of and advances in the study of cognitive control, including how metaphors and cultural norms of power, morality, and rationality are intertwined with definitions of control, to consider holistically how different models explain which brain regions act as controllers. Controllers, the source of top-down signals, are typically localized in regions whose neural activations implement elementary component processes of control, including conflict monitoring and behavioral inhibition. Top-down signals from these regions guide the activation of other task-specific regions, biasing them towards task-specific activity patterns. A relatively new approach, network control theory, has roots in dynamical systems theory and systems engineering. This approach can mathematically show that controllers are regions with strongly nested and recurrent anatomical connectivity that efficiently propagate top-down signals, and precisely estimate the amount, location, and timing of signaling required to bias global activity to task-specific patterns. The theory converges with prior evidence, offers new mathematical tools and intuitions for understanding control loops across levels of analysis, and naturally produces graded predictions of control across brain regions and modules of psychological function that have been unconsidered or marginalized. We describe how prior approaches converge and diverge, noting directions for future integration to improve understanding of how the brain instantiates cognitive control. |
| title | Neural dynamics of cognitive control: Current tensions and future promise |
| topic | Neurons and Cognition |
| url | https://arxiv.org/abs/2511.02063 |