- Cognitive control is a dynamic, distributed neural process integrating perception, valuation and action within feedback loops influenced by cultural metaphors of power and rationality.
- Controllers are brain regions whose activations implement component processes like conflict monitoring and inhibition, sending top-down signals to bias task-specific regions.
- Network control theory mathematically identifies controllers by nested recurrent connectivity, estimating required signalling amount, location and timing to bias global activity patterns.
Neurosci Biobehav Rev. 2026 Aug 17:106909. doi: 10.1016/j.neubiorev.2026.106909. Online ahead of print.
ABSTRACT
Cognitive control is a suite of processes that helps individuals pursue goals despite resistance or uncertainty about what to do. Deficits of cognitive control underlie compulsive or risky behavior, as well as other clinical challenges associated with difficulties in regulating impulses, attention, thoughts, and feelings. 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. Importantly, the theory converges with established findings, provides 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, marginalized, or indirectly linked. We describe how psychological and network control approaches converge and diverge, noting directions for future integration that could strengthen and sharpen our understanding and predictions of how the brain instantiates cognitive control.
PMID:42607981 | DOI:10.1016/j.neubiorev.2026.106909
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