Dynamic Coding for Cognitive Control in Prefrontal Cortex

By Mark G. Stokes, Makoto Kusunoki, Natasha Sigala, Hamed Nili, David Gaffan, John S. Duncan. 2013

679 citations recorded by the source corpus.

Summary Cognitive flexibility is fundamental to adaptive intelligent behavior. Prefrontal cortex has long been associated with flexible cognitive function, but the neurophysiological principles that enable prefrontal cells to adapt their response properties according to context-dependent rules remain poorly understood. Here, we use time-resolved population-level neural pattern analyses to explore how context is encoded and maintained in primate prefrontal cortex and used in flexible decision making. We show that an instruction cue triggers a rapid series of state transitions before settling into a stable low-activity state. The postcue state is differentially tuned according to the current task-relevant rule. During decision making, the response to a choice stimulus is characterized by an initial stimulus-specific population response but evolves to different final decision-related states depending on the current rule. These results demonstrate how neural tuning profiles in prefrontal cortex adapt to accommodate changes in behavioral context. Highly flexible tuning could be mediated via short-term synaptic plasticity.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

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Citations in the corpus

Learning Rapid-Temporal Adaptations (2017, background): “Neuroscientiﬁc evidence suggests that PFC uses incoming information to support task-speciﬁc temporal adaptation and planning [38, 35, 22, 5].”
Deconstructing multivariate decoding for the study of brain function (2017, background): “Likewise, cross-classification in generalization across time is becoming more common to infer stable or dynamic representations (Stokes et al., 2013).”
Mapping the human brain’s cortical-subcortical functional network organization (2018, neutral): “This result suggests that the task-rule-oriented representations in lateral prefrontal cortex (Cole et al., 2011; Stokes et al., 2013) likely interact extensively with action-outcome and stimulus-reward associations in OFC (Kahnt et al.”
Low-dimensional dynamics for working memory and time encoding (2020, background): “Thethird category of models is one in which the activity varies in time but across trajectories that are low-dimensional (19–22).”
Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks (2017, result): “These findings are compatible with evidence of adaptive coding properties in FPCN neurons (2) and suggest that some FPCN nodes may be relatively domain general in nature, consistent with the notion of a multiple demand system (4).”
The theory of constructed emotion: an active inference account of interoception and categorization (2017, neutral): “However, a given neuron (or group of neurons) represents different features from moment to moment (e.g. Stokes et al., 2013; Spillmann et al., 2015) because many neurons synapse onto one (many-to-one connectivity), and a neuron’s receptive field depends on the information it receives (i.e. depends…”
Neural Coding of Cognitive Control: The Representational Similarity Analysis Approach. (2020, background): “, [125,126]): neuronal selectivities appear to be dynamic, often changing within single trials [127], and are highly conjunctive, reflecting a mixture of task attributes [128].”
Executive control and decision-making in the prefrontal cortex (2015, neutral): “In such situations, consistently, both reward-based and cue-based decisions engage the lateral prefrontal cortex (lPFC) [26,27], which subserves cognitive control, that is, the formation and selection of such action sets [3,9,23,24,28–32].”
Gamma and beta bursts underlie working memory (2016, neutral): “Instead, most neurons show brief bouts of activity with variable onset latency and durations, sprinkled throughout the delay (Cromer et al., 2010; Shafi et al., 2007) suggesting highly dynamic activity (Durstewitz and Seamans, 2006; Stokes et al., 2013).”
The Role of Prefrontal Mixed Selectivity in Cognitive Control (2016, background): “These findings challenge the classical view regarding the implementation of working memory and suggest that additional mechanisms maintain stimulus information (Lebedev et al., 2004; Stokes et al., 2013; Jacob and Nieder, 2014; Lara and Wallis, 2014).”
Decoding Dynamic Brain Patterns from Evoked Responses: A Tutorial on Multivariate Pattern Analysis Applied to Time Series Neuroimaging Data (2016, neutral): “Ramkumar, Jas, Pannasch, Hari, & Parkkonen, 2013) and to study decision-making (Stokes et al., 2013; Bode et al., 2012), illusions (Hogendoorn, Verstraten, & Cavanagh, 2015), or working memory (Wolff, Ding, Myers, & Stokes, 2015; van Gerven et al.”
Emotion and the Prefrontal Cortex: An Integrative Review (2017, background): “The lateral PFC has a well-established role in contributing to cognitive control via flexible representation of task rules, abstract concepts, social context, and long-term goals (Bunge et al., 2003; Christoff & Keramatian, 2007; Duncan, 2010; McClure, Laibson, Loewenstein, & Cohen, 2004; Miller & C”