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Response function as a quantitative measure of consciousness in brain dynamics

Wenkang Du, Haiping Huang

Physical Review Research December 3, 2025 DOI: 10.1103/6lx7-qsv7 (opens in new tab) via DOAJ

Summary

AI-generated from the abstract

A robust, brain-state-dependent neural response function may be a necessary dynamical condition for consciousness. Using intracranial recordings from nonhuman primates across wakefulness, anesthesia, and recovery, researchers fit a nonequilibrium recurrent neural network model to extract the neural response function as an indicator of dynamics complexity. The amplitude of this function peaks near the transition between ordered and chaotic regimes, highlighting criticality as a potential principle for flexible cortical dynamics. During wakefulness, neural responsiveness is strong and widely distributed. Under anesthesia, response amplitudes are suppressed and dynamics become more chaotic. During recovery, the response function is elevated, paralleling the restoration of conscious processing.

Study at a glance

Characteristics Observational study Peer reviewed
Population Nonhuman primates
Key finding The amplitude of the neural response function serves as a robust dynamical indicator of conscious state, with strong responsiveness during wakefulness, suppression under anesthesia, and elevation during recovery.

Abstract

Understanding the neural correlates of consciousness remains a central challenge in neuroscience. In this study, we investigate the relationship between consciousness and neural responsiveness by analyzing intracranial electrocorticography recordings from nonhuman primates across three distinct states: wakefulness, anesthesia, and recovery. Using a nonequilibrium recurrent neural network (RNN) model, we fit state-dependent cortical dynamics to extract the neural response function as a dynamics complexity indicator. Our findings demonstrate that the amplitude of the neural response function serves as a robust dynamical indicator of conscious state, consistent with the role of a linear response function in statistical physics. Notably, this aligns with our previous theoretical results showing that the response function in RNNs peaks near the transition between ordered and chaotic regimes—highlighting criticality as a potential principle for sustaining flexible and responsive cortical dynamics. Empirically, we find that during wakefulness, neural responsiveness is strong, widely distributed, and consistent with rich nonequilibrium fluctuations. Under anesthesia, response amplitudes are significantly suppressed, and the network dynamics become more chaotic, indicating a loss of dynamical sensitivity. During recovery, the neural response function is elevated, supporting the gradual re-establishment of flexible and responsive activity that parallels the restoration of conscious processing. Our work suggests that a robust, brain-state-dependent neural response function may be a necessary dynamical condition for consciousness, providing a principled framework for quantifying levels of consciousness in terms of nonequilibrium responsiveness in the brain.

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