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A central challenge in neuroscience is to understand how the brain flexibly balances local and distributed information processing to support diverse cognitive and conscious states. We hypothesize that a key signature of this balance is the presence of memory effects, which arise when a brain region’s future activity depends not only on its current state, but also on past information fed back from the wider network. Here we introduce the FDTest, a method for assessing local memory effects in multidimensional systems by measuring violations of a generalized Fluctuation–dissipation theorem (FDT). We first apply this framework to whole-brain models fitted to human neuroimaging data, demonstrating that the brain’s memory structure reflects its underlying connectivity. We then extend the analysis to individualized models of subjects during wakefulness and deep sleep. Memory effects are consistently stronger in wakefulness, indicating richer inter-regional dependencies and more integrated dynamics. These findings establish local memory as a dynamical marker of brain state and position the FDTest as a principled tool for probing the hidden structure of neural dynamics.
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Geli et al. (2026) studied this question.
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