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When neural spikes break time’s symmetry: Linking the information-theoretic cost of brain activity to behavior

What if we could peer into the brain and watch how it organizes information as we act, perceive, or make decisions? A new study has introduced a method that does exactly this—not just by looking at fine-grained neuronal spiking activity, but by characterizing its collective dynamics using principles from thermodynamics.

A team from Kyoto University and Hokkaido University developed a new statistical framework capable of tracing directional, nonequilibrium neural dynamics directly from large-scale spike recordings, enabling them to show how neurons dissipate entropy as they compute. Their findings reveal how neurons dynamically reshape their interactions during behavior and how the brain’s internal “temporal asymmetry” shifts during task engagement, shedding light on how efficient computation arises. The work is published in Nature Communications.

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