The physical basis of information flow in neural matter: a thermocoherent perspective on cognitive dynamics

Abstract

Information flow is central to contemporary accounts of cognition, yet its physical basis in living neural matter remains poorly specified. Here, we develop a multiscale resource-theoretical framework motivated by the \textit{thermocoherent effect}, where heat flow is reciprocally coupled to a delocalized information flow carried by shared coherence and not reducible to local subsystem variables. Extending this line of work in light of recent results on correlation-enabled Mpemba-type thermal relaxation, we argue that the operational relevance of correlations depends less on their taxonomy than on their dynamical accessibility under the underlying interaction geometry. Relational structure encoded in the state of a single composite system -- including quantum entanglement, quantum discord, and classical correlations -- may therefore act as a usable physical resource that remains hidden from local subsystem descriptions. We propose that electrical, chemical, ionic, and thermal transport processes in neural matter may, under suitable microscopic conditions, generate or transduce partially hidden relational resources whose mutual coupling can progressively build larger-scale thermocoherent organization across spatial or spatiotemporal partitions in neural tissue. Ion-channel interfaces, hydrogen-bonded proton networks, aromatic $π$-electron architectures, and phosphate-rich motifs emerge as plausible substrate classes in which such resources may arise, become transiently accessible under environmental coupling, and leave coarse-grained signatures in neural dynamics. The resulting picture is neither a claim of macroscopic quantum cognition nor a reduction of cognition to abstract coding, but a falsifiable framework in which microscopic relational resources can bias transport, relaxation, signaling, and cross-scale neural coordination.

Figures (4)

• Figure 1: A schematic illustration of a carrier-based local picture of information flow. In this conventional view, the flow of information is identified with the motion or transduction of locally encoded physical carriers (here represented by binary occupancy and color-coded local states). This intuition is often useful at coarse-grained levels, but it does not exhaust the physically relevant possibilities in nonequilibrium composite systems, where information can instead be stored or transferred in relational structure not reducible to any single local current.
• Figure 2: Schematic illustration of a delocalized information flow in a nonequilibrium three-subsystem setting. Relational support is redistributed across subsystem partitions during relaxation, alongside an accompanying heat current $J_{\mathrm{heat}}$ and thermal gradient. The subsystem colors indicate local temperatures, while the superscript $\mathrm{corr}=\{\mathrm{cc},\mathrm{qd},\mathrm{qe}\}$ denotes the pairwise relational structure. The parameter $\theta$ takes the values $\chi$, $\lambda$, and $\mu$, respectively.
• Figure 3: Schematic summary of three substrate-independent operational motifs by which hidden relational structure may become dynamically consequential in biological or neural matter. (a) A classically driven conformational or geometric reconfiguration (Conf$_1 \to$ Conf$_2$) can alter which relational sectors of a composite system become dynamically accessible under the effective interaction geometry, allowing hidden relational support to be redistributed across new subsystem partitions. (b) A short-lived quantum contribution associated with the entanglement-linked sector $\Delta_\mu$ need not remain long-lived to be functionally relevant: near a transition region or reaction bottleneck, transiently accessible quantum structure can be converted into a more robust classically correlated residue $\Delta_\chi$, leaving a persistent relational bias after the underlying quantum correlations have decohered. (c) Two preparations with comparable coarse-grained local membrane descriptors can nonetheless exhibit distinct membrane-potential recovery trajectories if they differ in hidden relational structure; schematically, a relational contribution $\theta$ that becomes dynamically consequential near the resetting transition can alter the ordering or timing of repolarization, in analogy with correlation-enabled Mpemba-type relaxation. This panel is intended as a coarse-grained operational motif rather than a literal electrophysiological model. Together, the three panels highlight a central theme of the present framework: biologically relevant hidden relational resources need not rely on long-lived coherence alone, but may also emerge through classical reconfiguration, transient quantum-to-classical transduction, and altered relaxation or resetting order at the coarse-grained level.
• Figure 4: Schematic illustration of coupled transport processes in neural matter and their possible multiscale reorganization. Electrical, chemical, ionic, thermal, and correlation flows may generate, transduce, or redistribute hidden relational structure across suitable microscopic substrates. Such substrate-level contributions -- including coupled proton/electron delocalization, aromatic $\pi$-architectures, and geometry-dependent buffering motifs -- may then coarse-grain into larger-scale thermocoherent organization across neural tissue.