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ARXIV:2605.15652 · NEURO-INSPIRED COMPUTING · SUBMITTED 18 MAY · 20:34 UTC · FRESHNESS STALE
ARXIV:2605.15652NEURO-INSPIRED COMPUTINGSUBMITTED 18 MAY · 20:34 UTCFRESHNESS STALEHiroyuki Chuma · Kanji Otsuka · Yoichi Sato · arXiv
A theoretical algebro-deterministic memory architecture inspired by hippocampal function, bridging computational neuroscience and hyperdimensional engineering.
Opportunity summary
Pain A theoretical algebro-deterministic memory architecture inspired by hippocampal function, bridging computational neuroscience and hyperdimensional engineering.
Evidence 0 refs | 3 sources | 50% coverage
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A theoretical algebro-deterministic memory architecture inspired by hippocampal function, bridging computational neuroscience and hyperdimensional engineering. Human iEEG shows that hippocampal sharp-wave ripples (SWRs) gate episodic recall, ripple-locked cortical reactivation recapitulates encoding-time patterns, and multi-hop…
Vector-HaSH and the Tolman-Eichenbaum Machine (TEM) propose that the hippocampal-entorhinal circuit factorizes content from a prestructured grid-cell scaffold and supports compositional memory via ripple-mediated replay. Human iEEG shows that hippocampal sharp-wave ripples (SWRs) gate…
ScienceToStartup currently rates this 1.0/10 on the public viability pass. Vector-HaSH and the Tolman-Eichenbaum Machine (TEM) propose that the hippocampal-entorhinal circuit factorizes content from a prestructured grid-cell scaffold and supports compositional memory via ripple-mediated…
Neuro-Inspired Computing moved forward this cycle; last verified May 2026. Public score 1.0/10.
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A theoretical algebro-deterministic memory architecture inspired by hippocampal function, bridging computational neuroscience and hyperdimensional engineering.
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10.48550/arXiv.2605.15652A theoretical algebro-deterministic memory architecture inspired by hippocampal function, bridging computational neuroscience and hyperdimensional engineering.
Abstract
Vector-HaSH and the Tolman-Eichenbaum Machine (TEM) propose that the hippocampal-entorhinal circuit factorizes content from a prestructured grid-cell scaffold and supports compositional memory via ripple-mediated replay. Human iEEG shows that hippocampal sharp-wave ripples (SWRs) gate episodic recall, ripple-locked cortical reactivation recapitulates encoding-time patterns, and multi-hop replay fidelity decays multiplicatively along sequence length. These literatures have advanced in parallel without a shared algebraic object. We show that VaCoAl, an algebro-deterministic hyperdimensional memory architecture built from Galois-field LFSRs, supplies that object. Specifically, deterministic Galois-field diffusion provides a substrate-level alternative to Vector-HaSH's random scaffold-to-hippocampus projection that satisfies the same quasi-orthogonality requirement, with matched second-moment statistics, stronger avalanche behavior, and bit-exact reproducibility. The path-integral Confidence Ratio $CR_2$, the product of per-step $CR_1$ values along an $n$-hop chain, is the natural functional form for multi-hop replay-fidelity decay under conditional independence of per-step reactivation, providing the first algebraically tractable model of reported multiplicative decay. STDP-like path selection in VaCoAl follows from architectural demands -- similarity preservation, compositional reversibility, and bounded-frontier search -- that also constrain hippocampal computation. We further argue that VaCoAl operating regimes share architectural commitments with the EC--CA3 and EC--DG--CA3 pathways, motivating an energy-capacity-plasticity reading of why both are conserved across $>$520 Myr of evolution and primate dentate-gyrus elaboration. We prove formal correspondences, derive testable iEEG predictions, and bridge computational neuroscience and hyperdimensional engineering.
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PROBLEM
A theoretical algebro-deterministic memory architecture inspired by hippocampal function, bridging computational neuroscience and hyperdimensional engineering. Human iEEG shows that hippocampal sharp-wave ripples (SWRs) gate episodic recall, ripple-locked cortical reactivation r...
METHOD
Vector-HaSH and the Tolman-Eichenbaum Machine (TEM) propose that the hippocampal-entorhinal circuit factorizes content from a prestructured grid-cell scaffold and supports compositional memory via ripple-mediated replay. Human iEEG shows that hippocampal sharp-wave ripples (SWRs...
RESULT
ScienceToStartup currently rates this 1.0/10 on the public viability pass. Vector-HaSH and the Tolman-Eichenbaum Machine (TEM) propose that the hippocampal-entorhinal circuit factorizes content from a prestructured grid-cell scaffold and supports compositional memory via ripple-...
WHY NOW
Neuro-Inspired Computing moved forward this cycle; last verified May 2026. Public score 1.0/10.
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A theoretical algebro-deterministic memory architecture inspired by hippocampal function, bridging computational neuroscience and hyperdimensional engineering. Human iEEG shows that hippocampal sharp-wave ripples (SWRs) gate episodic recall, ripple-locked cortical reactivation recapitulates encoding-time patterns, and multi-hop replay fidelity decays multiplicatively along sequence length.
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partial
Vector-HaSH and the Tolman-Eichenbaum Machine (TEM) propose that the hippocampal-entorhinal circuit factorizes content from a prestructured grid-cell scaffold and supports compositional memory via ripple-mediated replay. Human iEEG shows that hippocampal sharp-wave ripples (SWRs) gate episodic recall, ripple-locked cortical reactivation recapitulates encoding-time patterns, and multi-hop replay fidelity decays multiplicatively along sequence length.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
ScienceToStartup currently rates this 1.0/10 on the public viability pass. Vector-HaSH and the Tolman-Eichenbaum Machine (TEM) propose that the hippocampal-entorhinal circuit factorizes content from a prestructured grid-cell scaffold and supports compositional memory via ripple-mediated replay.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Neuro-Inspired Computing moved forward this cycle; last verified May 2026. Public score 1.0/10.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
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A theoretical algebro-deterministic memory architecture inspired by hippocampal function, bridging computational neuroscience and hyperdimensional engineering.
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