arXiv — NLP / Computation & Language · · 3 min read

From Observation to Intervention: Memory in Brains and Large Language Models

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Quantitative Biology > Neurons and Cognition

arXiv:2608.12377 (q-bio)
[Submitted on 27 Jul 2026]

Title:From Observation to Intervention: Memory in Brains and Large Language Models

View a PDF of the paper titled From Observation to Intervention: Memory in Brains and Large Language Models, by Morteza Salehjahromi and 3 other authors
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Abstract:Brains and large language models (LLMs) are fundamentally different memory systems, but they can be compared through shared functional questions: where memory-related information is represented, how partial cues recover broader associations, how new information is written or updated, and how memory-related states can be perturbed. In biological systems, these questions span synapses, neuronal ensembles, hippocampal-cortical interactions, and plasticity; in LLMs, they span weights, activations, context windows, retrieval systems, and external stores. The comparison is therefore functional and experimental rather than anatomical. Human studies reveal sparse concept responses, temporal binding, rapid association formation, episode-specific coding, and recall-related reactivation, but selective intervention remains limited. Rodent studies provide more selective causal access to learning-related ensembles, whereas human and macaque interventions usually affect broader circuits. LLMs lack lived episodic memory, yet they permit unusually direct and repeatable manipulation of internal states and stored information. We argue that this asymmetry creates a new opportunity. LLMs are not ahead in memory itself, but in experimental access. Their tools may help turn broad questions about retrieval, updating, persistence, reversibility, and unintended effects into sharper biological hypotheses. The productive bridge is to transfer experimental logic, not anatomical parts.
Comments: Perspective article, 11 pages, 3 figures, 1 table, and 1 key terms box. Submitted for consideration to Nature Machine Intelligence
Subjects: Neurons and Cognition (q-bio.NC); Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
Cite as: arXiv:2608.12377 [q-bio.NC]
  (or arXiv:2608.12377v1 [q-bio.NC] for this version)
  https://doi.org/10.48550/arXiv.2608.12377
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Amgad Muneer [view email]
[v1] Mon, 27 Jul 2026 16:45:00 UTC (744 KB)
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