Article
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Preserved in Portico This version is not peer-reviewed
The Mechanical Basis of Memory - the MeshCODE Theory
Version 1
: Received: 6 May 2020 / Approved: 7 May 2020 / Online: 7 May 2020 (10:16:49 CEST)
Version 2 : Received: 21 October 2020 / Approved: 22 October 2020 / Online: 22 October 2020 (05:40:50 CEST)
Version 2 : Received: 21 October 2020 / Approved: 22 October 2020 / Online: 22 October 2020 (05:40:50 CEST)
A peer-reviewed article of this Preprint also exists.
GoultBT (2021) The MechanicalBasis of Memory – the MeshCODETheory.Front. Mol. Neurosci. 14:592951 GoultBT (2021) The MechanicalBasis of Memory – the MeshCODETheory.Front. Mol. Neurosci. 14:592951
Abstract
One of the major unsolved mysteries of biological science concerns the question of where and in what form information is stored in the brain. I propose that memory is stored in the brain in a mechanically encoded binary format written into the conformations of proteins found in the cell-extracellular matrix adhesions that organise each and every synapse. The MeshCODE framework outlined here represents a unifying theory of data storage in animals, providing read-write storage of both dynamic and persistent information in a binary format. Mechanosensitive proteins that contain force-dependent switches can store information persistently, which can be written or updated using small changes in mechanical force. These mechanosensitive proteins, such as talin, scaffold each synapse, creating a meshwork of switches that together form a code, the so-called MeshCODE. Large signalling complexes assemble on these scaffolds as a function of the switch patterns and these complexes would both stabilise the patterns and coordinate synaptic regulators to dynamically tune synaptic activity. Synaptic transmission and action potential spike trains would operate the cytoskeletal machinery to write and update the synaptic MeshCODEs, thereby propagating this coding throughout the organism. Based on established biophysical principles, such a mechanical basis for memory would provide a physical location for data storage in the brain, with the binary patterns, encoded in the information-storing mechanosensitive molecules in the synaptic scaffolds, and the complexes that form on them, representing the physical location of engrams. Furthermore, the conversion and storage of sensory and temporal inputs into a binary format would constitute an addressable read-write memory system, supporting the view of the mind as an organic supercomputer.
Keywords
Memory; talin; mechanobiology; information-processing; MeshCODE; brain; neuroscience; integrin; learning; cytoskeleton; REM sleep; vinculin; actin
Subject
Biology and Life Sciences, Biochemistry and Molecular Biology
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Commenter: Ben Goult
Commenter's Conflict of Interests: Author
The key to any code is a read-out mechanism and the mechanical code outlined here leads to a number of hypotheses for how such a coding in the brain would be read. This new section discusses how MeshCODE driven adhesion signalling might work in the context of a neuron, with the purpose being to demonstrate the feasibility and broad applicability of the theory to well-established neuronal processes.