Self-Improvising Memory: A Perspective on Memories as Agential, Dynamically Reinterpreting Cognitive Glue - PubMed
- ️Mon Jan 01 2024
Self-Improvising Memory: A Perspective on Memories as Agential, Dynamically Reinterpreting Cognitive Glue
Michael Levin. Entropy (Basel). 2024.
Abstract
Many studies on memory emphasize the material substrate and mechanisms by which data can be stored and reliably read out. Here, I focus on complementary aspects: the need for agents to dynamically reinterpret and modify memories to suit their ever-changing selves and environment. Using examples from developmental biology, evolution, and synthetic bioengineering, in addition to neuroscience, I propose that a perspective on memory as preserving salience, not fidelity, is applicable to many phenomena on scales from cells to societies. Continuous commitment to creative, adaptive confabulation, from the molecular to the behavioral levels, is the answer to the persistence paradox as it applies to individuals and whole lineages. I also speculate that a substrate-independent, processual view of life and mind suggests that memories, as patterns in the excitable medium of cognitive systems, could be seen as active agents in the sense-making process. I explore a view of life as a diverse set of embodied perspectives-nested agents who interpret each other's and their own past messages and actions as best as they can (polycomputation). This synthesis suggests unifying symmetries across scales and disciplines, which is of relevance to research programs in Diverse Intelligence and the engineering of novel embodied minds.
Keywords: basal cognition; diverse intelligence; learning; memory; morphogenesis.
Conflict of interest statement
The author declares no conflict of interest.
Figures

The temporal slices of a continuous being over time (A) support memories as messages that pass between the temporal slices (Selflets) of that being, analogously to the messages that pass laterally between different beings at a given time (conventional communication) (B). Images used with permission from Jeremy Guay of Peregrine Creative. Note that it is not claimed here that this is the correct way to think about Selves—this schematization focuses on an external (3rd-person) perspective that helps in understanding certain invariants in how biology uses information. This view omits the complementary perspective of the experiential Self (1st-person experience of the persistent flow itself).

Remodeling of a transplanted tail into a limb-like structure in a salamander. Image from [127].

Bowtie architectures feature a low-dimensional compressed medium at the center through which information must come, and active decoding and context-sensitive interpretation on the output. (A) Developmental processing of morphogenetic information. (B) A typical machine learning architecture. Images used with permission from Jeremy Guay of Peregrine Creative.

Cross-section of newt kidney tubule at different ploidy levels. Re-drawn by Jeremy Guay of Peregrine Creative from [142].

Novel forms made by genetically normal plant leaf cells, when prompted by signals from a wasp embryo.

A schematic of how biological systems can adaptively incorporate foreign material (whether evolved or engineered) at every level of organization. Taken from [124]; image by Jeremy Guay of Peregrine Creative.

Schematic representations of bowtie architectures in biochemical, bioelectrical, and biomechanical circuits. For example, causal parameters such as tension or resting voltage potential across the membrane (Vmem), as well as specific genes, can act as information hubs that ensure the compression of signals within biological control networks.
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References
-
- Baluška F., Miller W.B., Reber A.S. Cellular and evolutionary perspectives on organismal cognition: From unicellular to multicellular organisms. Biol. J. Linn. Soc. 2023;139:503–513. doi: 10.1093/biolinnean/blac005. - DOI
Grants and funding
I gratefully acknowledge support via Grant 62212 from the John Templeton Foundation, and of the Air Force Office of Scientific Research (AFOSR) under award number FA9550-22-1-0465, Cognitive & Computational Neuroscience program.
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