Work

Learning via Mechanosensitivity and Activity in Cytoskeletal Networks

Year: 2025

Type: article

Abstract: In this work we show how a network inspired by a coarse-grained description of the cytoskeleton can learn—in a contrastive learning framework—from environmental perturbations if it is endowed with mechanosensitive proteins and motors. Our work is a proof of principle for how force-sensitive proteins and molecular motors can form the basis of a general strategy to learn in biological systems without neurons. Our work identifies a minimal biologically plausible learning mechanism and also explores its implications for commonly occurring phenomenology, such as adaptation and homeostasis.

Source: PRX Life

DOI: 10.1103/s7tg-6q4q

Authors: Deb S. Banerjee, Martin J. Falk, Margaret L. Gardel, Aleksandra M. Walczak, Thierry Mora, Suriyanarayanan Vaikuntanathan