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We introduce frequency propagation, a learning algorithm for nonlinear physical networks. In a resistive electrical circuit with variable resistors, an activation current is applied at a set of input nodes at one frequency and an error current is applied at a set of output nodes at another frequency. The voltage response of the circuit to these boundary currents is the superposition of an activation signal and an error signal whose coefficients can be read in different frequencies of the frequency domain. Each conductance is updated proportionally to the product of the two coefficients. The learning rule is local and proved to perform gradient descent on a loss function. We argue that frequency propagation is an instance of a multimechanism learning strategy for physical networks, be it resistive, elastic, or flow networks. Multimechanism learning strategies incorporate at least two physical quantities, potentially governed by independent physical mechanisms, to act as activation and error signals in the training process. Locally available information about these two signals is then used to update the trainable parameters to perform gradient descent. We demonstrate how earlier work implementing learning via chemical signaling in flow networks (Anisetti, Scellier, et al., 2023) also falls under the rubric of multimechanism learning.

We present analysis of neuronal activity recordings from a subset of neurons in the medial prefrontal cortex of rats before and after the administration of cocaine. Using an underlying modern Hopfield model as a description for the neuronal network, combined with a machine learning approach, we compute the underlying functional connectivity of the neuronal network. We find that the functional connectivity changes after the administration of cocaine with both functional-excitatory and functional-inhibitory neurons being affected. Using conventional network analysis, we find that the diameter of the graph, or the shortest length between the two most distant nodes, increases with cocaine, suggesting that the neuronal network is less robust. We also find that the betweenness centrality scores for several of the functional-excitatory and functional-inhibitory neurons decrease significantly, while other scores remain essentially unchanged, to also suggest that the neuronal network is less robust. Finally, we study the distribution of neuronal activity and relate it to energy to find that cocaine drives the neuronal network towards destabilization in the energy landscape of neuronal activation. While this destabilization is presumably temporary given one administration of cocaine, perhaps this initial destabilization indicates a transition towards a new stable state with repeated cocaine administration. However, such analyses are useful more generally to understand how neuronal networks respond to perturbations.

The microtubule cytoskeleton is a major structural element inside cells that directs self‐organization using microtubule‐associated proteins and motors. It has been shown that finite‐sized, spindle‐like microtubule organizations, called “tactoids,” can form in vitro spontaneously from mixtures of tubulin and the antiparallel crosslinker, MAP65, from the MAP65/PRC1/Ase family. Here, we probe the ability of MAP65 to form tactoids as a function of the ionic strength of the buffer to attempt to break the electrostatic interactions binding MAP65 to microtubules and inter‐MAP65 binding. We observe that, with increasing monovalent salts, the organizations change from finite tactoids to unbounded length bundles, yet the MAP65 binding and crosslinking appear to stay intact. We further explore the effects of ionic strength on the dissociation constant of MAP65 using both microtubule pelleting and single‐molecule binding assays. We find that salt can reduce the binding, yet salt never negates it. Instead, we believe that the salt is affecting the ability of the MAP65 to form phase‐separated droplets, which cause the nucleation and growth of tactoids, as recently demonstrated.

Chromatin is an essential component of nuclear mechanical response and shape that maintains nuclear compartmentalization and function. However, major genomic functions, such as transcription activity, might also impact cell nuclear shape via blebbing and rupture through their effects on chromatin structure and dynamics. To test this idea, we inhibited transcription with several RNA polymerase II inhibitors in wild type cells and perturbed cells that present increased nuclear blebbing. Transcription inhibition suppresses nuclear blebbing for several cell types, nuclear perturbations, and transcription inhibitors. Furthermore, transcription inhibition suppresses nuclear bleb formation, bleb stabilization, and bleb-based nuclear ruptures. Interestingly, transcription inhibition does not alter either H3K9 histone modification state, nuclear rigidity, or actin compression and contraction, which typically control nuclear blebbing. Polymer simulations suggest that RNA pol II motor activity within chromatin could drive chromatin motions that deform the nuclear periphery. Our data provide evidence that transcription inhibition suppresses nuclear blebbing and rupture, separate and distinct from chromatin rigidity.