arXiv subjects

Marat M. Rvachev

Publications and source records attributed to Marat M. Rvachev.

6 recordsLinked to original sources

arXiv2026

Surface Waves and Axoplasmic Pressure Waves in Action Potential Propagation: Fundamentally Different Physics or Two Sides of the Same Coin?

In this commentary, we argue that El Hady and Machta's "surface wave" model for mechanical waves accompanying action potential (AP) propagation describes the same underlying process as the "axoplasmic pressure wave" model introduced earlier by Rvachev. Both models describe mechanical modes that store potential energy in the elastic components of the axon (axonal membrane, cytoskeleton, bulk axoplasmic deformation), with kinetic energy carried by the axoplasmic fluid and axoplasmic viscosity playing a significant role. The "surface wave" model quantitatively considers driving by the traveling electrical depolarization wave of the AP, whereas the "axoplasmic pressure wave" model qualitatively considers driving not only by the AP's electrical depolarization but also by other mechanisms, such as cytoskeletal actomyosin contractility. In addition, the "axoplasmic pressure wave" model considers mechanisms for synchronizing the depolarization wave and the pressure wave. Although derived using different approaches, the two models yield identical dependencies for the mechanical modes in key limits. The confusion in the literature, which treats these models as describing distinct processes, needs to be resolved to improve comprehensive understanding of the AP phenomenon and to guide future research.

physics.bio-ph↗

arXiv2025

An Operating Principle of the Cerebral Cortex, and a Cellular Mechanism for Attentional Trial-and-Error Pattern Learning and Useful Classification Extraction

A feature of the brains of intelligent animals is the ability to learn to respond to an ensemble of active neuronal inputs with a behaviorally appropriate ensemble of active neuronal outputs. Previously, a hypothesis was proposed on how this mechanism is implemented at the cellular level within the neocortical pyramidal neuron: the apical tuft or perisomatic inputs initiate "guess" neuron firings, while the basal dendrites identify input patterns based on excited synaptic clusters, with the cluster excitation strength adjusted based on reward feedback. This simple mechanism allows neurons to learn to classify their inputs in a surprisingly intelligent manner. Here, we revise and extend this hypothesis. We modify synaptic plasticity rules to align with behavioral time scale synaptic plasticity (BTSP) observed in hippocampal area CA1, making the framework more biophysically and behaviorally plausible. The neurons for the guess firings are selected in a voluntary manner via feedback connections to apical tufts in the neocortical layer 1, leading to dendritic Ca2+ spikes with burst firing, which are postulated to be neural correlates of attentional, aware processing. Once learned, the neuronal input classification is executed without voluntary or conscious control, enabling hierarchical incremental learning of classifications that is effective in our inherently classifiable world. In addition to voluntary, we propose that pyramidal neuron burst firing can be involuntary, also initiated via apical tuft inputs, drawing attention towards important cues such as novelty and noxious stimuli. We classify the excitations of neocortical pyramidal neurons into four categories based on their excitation pathway: attentional versus automatic and voluntary/acquired versus involuntary. Additionally, we hypothesize that dendrites within pyramidal neuron minicolumn bundles are coupled via depolarization...

q-bio.NC↗

arXiv2017

Neuron as a reward-modulated combinatorial switch and a model of learning behavior

This paper proposes a neuronal circuitry layout and synaptic plasticity principles that allow the (pyramidal) neuron to act as a "combinatorial switch". Namely, the neuron learns to be more prone to generate spikes given those combinations of firing input neurons for which a previous spiking of the neuron had been followed by a positive global reward signal. The reward signal may be mediated by certain modulatory hormones or neurotransmitters, e.g., the dopamine. More generally, a trial-and-error learning paradigm is suggested in which a global reward signal triggers long-term enhancement or weakening of a neuron's spiking response to the preceding neuronal input firing pattern. Thus, rewards provide a feedback pathway that informs neurons whether their spiking was beneficial or detrimental for a particular input combination. The neuron's ability to discern specific combinations of firing input neurons is achieved through a random or predetermined spatial distribution of input synapses on dendrites that creates synaptic clusters that represent various permutations of input neurons. The corresponding dendritic segments, or the enclosed individual spines, are capable of being particularly excited, due to local sigmoidal thresholding involving voltage-gated channel conductances, if the segment's excitatory and absence of inhibitory inputs are temporally coincident. Such nonlinear excitation corresponds to a particular firing combination of input neurons, and it is posited that the excitation strength encodes the combinatorial memory and is regulated by long-term plasticity mechanisms. It is also suggested that the spine calcium influx that may result from the spatiotemporal synaptic input coincidence may cause the spine head actin filaments to undergo mechanical (muscle-like) contraction, with the ensuing cytoskeletal deformation transmitted to the axon initial segment where it may...

physics.bio-ph↗

arXiv2010

On axoplasmic pressure waves and their possible role in nerve impulse propagation

It is suggested that the propagation of the action potential is accompanied by an axoplasmic pressure pulse propagating in the axoplasm along the axon length. The pressure pulse stretch-modulates voltage-gated Na (Nav) channels embedded in the axon membrane, causing their accelerated activation and inactivation and increasing peak channel conductance. As a result, the action potential propagates due to mechano-electrical activation of Nav channels by straggling ionic currents and the axoplasmic pressure pulse. The velocity of such propagation is higher than in the classical purely electrical Nav activation mechanism, and it may be close to the velocity of propagation of pressure pulses in the axoplasm. Extracellular Ca ions influxing during the voltage spike, or Ca ions released from intracellular stores, may trigger a mechanism that generates and augments the pressure pulse, thus opposing its viscous decay. The model can potentially explain a number of phenomena that are not contained within the purely electrical Hodgkin-Huxley-type framework: the Meyer-Overton rule for the effectiveness of anesthetics, as well as various mechanical, optical and thermodynamic phenomena accompanying the action potential. It is shown that the velocity of propagation of axoplasmic pressure pulses is close to the measured velocity of the nerve impulse, both in absolute magnitude and in dependence on axon diameter, degree of myelination and temperature.

physics.bio-ph↗

arXiv2009

Action potential as a pressure pulse propagating in the axoplasm

We suggest that the propagation of the action potential is driven by a pressure pulse propagating in the axoplasm along the axon length. The pressure pulse mechanically activates Na ion channels embedded in the axon membrane. This activation initiates the development of a local membrane voltage spike, as in the Hodgkin-Huxley model of the action potential. Extracellular Ca ions influxing during the voltage spike trigger a mechanism that amplifies the pressure pulse and therefore prevents its viscous decay. The model is able to explain a number of phenomena that are unexplained within the Hodgkin-Huxley framework: the Meyer-Overton rule for the effectiveness of anesthetics, as well as various mechanical, optical and thermodynamic phenomena accompanying the action potential. The model correctly predicts the velocity of propagation of the nerve impulse, including its dependence on axon diameter, degree of myelination and temperature.

physics.bio-ph↗

arXiv2003

Alternative model of propagation of spikes along neurons

Here a viable and never before investigated mechanism of propagation of spikes along neurons is proposed. In the following, velocity of propagation of small-amplitude pressure waves through the cytoplasmic interior of myelinated and unmyelinated axons of different diameters is theoretically estimated, and is found to generally agree with the action potential (AP) conduction velocities. This remarkable coincidence allows to surmise a model in which AP spread along axon is propelled not by straggling ionic currents as in the widely accepted local circuit theory, but by mechanoactivation of the membrane ion channels by a traveling pressure pulse. Hydraulic pulses propagating in the viscous axoplasm are calculated to decay over $\sim$ 1 mm distances, and it is further hypothesized that it is the role of influxing during the AP Ca$^{2+}$ ions to activate the membrane skeletal protein network for a brief radial contraction amplifying the pressure pulse and preventing its decay. The model correctly predicts that the AP conduction velocity should vary as the one-half power of axon diameter for large unmyelinated axons, and as the first power of the diameter for myelinated axons, provided that specific mechanical properties of axons are independent from diameter; that myelinization increases the conduction velocity; that the conduction velocity increases with the temperature. Unlike the local circuit theory, the model is able to qualitatively explain observed increase in the AP duration in axons of smaller diameters. Predictions of...

physics.bio-ph↗