Distributional invariance and proportional scaling in axonal conduction \ Laurie D. Cohen and Shimon Marom \ bioRxiv (2025): Conduction velocity along axons depends on geometric and biophysical factors whose collective statistical organization has remained unexplored. Using high-resolution time-of-arrival measurements along hundreds of identified cortical axonal branches, we quantified how propagation speed changes along trajectories.
Dynamics of Excitability in Axonal Trees \ Laurie D. Cohen, Tamar Galateanu Tamar, Shimon Marom \ Biophysical Journal (2026): We report that axons of cortical neurons, structurally intricate excitable media, maintain somatic spike timing with high fidelity during spontaneous network activity, even at short (2–3 msec) inter-spike intervals. However, long series of external stimulation at physiological frequencies expose a vulnerability that varies depending on distance and branching.
A biophysical perspective on the resilience of neuronal excitability across timescales \ Marom, Marder \ Nature Rev. Neurosci. (2023): Neuronal membrane excitability must be resilient to perturbations that can take place over timescales from milliseconds to months (or even years in long-lived animals). This paper offers a self-regulating ‘automatic’ mechanism that contributes to neuronal resilience by virtue of the kinetic properties of ion channels themselves.
Sodium channel slow inactivation normalizes firing in axons with uneven conductance distributions \ Zang, Marder, Marom \ Current Biology (2023): Here we model spike propagation in axons with uneven distributions of Na+ and K+ channels. Including slow inactivation of the Na+ channel enhances the reliability of spike propagation and can compensate for uneven channel distributions.
Dynamic clamp constructed phase diagram for the Hodgkin and Huxley model of excitability \ Ori, Hazan, Marder, Marom \ PNAS (2020): Here we study the relationship between sodium and potas- sium channel parameters and membrane excitability. We used the dynamic clamp, and established a real-time closed-loop interaction between a genetically controlled population of excitability-relevant ion channels and a low-dimensional mathematical description of excitability. The results provide insights into how robustness of excitability benefits from the variability of history-dependent time scales that ion channels display.
Emergence and maintenance of excitability: kinetics over structure \ Marom \ Current Opinion in Neurobiology (2016): Alongside studies that extend traditional focus on control-based regulation of structural parameters (channel densities), there is a budding interest in self-organization of kinetic parameters. In this picture, ionic channels are continually forced by activity in-and-out of a pool of states not available for the mechanism of excitability. The process, acting on expressed structure, provides a bed for generation of a spectrum of excitability modes.
Cellular function given parametric variation in the Hodgkin and Huxley model of excitability \ Ori, Marder, Marom \ PNAS (2018): A theoretical study, showing that although the full Hodgkin–Huxley model is very sensitive to fluctuations that independently occur in its many parameters, the outcome is in fact determined by a simple combinations of these parameters along two physiological dimensions - structural and kinetic (denoted S and K, respectively). The impacts of parametric fluctuations on the dynamics of the system — seemingly complex in the high-dimensional representation of the Hodgkin–Huxley model — are tractable when examined within the S–K plane.
Entrainment of the intrinsic dynamics of single isolated neurons by natural-like input \ Gal, Marom \ J Neurosci. (2013): Neuronal dynamics is intrinsically unstable, producing activity fluctuations that are essentially scale free. Here we experimentally study single cortical neurons, and show that while these scale-free fluctuations are independent of temporal input statistics, they can be entrained by input variation. Response entrainment was found to be maximal when the input itself possesses natural-like, scale-free statistics.
Neural timescales or lack thereof \ Marom \ Prog. Neurobiol. (2010): This article aims at making readers, experimentalists and theorists, more aware of the abstractions made by an observer when measuring and reporting behavioral and neural timescales. These abstractions stow away the fact that, above lower boundaries that reflect fairly well understood physical constraints, observed and reported timescales are often not intrinsic to the biological system; rather, in most cases they reflect conditions that are imposed by the observer through the measuring procedure.
Self-organized criticality in single-neuron excitability \ Gal, Marom \ Phys. Rev. E (2013): Here, we suggest that neuronal response fluctuations reflect a process that positions the neuron near a transition point that separates excitable and unexcitable phases. This view is supported by the dynamical properties of the system as observed in experiments on isolated cultured cortical neurons, and by a theoretical mapping between the constructs of self-organized criticality and membrane excitability.
Interaction between duration of activity and time course of recovery from slow inactivation in mammalian brain Na+ channels \ Toib, Lyakhov, Marom \ J. Neurosci. (1998): The relationships between activity and availability for activation of voltage gated Na channels were examined using the Xenopus expression system. The main point of this work is that the time constant of recovery from the unavailable (inactivated) pool is related to the duration of previous activation by a power law. These relationships extend from tens of milliseconds to several minutes and are intrinsic to the channel protein.
Adaptive transition rates in excitable membranes \ Marom \ Frontiers Comp. Neurosci. (2009): This study shows that adaptation in excitable membranes is reducible to a simple Logistic-like equation in which the essential non-linearity is replaced by a feedback loop between the history of activation and an adaptive transition rate that is sensitive to a single dimension of the space of inactive states. This physiologically measurable dimension contributes to the stability of the system and serves as a powerful, intrinsic modulator of input–output relations that depends on the patterns of prior activity.
Modeling State-Dependent Inactivation of Membrane Currents \ Marom, Abbott \ Biophysical J. (1994): Inactivation of many ion channels occurs through largely voltage-independent traitions to an inactivated state from the open state or from other states in the pathway leaing to opening of the chanel. Because this form of inactvation is state-dependent rather than voltage-dendent, it cannot be described by the standard Hodgkin-Huxley (HH) formalism. Using two examples ,we extend the standad HH formalism for modeling macroscopic currents to account for state-dependent inacvation.
A 3-D approach to voltage-clamp data \ Marom \ J Theoreticl Biology (1992): This very early paper, which I am most proud of, was never cited, by no-one... It presents a simple transition from 2-D handling of voltage clamp data, to 3-D, thus uncovering some stimulating relationships between the graphic representation of the I–V–t space of electrical activity of the membrane, and the physiological and biophysical functions of the plotted ionic currents.