Ion Gradient-driven Bifurcations of a Multi-Scale Neuronal Model DOI Creative Commons
Anthony G. Chesebro, Lilianne R. Mujica‐Parodi, Corey Weistuch

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2022, Номер unknown

Опубликована: Окт. 5, 2022

Abstract Metabolic limitations within the brain frequently arise in context of aging and disease. As largest consumers energy brain, ion pumps that maintain neuronal membrane potential are most affected when supply becomes limited. To characterize effects such limitations, we analyze gradients present Larter-Breakspear neural mass model. We show existence locations Neimark-Sacker period-doubling bifurcations sodium, calcium, potassium reversal potentials, demonstrate these form physiologically relevant bounds gradient variability. Within bounds, how depolarization will cause decreased activity. also decreases inter-regional coherence, causing a shift critical point at which coupling occurs thereby inducing loss synchrony between regions. In this way, model captures variability microscale level propagates changes to macroscale congruent with those observed human neuroimaging studies.

Язык: Английский

Biophysical neurons, energy, and synapse controllability: a review DOI
Jun Ma

Journal of Zhejiang University. Science A, Год журнала: 2022, Номер 24(2), С. 109 - 129

Опубликована: Дек. 23, 2022

Язык: Английский

Процитировано

137
Neural heterogeneity controls computations in spiking neural networks DOI Creative Commons
Richard Gast, Sara A. Solla, Ann Kennedy

и другие.

Proceedings of the National Academy of Sciences, Год журнала: 2024, Номер 121(3)

Опубликована: Янв. 10, 2024

The brain is composed of complex networks interacting neurons that express considerable heterogeneity in their physiology and spiking characteristics. How does this neural influence macroscopic dynamics, how might it contribute to computation? In work, we use a mean-field model investigate computation heterogeneous networks, by studying the cell thresholds affects three key computational functions population: gating, encoding, decoding signals. Our results suggest serves different types. inhibitory interneurons, varying degree spike threshold allows them gate propagation signals reciprocally coupled excitatory population. Whereas homogeneous interneurons impose synchronized dynamics narrow dynamic repertoire neurons, act as an offset while preserving neuron function. Spike also controls entrainment properties periodic input, thus affecting temporal gating synaptic inputs. Among increases dimensionality improving network’s capacity perform tasks. Conversely, suffer for function generation, but excel at encoding via multistable regimes. Drawing from these findings, propose intra-cell-type mechanism sculpting local circuits permitting same canonical microcircuit be tuned diverse

Язык: Английский

Процитировано

30
Firing activity in an N-type locally active memristor-based Hodgkin–Huxley circuit DOI
Quan Xu, Yujian Fang,

Chengtao Feng

и другие.

Nonlinear Dynamics, Год журнала: 2024, Номер 112(15), С. 13451 - 13464

Опубликована: Май 18, 2024

Язык: Английский

Процитировано

14
Exact mean-field models for spiking neural networks with adaptation DOI
Liang Chen, Sue Ann Campbell

Journal of Computational Neuroscience, Год журнала: 2022, Номер 50(4), С. 445 - 469

Опубликована: Июль 14, 2022

Язык: Английский

Процитировано

26
Ketosis regulates K+ ion channels, strengthening brain-wide signaling disrupted by age DOI Creative Commons
Helena van Nieuwenhuizen, Anthony G. Chesebro,

Claire Polizu

и другие.

Imaging Neuroscience, Год журнала: 2024, Номер 2, С. 1 - 14

Опубликована: Апрель 23, 2024

Aging is associated with impaired signaling between brain regions when measured using resting-state fMRI. This age-related destabilization and desynchronization of networks reverses itself the switches from metabolizing glucose to ketones. Here, we probe mechanistic basis for these effects. First, confirmed their robustness across measurement modalities two datasets acquired EEG (

Язык: Английский

Процитировано

5
Pulse Shape and Voltage-Dependent Synchronization in Spiking Neuron Networks DOI
Bastian Pietras

Neural Computation, Год журнала: 2024, Номер 36(8), С. 1476 - 1540

Опубликована: Июль 19, 2024

Abstract Pulse-coupled spiking neural networks are a powerful tool to gain mechanistic insights into how neurons self-organize produce coherent collective behavior. These use simple neuron models, such as the θ-neuron or quadratic integrate-and-fire (QIF) neuron, that replicate essential features of real dynamics. Interactions between modeled with infinitely narrow pulses, spikes, rather than more complex dynamics synapses. To make these biologically plausible, it has been proposed they must also account for finite width which can have significant impact on network However, derivation and interpretation pulses contradictory, pulse shape is largely unexplored. Here, I take comprehensive approach coupling in QIF θ-neurons. argue activate voltage-dependent synaptic conductances show implement them their effect last through phase after spike. Using an exact low-dimensional description globally coupled neurons, prove instantaneous interactions oscillations emerge due effective mean voltage. analyze by means family smooth functions arbitrary symmetric asymmetric shapes. For resulting voltage not very synchronizing but slightly skewed spike readily generate oscillations. The results unveil synchronization mechanism at heart emergent behavior, facilitated complementary traditional transmission networks.

Язык: Английский

Процитировано

5
Ion gradient-driven bifurcations of a multi-scale neuronal model DOI Creative Commons
Anthony G. Chesebro, Lilianne R. Mujica‐Parodi, Corey Weistuch

и другие.

Chaos Solitons & Fractals, Год журнала: 2023, Номер 167, С. 113120 - 113120

Опубликована: Янв. 9, 2023

Язык: Английский

Процитировано

10
Low-dimensional model for adaptive networks of spiking neurons DOI
Bastian Pietras, Pau Clusella, Ernest Montbrió

и другие.

Physical review. E, Год журнала: 2025, Номер 111(1)

Опубликована: Янв. 24, 2025

We investigate a large ensemble of quadratic integrate-and-fire neurons with heterogeneous input currents and adaptation variables. Our analysis reveals that, for specific class adaptation, termed spike-frequency the high-dimensional system can be exactly reduced to low-dimensional ordinary differential equations, which describes dynamics three mean-field variables: population's firing rate, mean membrane potential, variable. The resulting rate equations (FREs) uncover key generic feature networks adaptation: Both center width distribution neurons' frequencies are reduced, this largely promotes emergence collective synchronization in network. findings further supported by bifurcation FREs, accurately captures spiking neuron network, including phenomena such as oscillations, bursting, macroscopic chaos.

Язык: Английский

Процитировано

0
Symmetric and asymmetric bursting oscillations in a hybrid van der Pol-Duffing-Rayleigh system DOI
Xindong Ma, Zhao Zhang

Chaos Solitons & Fractals, Год журнала: 2024, Номер 186, С. 115310 - 115310

Опубликована: Июль 26, 2024

Язык: Английский

Процитировано

3
Comparison between an exact and a heuristic neural mass model with second-order synapses DOI Creative Commons
Pau Clusella, Elif Köksal Ersöz, Jordi García‐Ojalvo

и другие.

Biological Cybernetics, Год журнала: 2022, Номер 117(1-2), С. 5 - 19

Опубликована: Дек. 1, 2022

Neural mass models (NMMs) are designed to reproduce the collective dynamics of neuronal populations. A common framework for NMMs assumes heuristically that output firing rate a neural population can be described by static nonlinear transfer function (NMM1). However, recent exact mean-field theory quadratic integrate-and-fire (QIF) neurons challenges this view showing mean is not state but follows two coupled differential equations (NMM2). Here we analyze and compare these descriptions in presence second-order synaptic dynamics. First, derive mathematical equivalence between infinitely slow synapse limit, i.e., show NMM1 an approximation NMM2 regime. Next, evaluate applicability limit context realistic physiological parameter values analyzing with inhibitory or excitatory synapses. We fails important dynamical features model, such as self-sustained oscillations interneuron QIF network. Furthermore, model one, stimulation pyramidal cell induces resonant oscillatory activity whose peak frequency amplitude increase self-coupling gain external input. This may play role enhanced response densely connected networks weak uniform inputs, electric fields produced non-invasive brain stimulation.

Язык: Английский

Процитировано

12