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Dynamical balance of excitation and inhibition is usually invoked to explain the irregular low firing activity observed in the cortex. We propose a robust nonlinear balancing mechanism for a random network of spiking neurons, which works…

无序系统与神经网络 · 物理学 2025-05-29 Antonio Politi , Alessandro Torcini

We study the spike statistics of neurons in a network with dynamically balanced excitation and inhibition. Our model, intended to represent a generic cortical column, comprises randomly connected excitatory and inhibitory leaky…

神经元与认知 · 定量生物学 2007-05-23 Alexander Lerchner , Cristina Ursta , John Hertz , Mandana Ahmadi , Pauline Ruffiot

Many biological neuronal networks exhibit highly variable spiking activity. Balanced networks offer a parsimonious model of this variability. In balanced networks, strong excitatory synaptic inputs are canceled by strong inhibitory inputs…

神经元与认知 · 定量生物学 2016-05-04 Ryan Pyle , Robert Rosenbaum

Large sparse circuits of spiking neurons exhibit a balanced state of highly irregular activity under a wide range of conditions. It occurs likewise in sparsely connected random networks that receive excitatory external inputs and recurrent…

神经元与认知 · 定量生物学 2013-08-16 Sven Jahnke , Raoul-Martin Memmesheimer , Marc Timme

Strong inhibitory input to neurons, which occurs in balanced states of neural networks, increases synaptic current fluctuations. This has led to the assumption that inhibition contributes to the high spike-firing irregularity observed in…

神经元与认知 · 定量生物学 2021-02-19 Tomas Barta , Lubomir Kostal

Networks of model neurons with balanced recurrent excitation and inhibition produce irregular and asynchronous spiking activity. We extend the analysis of balanced networks to include the known dependence of connection probability on the…

神经元与认知 · 定量生物学 2014-06-02 Robert Rosenbaum , Brent Doiron

The background activity of a cortical neural network is modeled by a homogeneous integrate-and-fire network with unreliable inhibitory synapses. Numerical and analytical calculations show that the network relaxes into a stationary state of…

无序系统与神经网络 · 物理学 2007-05-23 Wolfgang Kinzel

How the information microscopically processed by individual neurons is integrated and used in organizing the behavior of an animal is a central question in neuroscience. The coherence of neuronal dynamics over different scales has been…

无序系统与神经网络 · 物理学 2020-03-11 Takashi Hayakawa , Tomoki Fukai

The study of balanced networks of excitatory and inhibitory neurons has led to several open questions. On the one hand it is yet unclear whether the asynchronous state observed in the brain is autonomously generated, or if it results from…

神经元与认知 · 定量生物学 2016-09-22 Rodrigo Echeveste , Claudius Gros

Recurrent neural networks with balanced excitation and inhibition exhibit irregular asynchronous dynamics, which is fundamental for cortical computations. Classical balance mechanisms require strong external inputs to sustain finite firing…

神经元与认知 · 定量生物学 2025-10-21 David Angulo-Garcia , Alessandro Torcini

Measured responses from visual cortical neurons show that spike times tend to be correlated rather than exactly Poisson distributed. Fano factors vary and are usually greater than 1 due to the tendency of spikes being clustered into bursts.…

神经元与认知 · 定量生物学 2007-05-23 Alexander Lerchner , Mandana Ahmadi , John Hertz

We revisit the dynamics of a prototypical model of balanced activity in networks of spiking neutrons. A detailed investigation of the thermodynamic limit for fixed density of connections (massive coupling) shows that, when inhibition…

适应与自组织系统 · 物理学 2018-09-03 Ekkehard Ullner , Antonio Politi , Alessandro Torcini

Networks of excitatory and inhibitory neurons display asynchronous irregular (AI) states, where the activities of the two populations are balanced. At the single cell level, it was shown that neurons subject to balanced and noisy synaptic…

神经元与认知 · 定量生物学 2016-11-29 Zahara Girones , Alain Destexhe

Large networks of sparsely coupled, excitatory and inhibitory cells occur throughout the brain. A striking feature of these networks is that they are chaotic. How does this chaos manifest in the neural code? Specifically, how variable are…

神经元与认知 · 定量生物学 2014-02-25 Guillaume Lajoie , Jean-Philippe Thivierge , Eric Shea-Brown

Neurons and networks in the cerebral cortex must operate reliably despite multiple sources of noise. To evaluate the impact of both input and output noise, we determine the robustness of single-neuron stimulus selective responses, as well…

神经元与认知 · 定量生物学 2018-01-24 Ran Rubin , L. F. Abbott , Haim Sompolinsky

The balance between excitation and inhibition is crucial for neuronal computation. It is observed that the balanced state of neuronal networks exists in many experiments, yet its underlying mechanism remains to be fully clarified.…

神经元与认知 · 定量生物学 2017-10-17 Qing-long L. Gu , Songting Li , Wei P. Dai , Douglas Zhou , David Cai

The theory of Balanced Neural Networks is a very popular explanation for the high degree of variability and stochasticity in the brain's activity. Roughly speaking, it entails that typical neurons receive many excitatory and inhibitory…

概率论 · 数学 2025-05-27 James MacLaurin , Pedro Vilanova

Distributions of neuronal activity within cortical circuits are often found to display highly skewed shapes with many neurons emitting action potentials at low or vanishing rates, while some are active at high rates. Theoretical studies…

神经元与认知 · 定量生物学 2024-12-20 Alexander Schmidt , Peter Hiemeyer , Fred Wolf

There is consensus in the current literature that stable states of asynchronous irregular spiking activity require (i) large networks of 10 000 or more neurons and (ii) external background activity or pacemaker neurons. Yet already in 1963,…

神经元与认知 · 定量生物学 2013-11-07 Marc-Oliver Gewaltig

Dynamic excitatory-inhibitory (E-I) balance is a paradigmatic mechanism invoked to explain the irregular low firing activity observed in the cortex. However, we will show that the E-I balance can be at the origin of other regimes observable…

神经元与认知 · 定量生物学 2023-11-13 Hongjie Bi , Matteo Di Volo , Alessandro Torcini
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