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We study analytically the dynamics of a network of sparsely connected inhibitory integrate-and-fire neurons in a regime where individual neurons emit spikes irregularly and at a low rate. In the limit when the number of neurons N tends to…

Disordered Systems and Neural Networks · Physics 2007-05-23 N. Brunel , V. Hakim

We studied neural automata -or neurobiologically inspired cellular automata- which exhibits chaotic itinerancy among the different stored patterns or memories. This is a consequence of activity-dependent synaptic fluctuations, which…

Neurons and Cognition · Quantitative Biology 2007-05-23 J. M. Cortes , J. Marro , J. J. Torres

Recent physiological measurements have provided clear evidence about scale-free avalanche brain activity and EEG spectra, feeding the classical enigma of how such a chaotic system can ever learn or respond in a controlled and reproducible…

Neurons and Cognition · Quantitative Biology 2015-05-18 Lucilla de Arcangelis , Hans J. Herrmann

Variability in neural responses is an ubiquitous phenomenon in neurons, usually modeled with stochastic differential equations. In particular, stochastic integrate-and-fire models are widely used to simplify theoretical studies. The…

Neurons and Cognition · Quantitative Biology 2009-06-12 Eugenio Urdapilleta , Ines Samengo

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…

Neurons and Cognition · Quantitative Biology 2016-05-04 Ryan Pyle , Robert Rosenbaum

The human cortex is never at rest but in a state of sparse and noisy neural activity that can be detected at broadly diverse resolution scales. It has been conjectured that such a state is best described as a critical dynamical process --…

Statistical Mechanics · Physics 2021-06-30 Victor Buendía , Pablo Villegas , Raffaella Burioni , Miguel A. Muñoz

Author summary: Synchronization of neuronal spiking in the brain is related to cognitive functions, such as perception, attention, and memory. It is therefore important to determine which properties of neurons influence their collective…

Neurons and Cognition · Quantitative Biology 2013-11-06 Josef Ladenbauer , Moritz Augustin , LieJune Shiau , Klaus Obermayer

We extensively explore networks of weakly unbalanced, leaky integrate-and-fire (LIF) neurons for different coupling strength, connectivity, and by varying the degree of refractoriness, as well as the delay in the spike transmission. We find…

Neurons and Cognition · Quantitative Biology 2018-12-14 Antonio Politi , Ekkehard Ullner , Alessandro Torcini

We investigated the influence of efficacy of synaptic interaction on firing synchronization in excitatory neuronal networks. We found spike death phenomena, namely, the state of neurons transits from limit cycle to fixed point or transient…

Disordered Systems and Neural Networks · Physics 2009-11-13 Sheng-Jun Wang , Xin-Jian Xu , Zhi-Xi Wu , Zi-Gang Huang , Ying-Hai Wang

A massively recurrent neural network responds on one side to input stimuli and is autonomously active, on the other side, in the absence of sensory inputs. Stimuli and information processing depends crucially on the qualia of the…

Disordered Systems and Neural Networks · Physics 2012-02-01 Dimitrije Markovic , Claudius Gros

Epilepsy is a common neurological disorder characterized by abrupt seizures. Although seizures may appear random, they are often preceded by early warning signs in neural signals, notably, critical slowing down, a phenomenon in which the…

Systems and Control · Electrical Eng. & Systems 2024-11-12 Yuzhen Qin , Marcel van Gerven

Spiking neural networks drawing inspiration from biological constraints of the brain promise an energy-efficient paradigm for artificial intelligence. However, challenges exist in identifying guiding principles to train these networks in a…

Neural and Evolutionary Computing · Computer Science 2024-04-25 Joseph A. Kilgore , Jeffrey D. Kopsick , Giorgio A. Ascoli , Gina C. Adam

Superintelligence is commonly envisioned as a quantitative extrapolation of human cognitive abilities driven by scale and computational power. Here we show that qualitative transitions in intelligence instead arise as dynamical phase…

Biological Physics · Physics 2026-02-10 Byung Gyu Chae

We investigate a mean-field model of interacting synapses on a directed neural network. Our interest lies in the slow adaptive dynamics of synapses, which are driven by the fast dynamics of the neurons they connect. Cooperation is modelled…

Disordered Systems and Neural Networks · Physics 2014-10-01 J. M. Luck , A. Mehta

Neural systems process information in a dynamical regime between silence and chaotic dynamics. This has lead to the criticality hypothesis which suggests that neural systems reach such a state by self-organizing towards the critical point…

Disordered Systems and Neural Networks · Physics 2021-03-10 Stefan Landmann , Lorenz Baumgarten , Stefan Bornholdt

The relation between spontaneous and stimulated brain activity is a fundamental question in neuroscience, which has received wide attention in experimental studies. Recently, it has been suggested that the evoked response to external…

Disordered Systems and Neural Networks · Physics 2023-06-16 M. K. Nandi , A. De Candia , A. Sarracino , H. J. Herrmann , L. de Arcangelis

The presence of correlated noise, arising from a mixture of independent fluctuations and a common noisy input shared across the neural population, is a ubiquitous feature of neural circuits, yet its impact on collective network dynamics…

Neurons and Cognition · Quantitative Biology 2026-01-16 Hui Wang , Chunming Zheng

Scale-invariant neuronal avalanches have been observed in cell cultures and slices as well as anesthetized and awake brains, suggesting that the brain operates near criticality, i.e. within a narrow margin between avalanche propagation and…

Neurons and Cognition · Quantitative Biology 2011-01-18 Tiago L. Ribeiro , Mauro Copelli , Fábio Caixeta , Hindiael Belchior , Dante R. Chialvo , Miguel A. L. Nicolelis , Sidarta Ribeiro

The nervous system encodes continuous information from the environment in the form of discrete spikes, and then decodes these to produce smooth motor actions. Understanding how spikes integrate, represent, and process information to produce…

Neural and Evolutionary Computing · Computer Science 2017-11-15 Madhavun Candadai Vasu , Eduardo Izquierdo

The functional significance of correlations between action potentials of neurons is still a matter of vivid debates. In particular it is presently unclear how much synchrony is caused by afferent synchronized events and how much is…

Neurons and Cognition · Quantitative Biology 2013-04-09 Matthias Schultze-Kraft , Markus Diesmann , Sonja Grün , Moritz Helias
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