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Synaptic plasticity is a key component of neuronal dynamics, describing the process by which the connections between neurons change in response to experiences. In this study, we extend a network model of $\theta$-neuron oscillators to…

神经元与认知 · 定量生物学 2024-08-01 Niamh Fennelly , Alannah Neff , Renaud Lambiotte , Andrew Keane , Áine Byrne

Elastic confinements are an important component of many biological systems and dictate the transport properties of suspended particles under flow. In this chapter, we review the Brownian motion of a particle moving in the vicinity of a…

软凝聚态物质 · 物理学 2022-10-28 Abdallah Daddi-Moussa-Ider , Stephan Gekle

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…

无序系统与神经网络 · 物理学 2007-05-23 N. Brunel , V. Hakim

The aim of the paper is to present numerical results supporting the presence of conformal invariance in three dimensional statistical mechanics models at criticality and to elucidate the geometric aspects of universality. As a case study we…

统计力学 · 物理学 2015-10-05 G. Gori , A. Trombettoni

We present exact results, as well as some illustrative Monte Carlo simulations, concerning a stochastic network with weighted connections in which the fraction of nodes that are dynamically synchronized is a parameter. This allows one to…

无序系统与神经网络 · 物理学 2007-05-23 J. Marro , J. J. Torres , J. M. Cortes , B. Wemmenhove

Hebbian plasticity is a powerful principle that allows biological brains to learn from their lifetime experience. By contrast, artificial neural networks trained with backpropagation generally have fixed connection weights that do not…

神经与进化计算 · 计算机科学 2016-10-20 Thomas Miconi

In this article, a correlation metric $\kappa_C$ is proposed for the inference of the dynamical state of neuronal networks. $\kappa_C$ is computed from the scaling of the correlation length with the size of the observation region, which…

Multiple studies of neural avalanches across different data modalities led to the prominent hypothesis that the brain operates near a critical point. The observed exponents often indicate the mean-field directed-percolation universality…

神经元与认知 · 定量生物学 2022-11-14 Roxana Zeraati , Victor Buendía , Tatiana A. Engel , Anna Levina

The stability of complex networks, from power grids to biological systems, is crucial for their proper functioning. It is thus important to control such systems to maintain or restore their stability. Traditional approaches rely on…

最优化与控制 · 数学 2025-09-23 Yuzhen Qin , Fabio Pasqualetti , Danielle S. Bassett , Marcel van Gerven

Population-wide oscillations are ubiquitously observed in mesoscopic signals of cortical activity. In these network states a global oscillatory cycle modulates the propensity of neurons to fire. Synchronous activation of neurons has been…

神经元与认知 · 定量生物学 2017-07-04 Tobias Kühn , Moritz Helias

Criticality has been proposed as a key principle underlying complex behavior in biological and artificial systems; however, how criticality translates from individual dynamics to collective behavior remains unclear. We study this question…

适应与自组织系统 · 物理学 2026-05-05 Nicolas Bessone , Erwan Plantec

One of the defining features of active nematics is that above a critical activity the quiescent state becomes unstable to a distorted, flowing one. We show that spatial variations in activity can fundamentally change the nature of this…

软凝聚态物质 · 物理学 2025-12-15 Alexander J. H. Houston , Michael Grinfeld , Geoff McKay , Nigel J. Mottram

We present a model of adaptive regulatory networks consisting of a simple biologically-motivated rewiring procedure coupled to an elementary stability criterion. The resulting networks exhibit a characteristic stationary heavy-tailed degree…

物理与社会 · 物理学 2020-08-05 Ben D. MacArthur , Rubén J. Sánchez-García , Avi Ma'ayan

The exploration of brain networks has reached an important milestone as relatively large and reliable information has been gathered for connectomes of different species. Analyses of connectome data sets reveal that the structural length and…

生物物理 · 物理学 2025-04-03 Michelle T. Cirunay , Rene C. Batac , Géza Odór

Similar activity patterns may arise from model neural networks with distinct coupling properties and individual unit dynamics. These similar patterns may, however, respond differently to parameter variations and, specifically, to tuning of…

神经元与认知 · 定量生物学 2023-06-16 Zhuojun Yu , Jonathan E. Rubin , Peter J. Thomas

There is increasing interest in developing the theoretical foundations of networked control systems that illuminate how brain networks function so as to enable sensory perception, control of movement, memory and all the operations that are…

系统与控制 · 电气工程与系统科学 2025-06-03 Zexin Sun , John Baillieul

Critical dynamics are assumed to be an attractive mode for normal brain functioning as information processing and computational capabilities are found to be optimized there. Recent experimental observations of neuronal activity patterns…

神经元与认知 · 定量生物学 2015-05-28 Christian Meisel , Alexander Storch , Susanne Hallmeyer-Elgner , Ed Bullmore , Thilo Gross

Criticality, observed during second-order phase transitions, is an emergent phenomenon. The brain operates near criticality, where complex systems exhibit high correlations. The critical brain hypothesis suggests that the brain becomes an…

统计力学 · 物理学 2023-06-21 Anirudh Palutla , Shivansh Seth , S. S. Ashwin , Marimuthu Krishnan

We explore both analytically and numerically an ensemble of coupled phase-oscillators governed by a Kuramoto-type system of differential equations. However, we have included the effects of time-delay (due to finite signal-propagation…

适应与自组织系统 · 物理学 2015-06-16 Liam Timms , Lars Q. English

Highly correlated brain dynamics produces synchronized states with no behavioral value, while weakly correlated dynamics prevents information flow. We discuss the idea put forward by Per Bak that the working brain stays at an intermediate…

无序系统与神经网络 · 物理学 2009-09-29 Dante R. Chialvo