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When assessing spatially-extended complex systems, one can rarely sample the states of all components. We show that this spatial subsampling typically leads to severe underestimation of the risk of instability in systems with propagating…

数据分析、统计与概率 · 物理学 2018-07-06 Jens Wilting , Viola Priesemann

Neural circuits are able to perform computations under very diverse conditions and requirements. The required computations impose clear constraints on their fine-tuning: a rapid and maximally informative response to stimuli in general…

Developing networks of neural systems can exhibit spontaneous, synchronous activities called neural bursts, which can be important in the organization of functional neural circuits. Before the network matures, the activity level of a burst…

神经元与认知 · 定量生物学 2017-05-24 Chih-Hsu Huang , Yu-Ting Huang , Chun-Chung Chen , C. K. Chan

The characterization of network and biophysical properties from neural spiking activity is an important goal in neuroscience. A framework that provides unbiased inference on causal synaptic interaction and single neural properties has been…

神经元与认知 · 定量生物学 2024-05-27 Kevin S. Chen , Ying-Jen Yang

The idea that information-processing systems operate near criticality to enhance computational performance is supported by scaling signatures in brain activity. However, external signals raise the question of whether this behavior is…

神经元与认知 · 定量生物学 2026-02-10 Rubén Calvo , Carles Martorell , Adrián Roig , Miguel A. Muñoz

Many systems with propagation dynamics, such as spike propagation in neural networks and spreading of infectious diseases, can be approximated by autoregressive models. The estimation of model parameters can be complicated by the…

神经元与认知 · 定量生物学 2021-01-01 Jorge de Heuvel , Jens Wilting , Moritz Becker , Viola Priesemann , Johannes Zierenberg

Neuronal spiking exhibits an exquisite combination of modulation and robustness properties, rarely matched in artificial systems. We exploit the particular interconnection structure of conductance based models to investigate this remarkable…

神经元与认知 · 定量生物学 2013-11-12 Guillaume Drion , Alessio Franci , Vincent Seutin , Rodolphe Sepulchre

The principles of neural encoding and computations are inherently collective and usually involve large populations of interacting neurons with highly correlated activities. While theories of neural function have long recognized the…

神经元与认知 · 定量生物学 2019-05-14 Christophe Gardella , Olivier Marre , Thierry Mora

Repeating patterns of spike sequences from a neuronal network have been proposed to be useful in the reconstruction of the network topology. Reverberations in a physiologically realistic model with various physical connection topologies…

神经元与认知 · 定量生物学 2014-07-15 Hao Song , Chun-Chung Chen , Jyh-Jang Sun , Pik-Yin Lai , C. K. Chan

A rigorous understanding of brain dynamics and function requires a conceptual bridge between multiple levels of organization, including neural spiking and network-level population activity. Mounting evidence suggests that neural networks of…

神经元与认知 · 定量生物学 2016-10-11 Yahya Karimipanah , Zhengyu Ma , Ralf Wessel

Being permanently confronted with an uncertain world, brains have faced evolutionary pressure to represent this uncertainty in order to respond appropriately. Often, this requires visiting multiple interpretations of the available…

In this work we explore encoding strategies learned by statistical models of sensory coding in noisy spiking networks. Early stages of sensory communication in neural systems can be viewed as encoding channels in the information-theoretic…

神经元与认知 · 定量生物学 2020-06-30 M. E. Rule , M. Sorbaro , M. H. Hennig

An essential step toward understanding neural circuits is linking their structure and their dynamics. In general, this relationship can be almost arbitrarily complex. Recent theoretical work has, however, begun to identify some broad…

神经元与认知 · 定量生物学 2017-03-10 Gabriel Koch Ocker , Yu Hu , Michael A. Buice , Brent Doiron , Krešimir Josić , Robert Rosenbaum , Eric Shea-Brown

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

Thanks to novel, powerful brain activity recording techniques, we can create data-driven models from thousands of recording channels and large portions of the cortex, which can improve our understanding of brain-states neuromodulation and…

This paper introduces a class of stochastic models of interacting neurons with emergent dynamics similar to those seen in local cortical populations, and compares them to very simple reduced models driven by the same mean excitatory and…

神经元与认知 · 定量生物学 2017-11-07 Yao Li , Logan Chariker , Lai-Sang Young

The branching process is the minimal model for propagation dynamics, avalanches and criticality, broadly used in neuroscience. A simple extension of it, adding inhibitory nodes, induces a much-richer phenomenology, including, an…

统计力学 · 物理学 2022-07-08 Roberto Corral López , Victor Buendía , Miguel A. Muñoz

Neurophysiologists are nowadays able to record from a large number of extracellular electrodes and to extract, from the raw data, the sequences of action potentials or spikes generated by many neurons. Unfortunately these ''many neurons''…

应用统计 · 统计学 2026-04-22 Pierre Charitat , Ségolen Geffray , Christophe Pouzat

The critical brain hypothesis posits that neural circuitry operates near criticality to reap the computational benefits of accessing a wide range of timescales. The theory of critical phenomena generally predicts heavy-tailed (power-law)…

神经元与认知 · 定量生物学 2025-12-23 Jacob T. Crosser , Braden A. W. Brinkman

When brain signals are recorded in an electroencephalogram or some similar large-scale record of brain activity, oscillatory patterns are typically observed that are thought to reflect the aggregate electrical activity of the underlying…

神经元与认知 · 定量生物学 2013-06-04 Andre Nathan , Valmir C. Barbosa
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