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Many of the biological, social and man-made networks around us are inherently dynamic, with their links switching on and off over time. The evolution of these networks is often non-Markovian, and the dynamics of their links correlated.…

Statistical Mechanics · Physics 2021-07-23 Oliver E. Williams , Piero Mazzarisi , Fabrizio Lillo , Vito Latora

The apparent randomness of chaotic eigenstates in interacting quantum systems hides subtle correlations dynamically imposed by their finite energy per particle. These correlations are revealed when Berrys approach for chaotic eigenfunctions…

Quantum Physics · Physics 2025-02-05 Florian Schoeppl , Remy Dubertrand , Juan-Diego Urbina , Klaus Richter

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.…

Neurons and Cognition · Quantitative Biology 2007-05-23 Alexander Lerchner , Mandana Ahmadi , John Hertz

Two recent experimental observations pose a challenge to many cortical models. First, the activity in the auditory cortex is sparse, and firing rates can be described by a lognormal distribution. Second, the distribution of non-zero…

Neurons and Cognition · Quantitative Biology 2008-09-10 Alexei Koulakov , Tomas Hromadka , Anthony M. Zador

Bursty transport phenomena associated with convective motion present universal statistical characteristics among different physical systems. In this letter, a stochastic univariate model and the associated probability distribution function…

Plasma Physics · Physics 2015-05-13 I. Sandberg , S. Benkadda , X. Garbet , G. Ropokis , K. Hizanidis , D. del-Castillo-Negrete

Many real-world complex systems including human interactions can be represented by temporal (or evolving) networks, where links activate or deactivate over time. Characterizing temporal networks is crucial to compare such systems and to…

Physics and Society · Physics 2022-08-30 Alberto Ceria , Shlomo Havlin , Alan Hanjalic , Huijuan Wang

We use mean field theory to study the response properties of a simple randomly-connected model cortical network of leaky integrate-and-fire neurons with balanced excitation and inhibition. The formulation permits arbitrary temporal…

Disordered Systems and Neural Networks · Physics 2007-05-23 John Hertz , Barry Richmond , Kristian Nilsen

We adopt the concept of the correlation matrix to study correlations among sequences of time-extended events occuring repeatedly at consecutive time-intervals. As an application we analyse the magnetoencephalography recordings obtained from…

Statistical Mechanics · Physics 2009-10-31 J. Kwapien , S. Drozdz , A. A. Ioannides

Random walks are basic diffusion processes on networks and have applications in, for example, searching, navigation, ranking, and community detection. Recent recognition of the importance of temporal aspects on networks spurred studies of…

Physics and Society · Physics 2015-01-14 Leo Speidel , Renaud Lambiotte , Kazuyuki Aihara , Naoki Masuda

We introduce a model of adaptive temporal networks whose evolution is regulated by an interplay between node activity and dynamic exchange of information through links. We study the model by using a master equation approach. Starting from a…

Physics and Society · Physics 2016-04-18 Takaaki Aoki , Luis E. C. Rocha , Thilo Gross

Continuous-time systems with switch-like behaviour occur in chemical kinetics, gene regulatory networks and neural networks. Networks with hard switching, as a limiting case of smooth sigmoidal switching, retain the richest possible range…

Dynamical Systems · Mathematics 2019-05-10 Roderick Edwards

Although the time profiles of gamma ray bursts (GRBs) show extremely diverse behavior, their average statistical properties such as the average peak-aligned profile and the auto-correlation function show simple stretched-exponential…

Astrophysics · Physics 2009-10-28 Boris E. Stern , Roland Svensson

Understanding the temporal properties of longitudinal data is critical for identifying trends, predicting future events, and making informed decisions in any field where temporal data is analysed, including health and epidemiology, finance,…

When a periodic 1D system described by a tight-binding model is uniformly initialized with equal amplitudes at all sites, yet with completely random phases, it evolves into a thermal distribution with no spatial correlations. However, when…

Disordered Systems and Neural Networks · Physics 2010-12-09 Yaron Silberberg , Yoav Lahini , Yaron Bromberg , Eran Small , Roberto Morandotti

In temporal networks, where nodes interact via sequences of temporary events, information or resources can only flow through paths that follow the time-ordering of events. Such temporal paths play a crucial role in dynamic processes.…

Physics and Society · Physics 2011-07-20 Raj Kumar Pan , Jari Saramäki

The relation between spontaneous and stimulated global brain activity is a fundamental problem in the understanding of brain functions. This question is investigated both theoretically and experimentally within the context of nonequilibrium…

Neurons and Cognition · Quantitative Biology 2020-09-07 A. Sarracino , O. Arviv , O. Shriki , L. de Arcangelis

Tasks that require information about the world imply a trade-off between the time spent on observation and the variance of the response. In particular, fast decisions need to rely on uncertain information. However, standard estimates of…

Neurons and Cognition · Quantitative Biology 2023-07-18 Sahel Azizpour , Viola Priesemann , Johannes Zierenberg , Anna Levina

In transport processes across materials like glasses, living cells, and porous media, the probability density function of displacements exhibits exponential decay rather than Gaussian behavior. We show that this universal behavior of rare…

Statistical Mechanics · Physics 2024-10-31 R. K. Singh , Stanislav Burov

A Gibbs-like approach for simultaneous multi-scale correlation functions in random, time-dependent, multiplicative processes for the turbulent energy cascade is investigated. We study the optimal log-normal Gibbs-like distribution able to…

Chaotic Dynamics · Physics 2007-06-13 Roberto Benzi , Luca Biferale , Mauro Sbragaglia

To make informed decisions in natural environments that change over time, humans must update their beliefs as new observations are gathered. Studies exploring human inference as a dynamical process that unfolds in time have focused on…

Neurons and Cognition · Quantitative Biology 2022-03-03 Arthur Prat-Carrabin , Robert C. Wilson , Jonathan D. Cohen , Rava Azeredo da Silveira