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Associative memory models retrieve stored information through content-based addressing, mimicking the neural processes of animal brains. The classical Hopfield network-based models store memories as vectors of discrete values and have good…

Neurons and Cognition · Quantitative Biology 2026-01-21 Nurani Rajagopal Rohan , V. Srinivasa Chakravarthy , Sayan Gupta

We consider a typical class of systems with delayed nonlinearity, which we show to exhibit chaotic diffusion. It is demonstrated that a periodic modulation of the time-lag can lead to an enhancement of the diffusion constant by several…

Chaotic Dynamics · Physics 2022-03-02 Tony Albers , David Müller-Bender , Lukas Hille , Günter Radons

The complex spatiotemporal patterns of atmospheric flows resulting from the cooperative existence of fluctuations ranging in size from millimeters to thousands of kilometers are found to exhibit long-range spatial and temporal correlations…

General Physics · Physics 2016-11-17 A. Mary Selvam

Chaotic dynamics have emerged as a versatile resource for neuromorphic and probabilistic computing, enabling high-dimensional nonlinear processing and classical analogues of quantum randomness. Exploiting chaos for computation requires…

Chaotic Dynamics · Physics 2026-05-20 Jungyoon Kim , Kyuho Kim , Kunwoo Park , Namkyoo Park , Sunkyu Yu

We present DiffCollage, a compositional diffusion model that can generate large content by leveraging diffusion models trained on generating pieces of the large content. Our approach is based on a factor graph representation where each…

Computer Vision and Pattern Recognition · Computer Science 2023-03-31 Qinsheng Zhang , Jiaming Song , Xun Huang , Yongxin Chen , Ming-Yu Liu

The generalization properties of an attractive network of non monotonic neurons which infers concepts from samples are studied. The macroscopic dynamics for the overlap between the state of the neurons with the concepts, well as the…

Statistical Mechanics · Physics 2009-10-31 D. R. C. Dominguez

Hair cells of the auditory and vestibular systems display astonishing sensitivity, frequency selectivity, and temporal resolution to external signals. These specialized cells utilize an internal active amplifier to achieve highly sensitive…

Neurons and Cognition · Quantitative Biology 2021-03-31 Justin Faber , Hancheng Li , Dolores Bozovic

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…

Neurons and Cognition · Quantitative Biology 2014-02-25 Guillaume Lajoie , Jean-Philippe Thivierge , Eric Shea-Brown

Cortical oscillations are thought to be involved in many cognitive functions and processes. Several mechanisms have been proposed to regulate oscillations. One prominent but understudied mechanism is gap-junctional coupling. Gap junctions…

Neurons and Cognition · Quantitative Biology 2018-07-04 Guillaume Pernelle , Wilten Nicola , Claudia Clopath

Coordinated responses to environmental stimuli are critical for multicellular organisms. To overcome the obstacles of cell-to-cell heterogeneity and noisy signaling dynamics within individual cells, cells must effectively exchange…

Biological Physics · Physics 2022-10-12 Guanyu Li , Ryan LeFebre , Alia Starman , Patrick Chappell , Andrew Mugler , Bo Sun

A main feature of a chaotic quantum system is a rigid spectrum where the levels do not cross. We discuss how the presence of level repulsion in lattice many-body quantum systems can be detected from the analysis of their time evolution…

Statistical Mechanics · Physics 2018-01-08 E. J. Torres-Herrera , Lea F. Santos

Spatiotemporal chaotic systems are difficult to characterize in a model-free manner because of their high dimensionality, strong nonlinearity, and sensitivity to initial conditions. Coupled map lattices, as a representative class of…

Chaotic Dynamics · Physics 2026-04-15 Xiaoqi Lei , Zixiang Yan , Jian Gao , Yueheng Lan , Jinghua Xiao

We investigate the equilibria of a random model network exhibiting extensive chaos. In this regime, a large number of equilibria is present. They are all saddles with low-dimensional unstable manifolds. Surprisingly, despite network's…

Disordered Systems and Neural Networks · Physics 2025-10-23 Xiaoyu Yang , Giancarlo La Camera , Gianluigi Mongillo

We introduce a model of randomly connected neural populations and study its dynamics by means of the dynamical mean-field theory and simulations. Our analysis uncovers a rich phase diagram, featuring high- and low-dimensional chaotic…

Biological Physics · Physics 2025-05-01 Łukasz Kuśmierz , Ulises Pereira-Obilinovic , Zhixin Lu , Dana Mastrovito , Stefan Mihalas

We demonstrate that diffusively coupled limit-cycle oscillators on random networks can exhibit various complex dynamical patterns. Reducing the system to a network analog of the complex Ginzburg-Landau equation, we argue that uniform…

Pattern Formation and Solitons · Physics 2009-04-06 Hiroya Nakao , Alexander S. Mikhailov

Complex dynamical systems are often modeled as networks, with nodes representing dynamical units which interact through the network's links. Gene regulatory networks, responsible for the production of proteins inside a cell, are an example…

Statistical Mechanics · Physics 2009-09-30 Zoran Levnajić

We investigate the connections between microscopic chaos, defined on a dynamical level and arising from collisions between molecules, and diffusion, characterized by a mean square displacement proportional to the time. We use a number of…

Chaotic Dynamics · Physics 2007-05-23 C. P. Dettmann , E. G. D. Cohen

Ensembles of phase-oscillators are known to exhibit a variety of collective regimes. Here, we show that a simple mean-field model involving two heterogenous populations of pulse-coupled oscillators, exhibits, in the strong-coupling limit, a…

Disordered Systems and Neural Networks · Physics 2024-07-12 German Mato , Antonio Politi , Alessandro Torcini

The rising computational and energy demands of artificial intelligence systems urge the exploration of alternative software and hardware solutions that exploit physical effects for computation. According to machine learning theory, a neural…

Chaotic Dynamics · Physics 2025-04-11 Hend Abdel-Ghani , A. H. Abbas , Ivan S. Maksymov

Strong nonlinear effects combined with diffusive coupling may give rise to unpredictable evolution in spatially extended deterministic dynamical systems even in the presence of a fully negative spectrum of Lyapunov exponents. This regime,…

Chaotic Dynamics · Physics 2009-11-07 F. Ginelli , R. Livi , A. Politi