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The development of new techniques to quantitatively measure gene expression in cells has shed light on a number of systems that display oscillations in protein concentration. Here we review the different mechanisms which can produce…

Molecular Networks · Quantitative Biology 2009-11-13 G. Tiana , S. Krishna , S. Pigolotti , M. H. Jensen , K. Sneppen

Neural interactions occur on different levels and scales. It is of particular importance to understand how they are distributed among different neuroanatomical and physiological relevant brain regions. We investigated neural cross-frequency…

Adaptation and Self-Organizing Systems · Physics 2023-10-20 Dushko Lukarski , Spase Petkoski , Peng Ji , Tomislav Stankovski

Selective attention allows to process stimuli which are behaviorally relevant, while attenuating distracting information. However, it is an open question what mechanisms implement selective routing, and how they are engaged in dependence on…

Neurons and Cognition · Quantitative Biology 2023-05-24 Maik Schünemann , Udo Ernst

Nonlinear oscillators can mutually synchronize when they are driven by common external impulses. Two important scenarios are (i) synchronization resulting from phase locking of each oscillator to regular periodic impulses and (ii)…

Adaptation and Self-Organizing Systems · Physics 2015-05-19 Shigefumi Hata , Takeaki Shimokawa , Kensuke Arai , Hiroya Nakao

Orbits in a three-dimensional potential subjected to periodic driving, V(x^i,t)=[1+m_0 sin(omega t) V_0(x^i), divide naturally into two types, regular and chaotic, between which transitions are seemingly impossible. The chaotic orbits…

Astrophysics · Physics 2007-05-23 Balsa Terzic , Henry E. Kandrup

Mounting experimental evidence suggests that brain-state-specific neural mechanisms, supported by connectomic architectures, play a crucial role in integrating past and contextual knowledge with the current, incoming flow of evidence (e.g.,…

Cross-frequency interactions are fundamental brain mechanisms for integrating information across temporal scales. However, accurate identification of these couplings is hindered by complex multi-frequency nonlinearities and by spurious,…

Neurons and Cognition · Quantitative Biology 2026-05-07 Alessio Basti , Rikkert Hindriks , Ruggero Freddi , Gian Luca Romani , Vittorio Pizzella , Guido Nolte , Laura Marzetti

We propose a stochastic dynamical model of noisy neural networks with complex architectures and discuss activation of neural networks by a stimulus, pacemakers and spontaneous activity. This model has a complex phase diagram with…

Disordered Systems and Neural Networks · Physics 2015-05-13 A. V. Goltsev , F. V. de Abreu , S. N. Dorogovtsev , J. F. F. Mendes

Neural circuits contain heterogeneous groups of neurons that differ in type, location, connectivity, and basic response properties. However, traditional methods for dimensionality reduction and clustering are ill-suited to recovering the…

Machine Learning · Statistics 2016-10-27 Scott W. Linderman , Ryan P. Adams , Jonathan W. Pillow

Among the versatile forms of dynamical patterns of activity exhibited by the brain, oscillations are one of the most salient and extensively studied, yet are still far from being well understood. In this paper, we provide various structural…

Systems and Control · Electrical Eng. & Systems 2021-08-12 Erfan Nozari , Robert Planas , Jorge Cortes

Neurons in the brain behave as a network of coupled nonlinear oscillators processing information by rhythmic activity and interaction. Several technological approaches have been proposed that might enable mimicking the complex information…

Applied Physics · Physics 2018-11-07 M. Vogel , B. Zimmermann , J. Wild , F. Schwarzhuber , C. Mewes , T. Mewes , J. Zweck , C. H. Back

-In recent years, there has been an increased focus on the mechanics of information transmission in spiking neural networks. Especially the Noise Shaping properties of these networks and their similarity to Delta-Sigma Modulators has…

Emerging Technologies · Computer Science 2014-08-11 C. Mayr , R. Schüffny

Crowd behaviour challenges our fundamental understanding of social phenomena. Involving complex interactions between multiple temporal and spatial scales of activity, its governing mechanisms defy conventional analysis. Using 1.5 million…

Physics and Society · Physics 2018-01-18 Miguel Aguilera

Spatial navigation in mammals is based on building a mental representation of their environment---a cognitive map. However, both the nature of this cognitive map and its underpinning in neural structures and activity remains vague. A key…

Neurons and Cognition · Quantitative Biology 2016-03-22 A. Babichev , S. Cheng , Yu. Dabaghian

While most models of randomly connected networks assume nodes with simple dynamics, nodes in realistic highly connected networks, such as neurons in the brain, exhibit intrinsic dynamics over multiple timescales. We analyze how the…

Disordered Systems and Neural Networks · Physics 2019-09-11 Samuel P. Muscinelli , Wulfram Gerstner , Tilo Schwalger

Neural processing systems typically represent data using leaky integrate and fire (LIF) neuron models that generate spikes or pulse trains at a rate proportional to their input amplitudes. This mechanism requires high firing rates when…

Emerging Technologies · Computer Science 2019-05-07 Manu V Nair , Giacomo Indiveri

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 seemingly stochastic transient dynamics of neocortical circuits observed in vivo have been hypothesized to represent a signature of ongoing stochastic inference. In vitro neurons, on the other hand, exhibit a highly deterministic…

Neurons and Cognition · Quantitative Biology 2017-03-14 Mihai A. Petrovici , Johannes Bill , Ilja Bytschok , Johannes Schemmel , Karlheinz Meier

Chaos provides many interesting properties that can be used to achieve computational tasks. Such properties are sensitivity to initial conditions, space filling, control and synchronization. Chaotic neural models have been devised to…

Neural and Evolutionary Computing · Computer Science 2015-01-12 M. Alhawarat , T. Olde Scheper , N. T. Crook

We experimentally demonstrate that networks of identical photonic spiking neurons based on coupled degenerate parametric oscillators can show various chimera states, in which, depending on their local synchronization and desynchronization,…