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Processing sequential inputs is a fundamental brain function, underlying tasks such as sensory perception, language, and motor control. A challenge in sequence processing is to represent not only the order of events, but also their precise…

Neurons and Cognition · Quantitative Biology 2026-05-22 Melissa Lober , Younes Bouhadjar , Markus Diesmann , Tom Tetzlaff

We propose a discrete time dynamical system (a map) as phenomenological model of excitable and spiking-bursting neurons. The model is a discontinuous two-dimensional map. We find condition under which this map has an invariant region on the…

Neurons and Cognition · Quantitative Biology 2009-11-13 Maurice Courbage , V. I. Nekorkin , L. V. Vdovin

The structure of a genetic network is uncovered by studying its response to external stimuli (input signals). We present a theory of propagation of an input signal through a linear stochastic genetic network. It is found that there are…

Molecular Networks · Quantitative Biology 2009-11-11 Ovidiu Lipan , Wing H. Wong

We investigate the efficient transmission and processing of weak, subthreshold signals in a realistic neural medium in the presence of different levels of the underlying noise. Assuming Hebbian weights for maximal synaptic conductances --…

Biological Physics · Physics 2015-08-19 Joaquin J. Torres , Irene Elices , J. Marro

When inhibitory neurons constitute about 40% of neurons they could have an important antinociceptive role, as they would easily regulate the level of activity of other neurons. We consider a simple network of cortical spiking neurons with…

Neurons and Cognition · Quantitative Biology 2014-01-28 Fernando Montani , Emilia B. Deleglise , Osvaldo A. Rosso

Recently, neuronal avalanches have been observed to display oscillations, a phenomenon regarded as the co-existence of a scale-free behaviour (the avalanches close to criticality) and scale-dependent dynamics (the oscillations). Ordinary…

Disordered Systems and Neural Networks · Physics 2020-03-09 Johannes Pausch , Rosalba Garcia-Millan , Gunnar Pruessner

Inspired by the operation of biological brains, Spiking Neural Networks (SNNs) have the unique ability to detect information encoded in spatio-temporal patterns of spiking signals. Examples of data types requiring spatio-temporal processing…

Neural and Evolutionary Computing · Computer Science 2021-04-27 Nicolas Skatchkovsky , Hyeryung Jang , Osvaldo Simeone

Sensory perception (e.g. vision) relies on a hierarchy of cortical areas, in which neural activity propagates in both directions, to convey information not only about sensory inputs but also about cognitive states, expectations and…

Neurons and Cognition · Quantitative Biology 2023-04-13 Grégory Faye , Guilhem Fouilhé , Rufin VanRullen

We consider two neuronal networks coupled by long-range excitatory interactions. Oscillations in the gamma frequency band are generated within each network by local inhibition. When long-range excitation is weak, these oscillations…

Neurons and Cognition · Quantitative Biology 2009-11-13 Demian Battaglia , Nicolas Brunel , David Hansel

We propose a framework for surrogate modelling of spiking systems. These systems are often described by stiff differential equations with high-amplitude oscillations and multi-timescale dynamics, making surrogate models an attractive tool…

Systems and Control · Electrical Eng. & Systems 2024-07-08 Miguel Aguiar , Amritam Das , Karl H. Johansson

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''…

Applications · Statistics 2026-04-22 Pierre Charitat , Ségolen Geffray , Christophe Pouzat

Many networks used in machine learning and as models of biological neural networks make use of stochastic neurons or neuron-like units. We show that stochastic artificial neurons can be realized on silicon chips by exploiting the…

Neural and Evolutionary Computing · Computer Science 2015-12-10 Hesham Mostafa , Giacomo Indiveri

In neural circuits, statistical connectivity rules strongly depend on neuronal type. Here we study dynamics of neural networks with cell-type specific connectivity by extending the dynamic mean field method, and find that these networks…

Neurons and Cognition · Quantitative Biology 2015-02-24 Johnatan Aljadeff , Merav Stern , Tatyana O. Sharpee

The brain is in a state of perpetual reverberant neural activity, even in the absence of specific tasks or stimuli. Shedding light on the origin and functional significance of such a dynamical state is essential to understanding how the…

Statistical Mechanics · Physics 2022-07-08 Guillermo B. Morales , Serena Di Santo , Miguel A. Munoz

Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a…

Adaptation and Self-Organizing Systems · Physics 2016-07-08 Christoph Kirst , Marc Timme , Demian Battaglia

The transmission or reception of packets passing between computers can be represented in terms of time-stamped events and the resulting activity understood in terms of point-processes. Interestingly, in the disparate domain of neuroscience,…

Applications · Statistics 2017-11-28 Alex Gibberd , Jordan Noble , Edward Cohen

In recent years it is increasingly being recognized that biochemical signals are not necessarily constant in time and that the temporal dynamics of a signal can be the information carrier. Moreover, it is now well established that…

Molecular Networks · Quantitative Biology 2015-06-17 Wiet de Ronde , Pieter Rein ten Wolde

Numerical calculations have been made on the spike-train response of a pair of Hodgkin-Huxley (HH) neurons coupled by synapses and axons with time delay. The recurrent excitatory-excitatory, inhibitory-inhibitory, excitatory-inhibitory, and…

Disordered Systems and Neural Networks · Physics 2007-05-23 Hideo Hasegawa

A recurrent idea in the study of complex systems is that optimal information processing is to be found near bifurcation points or phase transitions. However, this heuristic hypothesis has few (if any) concrete realizations where a standard…

Neurons and Cognition · Quantitative Biology 2007-05-23 Osame Kinouchi , Mauro Copelli

We study wave propagation in networks of coupled cells which can behave as excitable or self-oscillatory media. For excitable media, an asymptotic construction of wave trains is presented. This construction predicts their shape and speed,…

Other Condensed Matter · Physics 2009-11-11 A. Carpio
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