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The neural networks of the human brain act as very efficient parallel processing computers co-ordinating memory related responses to a multitude of input signals from sensory organs. Information storage, update and appropriate retrieval are…

chao-dyn · Physics 2015-06-24 A. M. Selvam

We present a biologically detailed extension of the classical Hopfield/Marr auto-associative memory model for CA3, implementing ten populations (two asymmetric pyramidal subtypes, eight GABAergic interneuron classes), forty-seven…

Neural and Evolutionary Computing · Computer Science 2026-04-23 Daniele Corradetti , Renato Corradetti

The brain is a noisy system subject to energy constraints. These facts are rarely taken into account when modelling artificial neural networks. In this paper, we are interested in demonstrating that those factors can actually lead to the…

Neural and Evolutionary Computing · Computer Science 2017-09-26 Eliott Coyac , Vincent Gripon , Charlotte Langlais , Claude Berrou

Continuous attractor networks (CANs) are widely used to model how the brain temporarily retains continuous behavioural variables via persistent recurrent activity, such as an animal's position in an environment. However, this memory…

Neural and Evolutionary Computing · Computer Science 2025-07-02 Madison Cotteret , Christopher J. Kymn , Hugh Greatorex , Martin Ziegler , Elisabetta Chicca , Friedrich T. Sommer

Sensory neurons give highly variable responses to stimulation, which can limit the amount of stimulus information available to downstream circuits. Much work has investigated the factors that affect the amount of information encoded in…

Neurons and Cognition · Quantitative Biology 2017-04-20 Joel Zylberberg , Alexandre Pouget , Peter E. Latham , Eric Shea-Brown

This paper describes a framework for modeling the interface between perception and memory on the algorithmic level of analysis. It is consistent with phenomena associated with many different brain regions. These include view-dependence (and…

Neural and Evolutionary Computing · Computer Science 2015-12-29 Joel Z. Leibo , Julien Cornebise , Sergio Gómez , Demis Hassabis

Memory for the past makes use of a record of what happened when---a function over past time. Time cells in the hippocampus and temporal context cells in the entorhinal cortex both code for events as a function of past time, but with very…

Neurons and Cognition · Quantitative Biology 2020-03-27 Marc W. Howard , Michael E. Hasselmo

In view of some recent results in case of the dopaminergic neurons exhibiting long range correlations in VTA of the limbic brain we are interested to find out whether any stochastic nonlinear response may be reproducible in the nano scales…

Neurons and Cognition · Quantitative Biology 2007-08-20 Indranil Mitra , Sisir Roy , Gary Hastings

Self-sustained activity in the brain is observed in the absence of external stimuli and contributes to signal propagation, neural coding, and dynamic stability. It also plays an important role in cognitive processes. In this work, by means…

Cognitive maps provide a powerful framework for understanding spatial and abstract reasoning in biological and artificial agents. While recent computational models link cognitive maps to hippocampal-entorhinal mechanisms, they often rely on…

Neurons and Cognition · Quantitative Biology 2025-10-07 E. A. Dzhivelikian , A. I. Panov

This work delves into studying the synchronization in two realistic neuron models using Hodgkin-Huxley dynamics. Unlike simplistic point-like models, excitatory synapses are here randomly distributed along the dendrites, introducing strong…

Neurons and Cognition · Quantitative Biology 2024-09-17 Alessandro Fiasconaro , Michele Migliore

The primate heteromodal cortex presents an evident functional modularity at a mesoscopic level, with physiological and anatomical evidence pointing to it as likely substrate of long-term memory. In order to investigate some of its…

Neurons and Cognition · Quantitative Biology 2021-12-09 Carlo Fulvi Mari

A model of the columnar functional organization of neocortical association areas is studied. The neuronal network is composed of many Hebbian autoassociators, or modules, each of which interacts with a relatively small number of the others.…

Disordered Systems and Neural Networks · Physics 2020-05-14 Carlo Fulvi Mari

Traditionally, physical models of associative memory assume conditions of equilibrium. Here, we consider a prototypical oscillator model of associative memory and study how active noise sources that drive the system out of equilibrium, as…

Disordered Systems and Neural Networks · Physics 2023-07-26 Matthew Du , Agnish Kumar Behera , Suriyanarayanan Vaikuntanathan

Over the brief time intervals available for processing retinal output, roughly 50 to 300 msec, the number of extra spikes generated by individual ganglion cells can be quite variable. Here, computer-generated spike trains were used to…

Neurons and Cognition · Quantitative Biology 2007-09-14 Garrett T. Kenyon

Neural coding is a field of study that concerns how sensory information is represented in the brain by networks of neurons. The link between external stimulus and neural response can be studied from two parallel points of view. The first,…

Neurons and Cognition · Quantitative Biology 2012-03-07 Shinsuke Koyama

Animals rely on different decision strategies when faced with ambiguous or uncertain cues. Depending on the context, decisions may be biased towards events that were most frequently experienced in the past, or be more explorative. A…

Neurons and Cognition · Quantitative Biology 2023-05-10 Younes Bouhadjar , Dirk J. Wouters , Markus Diesmann , Tom Tetzlaff

At functional scales, cortical behavior results from the complex interplay of a large number of excitable cells operating in noisy environments. Such systems resist to mathematical analysis, and computational neurosciences have largely…

Neurons and Cognition · Quantitative Biology 2014-03-05 Mathieu Galtier , Jonathan Touboul

Cells continuously sense their surroundings to detect modifications and generate responses. Very often changes in extracellular concentrations initiate signaling cascades that eventually result in changes in gene expression. Increasing…

Cell Behavior · Quantitative Biology 2024-08-27 Alan Givré , Alejandro Colman-Lerner , Silvina Ponce Dawson

Little is known theoretically about the associative memory capabilities of neural networks in which information is encoded not only in the mean firing rate but also in the timing of firings. Particularly, in the case that the fraction of…

Disordered Systems and Neural Networks · Physics 2009-10-31 Toshio Aoyagi , Masaki Nomura