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Synaptic plasticity poses itself as a powerful method of self-regulated unsupervised learning in neural networks. A recent resurgence of interest has developed in utilizing Artificial Neural Networks (ANNs) together with synaptic plasticity…

Neural and Evolutionary Computing · Computer Science 2021-11-09 Samuel Schmidgall , Joe Hays

A classical view of neural coding relies on temporal firing synchrony among functional groups of neurons; however the underlying mechanism remains an enigma. Here we experimentally demonstrate a mechanism where time-lags among neuronal…

Neurons and Cognition · Quantitative Biology 2013-10-31 Roni Vardi , Amir Goldental , Shoshana Guberman , Alexander Kalmanovich , Hagar Marmari , Ido Kanter

The modular and hierarchical organization of the brain is believed to support the coexistence of segregated (specialization) and integrated (binding) information processes. A relevant question is yet to understand how such architecture…

Neurons and Cognition · Quantitative Biology 2025-06-19 Raphaël Bergoin , Alessandro Torcini , Gustavo Deco , Mathias Quoy , Gorka Zamora-López

We demonstrate analytically and numerically, that a thin film of an antiferromagnetic (AFM) material, having biaxial magnetic anisotropy and being driven by an external spin-transfer torque signal, can be used for the generation of…

The response of a neural cell to an external stimulus can follow one of the two patterns: Nonresonant neurons monotonously relax to the resting state after excitation while resonant ones show subthreshold oscillations. We investigate how do…

Neurons and Cognition · Quantitative Biology 2009-11-10 T. Verechtchaguina , L. Schimansky-Geier , I. M. Sokolov

A fundamental feature of learning in animals is the "ability to forget" that allows an organism to perceive, model and make decisions from disparate streams of information and adapt to changing environments. Against this backdrop, we…

Neural and Evolutionary Computing · Computer Science 2018-06-12 Priyadarshini Panda , Jason M. Allred , Shriram Ramanathan , Kaushik Roy

Neuromorphic computing is a brainlike information processing paradigm that requires adaptive learning mechanisms. A spiking neuro-evolutionary system is used for this purpose; plastic resistive memories are implemented as synapses in…

Neural and Evolutionary Computing · Computer Science 2015-05-19 Gerard David Howard , Larry Bull , Ben de Lacy Costello , Andrew Adamatzky , Ella Gale

The plasticity property of biological neural networks allows them to perform learning and optimize their behavior by changing their configuration. Inspired by biology, plasticity can be modeled in artificial neural networks by using Hebbian…

Neural and Evolutionary Computing · Computer Science 2020-12-21 Anil Yaman , Giovanni Iacca , Decebal Constantin Mocanu , George Fletcher , Mykola Pechenizkiy

We use a biophysical model of a local neuronal circuit to study the implications of synaptic plasticity for the detection of weak sensory stimuli. Networks with fast plastic coupling show behavior consistent with stochastic resonance.…

Neurons and Cognition · Quantitative Biology 2009-11-13 Vladislav Volman , Herbert Levine

In this paper, we study analytically the impact of an inhibitory autapse on neuronal activity. In order to do this, we formulate conditions on a set of non-adaptive spiking neuron models with delayed feedback inhibition, instead of…

Neurons and Cognition · Quantitative Biology 2022-10-13 Olha Shchur , Alexander Vidybida

Spike timing dependent plasticity (STDP) is believed to play an important role in shaping the structure of neural circuits. Here we show that STDP generates effective interactions between synapses of different neurons, which were neglected…

Neurons and Cognition · Quantitative Biology 2016-08-25 Neta Ravid Tannenbaum , Yoram Burak

Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by…

Neurons and Cognition · Quantitative Biology 2017-01-11 Ryan Pyle , Robert Rosenbaum

We model spontaneous cortical activity with a network of coupled spiking units, in which multiple spatio-temporal patterns are stored as dynamical attractors. We introduce an order parameter, which measures the overlap (similarity) between…

Neurons and Cognition · Quantitative Biology 2015-06-17 Silvia Scarpetta , Antonio de Candia

Correlation-based Hebbian plasticity is thought to shape neuronal connectivity during development and learning, whereas homeostatic plasticity would stabilize network activity. Here we investigate another, new aspect of this dichotomy: Can…

Neurons and Cognition · Quantitative Biology 2018-03-02 Júlia V Gallinaro , Stefan Rotter

In recent years self organised critical neuronal models have provided insights regarding the origin of the experimentally observed avalanching behaviour of neuronal systems. It has been shown that dynamical synapses, as a form of short-term…

Adaptation and Self-Organizing Systems · Physics 2018-03-28 L. Michiels van Kessenich , M. Luković , L. de Arcangelis , H. J. Herrmann

Many of the iron pnictides have strongly anisotropic normal-state characteristics, important for the exotic magnetic and superconducting behavior these materials exhibit. Yet, the origin of the observed anisotropy is unclear. Electronically…

Excitatory synaptic connections in the adult neocortex consist of multiple synaptic contacts, almost exclusively formed on dendritic spines. Changes of dendritic spine shape and volume, a correlate of synaptic strength, can be tracked in…

Neurons and Cognition · Quantitative Biology 2018-03-13 Moritz Deger , Alexander Seeholzer , Wulfram Gerstner

Brain plasticity refers to brain's ability to change neuronal connections, as a result of environmental stimuli, new experiences, or damage. In this work, we study the effects of the synaptic delay on both the coupling strengths and…

Neurons and Cognition · Quantitative Biology 2018-11-14 E. L. Lameu , E. E. N. Macau , F. S. Borges , K. C. Iarosz , I. L. Caldas , R. R. Borges , P. R. Protachevicz , R. L. Viana , A. M. Batista

In this paper we present a simple microscopic stochastic model describing short term plasticity within a large homogeneous network of interacting neurons. Each neuron is represented by its membrane potential and by the residual calcium…

Probability · Mathematics 2020-01-29 Antonio Galves , Eva Löcherbach , Christophe Pouzat , Errico Presutti

We illuminate the intriguing role played by spatial anisotropy in three-dimensional Luttinger semimetals featuring quadratic band touching and long-range Coulomb interactions. We observe the anisotropy to be subject to an exceptionally slow…

Strongly Correlated Electrons · Physics 2017-03-01 Igor Boettcher , Igor F. Herbut