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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

Short-term memory is essential for cognitive processing, yet our understanding of its neural mechanisms remains unclear. Neuroscience has long focused on how sequential activity patterns, where neurons fire one after another within large…

Synaptic memory is considered to be the main element responsible for learning and cognition in humans. Although traditionally non-volatile long-term plasticity changes have been implemented in nanoelectronic synapses for neuromorphic…

Emerging Technologies · Computer Science 2017-12-20 Abhronil Sengupta , Kaushik Roy

The brain is not only constrained by energy needed to fuel computation, but it is also constrained by energy needed to form memories. Experiments have shown that learning simple conditioning tasks already carries a significant metabolic…

Neural and Evolutionary Computing · Computer Science 2026-04-17 Mark CW van Rossum

Synaptic connections in neuronal circuits are modulated by pre- and post-synaptic spiking activity. Heuristic models of this process of synaptic plasticity can provide excellent fits to results from in-vitro experiments in which pre- and…

Neurons and Cognition · Quantitative Biology 2022-07-14 Federico Devalle , Alex Roxin

Neural synchrony in the brain at rest is usually variable and intermittent, thus intervals of predominantly synchronized activity are interrupted by intervals of desynchronized activity. Prior studies suggested that this temporal structure…

Quantitative Methods · Quantitative Biology 2021-04-26 Joel Zirkle , Leonid L Rubchinsky

For many types of learning, spaced training that involves repeated long inter-trial intervals (ITIs) leads to more robust memory formation than does massed training that involves short or no intervals. Several cognitive theories have been…

Neurons and Cognition · Quantitative Biology 2016-06-28 Paul Smolen , Yili Zhang , John H. Byrne

Synaptic plasticity dynamically shapes the connectivity of neural systems and is key to learning processes in the brain. To what extent the mechanisms of plasticity can be exploited to drive a neural network and make it perform some kind of…

Neurons and Cognition · Quantitative Biology 2024-12-03 Francesco Borra , Simona Cocco , Rémi Monasson

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine…

Neurons and Cognition · Quantitative Biology 2018-01-08 David Kappel , Robert Legenstein , Stefan Habenschuss , Michael Hsieh , Wolfgang Maass

Short-term memory in the brain cannot in general be explained the way long-term memory can -- as a gradual modification of synaptic weights -- since it takes place too quickly. Theories based on some form of cellular bistability, however,…

Neurons and Cognition · Quantitative Biology 2013-01-31 Samuel Johnson , J. Marro , Joaquín J. Torres

Spiking neural networks (SNNs) promise energy-efficient computation by mimicking biological neural dynamics, yet existing plasticity rules focus on isolated spike pairs and fail to leverage the synchronous activity patterns that drive…

Neural and Evolutionary Computing · Computer Science 2025-08-26 Yuchen Tian , Assel Kembay , Samuel Tensingh , Nhan Duy Truong , Jason K. Eshraghian , Omid Kavehei

We analyze continuous Hopfield associative memories augmented by additional, rapid short-term associative synaptic plasticity. Through the cavity method, we determine the boundary between the retrieval and forgetting, or spin-glass phase,…

Neurons and Cognition · Quantitative Biology 2026-02-10 Martina Del Gaudio , Federico Ghimenti , Surya Ganguli

Synaptic delays play a crucial role in biological neuronal networks, where their modulation has been observed in mammalian learning processes. In the realm of neuromorphic computing, although spiking neural networks (SNNs) aim to emulate…

Neural and Evolutionary Computing · Computer Science 2025-06-19 Marissa Dominijanni , Alexander Ororbia , Kenneth W. Regan

The adaptive changes in synaptic efficacy that occur between spiking neurons have been demonstrated to play a critical role in learning for biological neural networks. Despite this source of inspiration, many learning focused applications…

Neural and Evolutionary Computing · Computer Science 2022-05-30 Samuel Schmidgall , Julia Ashkanazy , Wallace Lawson , Joe Hays

High-dimensional compartmental dynamical systems have been introduced to model brain metabolism. In this article, an approach is proposed to their mathematical analysis. Reductions of these models are obtained by replacing several…

Dynamical Systems · Mathematics 2013-08-05 Marion Lahutte-Auboin , Robert Costalat , Jean-Pierre Françoise , Remy Guillevin

In the mammalian brain newly acquired memories depend on the hippocampus for maintenance and recall, but over time these functions are taken over by the neocortex through a process called systems consolidation. However, reactivation of a…

Neurons and Cognition · Quantitative Biology 2019-03-29 Peter Helfer , Thomas R. Shultz

The main problem about replacing LTP as a memory mechanism has been to find other highly abstract, easily understandable principles for induced plasticity. In this paper we attempt to lay out such a basic mechanism, namely intrinsic…

Neurons and Cognition · Quantitative Biology 2014-05-13 Gabriele Scheler

The synaptic connectivity of cortex is plastic, with experience shaping the ongoing interactions between neurons. Theoretical studies of spike timing-dependent plasticity (STDP) have focused on either just pairs of neurons or large-scale…

Neurons and Cognition · Quantitative Biology 2016-08-02 Gabriel Koch Ocker , Brent Doiron

Synaptic plasticity allows cortical circuits to learn new tasks and to adapt to changing environments. How do cortical circuits use plasticity to acquire functions such as decision-making or working memory? Neurons are connected in complex…

Neurons and Cognition · Quantitative Biology 2023-03-08 Néstor Parga , Luis Serrano-Fernández , Joan Falcó-Roget

Asynchrony, overlaps and delays in sensory-motor signals introduce ambiguity as to which stimuli, actions, and rewards are causally related. Only the repetition of reward episodes helps distinguish true cause-effect relationships from…

Neural and Evolutionary Computing · Computer Science 2014-09-10 Andrea Soltoggio