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Various neurophysiological and cognitive functions are based on transferring information between spiking neurons via a complex system of synaptic connections. In particular, the capacity of presynaptic inputs to influence the postsynaptic…

Neurons and Cognition · Quantitative Biology 2018-10-30 Y. Dabaghian

We consider signal transaction in a simple neuronal model featuring intrinsic noise. The presence of noise limits the precision of neural responses and impacts the quality of neural signal transduction. We assess the signal transduction…

Biological Physics · Physics 2015-03-17 Michael J. Barber , Manfred L. Ristig

We study the learning of an external signal by a neural network and the time to forget it when this network is submitted to noise. The presentation of an external stimulus to the recurrent network of binary neurons may change the state of…

Probability · Mathematics 2020-06-11 Pascal Helson

Neurons in the nervous system are submitted to distinct sources of noise, such as ionic-channel and synaptic noise, which introduces variability in their responses to repeated presentations of identical stimuli. This motivates the use of…

Most neurons in the primary visual cortex initially respond vigorously when a preferred stimulus is presented, but adapt as stimulation continues. The functional consequences of adaptation are unclear. Typically a reduction of firing rate…

Neurons and Cognition · Quantitative Biology 2011-03-15 J. M. Cortes , D. Marinazzo , P. Series , M. W. Oram , T. J. Sejnowski , M. C. W. van Rossum

Neural networks with synaptic weights constructed according to the weighted Hebb rule, a variant of the familiar Hebb rule, are studied in the presence of noise(finite temperature), when the number of stored patterns is finite and in the…

Condensed Matter · Physics 2009-10-22 Caren Marzban , Raju Viswanathan

The capacity of non-coherent stationary Gaussian fading channels with memory under a peak-power constraint is studied in the asymptotic weak-signal regime. It is assumed that the fading law is known to both transmitter and receiver but that…

Information Theory · Computer Science 2007-07-13 Amos Lapidoth , Ligong Wang

We present a stochastic neural automata in which activity fluctuations and synaptic intensities evolve at different temperature, the latter moving through a set of stored patterns. The network thus exhibits various retrieval phases,…

Statistical Mechanics · Physics 2007-05-23 J. M. Cortes , P. L. Garrido , J. Marro , J. J. Torres

Large networks of spiking neurons show abrupt changes in their collective dynamics resembling phase transitions studied in statistical physics. An example of this phenomenon is the transition from irregular, noise-driven dynamics to…

Adaptation and Self-Organizing Systems · Physics 2008-11-25 Vicenç Gómez , Andreas Kaltenbrunner , Vicente López , Hilbert J. Kappen

Synchronization of neural activity in the gamma frequency band is associated with various cognitive phenomena. Abnormalities of gamma synchronization may underlie symptoms of several neurological and psychiatric disorders such as…

Neurons and Cognition · Quantitative Biology 2024-07-02 Quynh-Anh Nguyen , Leonid L Rubchinsky

We report on both analytical and numerical results concerning stochastic Hopfield--like neural automata exhibiting the following (biologically inspired) features: (1) Neurons and synapses evolve in time as in contact with respective baths…

Statistical Mechanics · Physics 2007-05-23 J. J. Torres , J. Marro , P. L. Garrido , J. M. Cortes , F. Ramos , M. A. Munoz

Short-term plasticity (STP) is a mechanism that stores decaying memories in synapses of the cerebral cortex. In computing practice, STP has been used, but mostly in the niche of spiking neurons, even though theory predicts that it is the…

Neural and Evolutionary Computing · Computer Science 2023-08-03 Hector Garcia Rodriguez , Qinghai Guo , Timoleon Moraitis

We investigate the impact of entropy change in deep learning systems by noise injection at different levels, including the embedding space and the image. The series of models that employ our methodology are collectively known as Noisy…

Artificial Intelligence · Computer Science 2025-09-09 Xiaowei Yu , Zhe Huang , Minheng Chen , Lu Zhang , Tianming Liu , Dajiang Zhu

Interest in understanding the interplay between noise and the response of a non-linear device cuts across disciplinary boundaries. It is as relevant for unmasking the dynamics of neurons in noisy environments as it is for designing reliable…

Biological Physics · Physics 2011-05-16 Cameron Sobie , Arif Babul , Rogerio de Sousa

This paper investigates in detail the effects of noise on the performance of reservoir computing. We focus on an application in which reservoir computers are used to learn the relationship between different state variables of a chaotic…

Neural and Evolutionary Computing · Computer Science 2023-05-10 Chad Nathe , Chandra Pappu , Nicholas A. Mecholsky , Joseph D. Hart , Thomas Carroll , Francesco Sorrentino

Working memory often appears to exceed its basic span by organizing items into compact representations called chunks. Chunking can be learned over time for familiar inputs; however, it can also arise spontaneously for novel stimuli. Such…

Neurons and Cognition · Quantitative Biology 2025-09-19 Weishun Zhong , Mikhail Katkov , Misha Tsodyks

As a means of dynamically reconfiguring the synaptic weight of a superconducting optoelectronic loop neuron, a superconducting flux storage loop is inductively coupled to the synaptic current bias of the neuron. A standard flux memory cell…

Deficits in working memory, which includes both the ability to learn and to retain information short-term, are a hallmark of many cognitive disorders. Our study analyzes data from a neuroscience experiment on animal subjects, where…

Applications · Statistics 2025-12-23 Maria Laura Battagliola , Laura J. Benoit , Sarah Canetta , Shizhe Zhang , R. Todd Ogden

Competition between synapses arises in some forms of correlation-based plasticity. Here we propose a game theory-inspired model of synaptic interactions whose dynamics is driven by competition between synapses in their weak and strong…

Disordered Systems and Neural Networks · Physics 2011-10-19 Ajaz Ahmad Bhat , Gaurang Mahajan , Anita Mehta

Synaptic strength can be seen as probability to propagate impulse, and according to synaptic plasticity, function could exist from propagation activity to synaptic strength. If the function satisfies constraints such as continuity and…

Neurons and Cognition · Quantitative Biology 2019-04-25 Sizhong Lan
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