English
Related papers

Related papers: Functional importance of noise in neuronal informa…

200 papers

A new type of deterministic (non-probabilistic) computer logic system inspired by the stochasticity of brain signals is shown. The distinct values are represented by independent stochastic processes: independent voltage (or current) noises.…

General Physics · Physics 2010-04-05 Laszlo B. Kish

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

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

The dynamics of noise-resilient Boolean networks with majority functions and diverse topologies is investigated. A wide class of possible topological configurations is parametrized as a stochastic blockmodel. For this class of networks, the…

Disordered Systems and Neural Networks · Physics 2012-01-11 Tiago P. Peixoto

Resistive memory is a promising alternative to SRAM, but is also an inherently unstable device that requires substantial effort to ensure correct read and write operations. To avoid the associated costs in terms of area, time and energy,…

Machine Learning · Computer Science 2024-01-12 Yannick Emonds , Kai Xi , Holger Fröning

Data noising is an effective technique for regularizing neural network models. While noising is widely adopted in application domains such as vision and speech, commonly used noising primitives have not been developed for discrete…

Machine Learning · Computer Science 2017-03-09 Ziang Xie , Sida I. Wang , Jiwei Li , Daniel Lévy , Aiming Nie , Dan Jurafsky , Andrew Y. Ng

Robustness to noise is of utmost importance in reinforcement learning systems, particularly in military contexts where high stakes and uncertain environments prevail. Noise and uncertainty are inherent features of military operations,…

Machine Learning · Computer Science 2023-11-16 Lorenzo Nodari , Federico Cerutti

Brain decoding algorithms form an important part of the arsenal of analysis tools available to neuroscientists, allowing for a more detailed study of the kind of information represented in patterns of cortical activity. While most current…

Quantitative Methods · Quantitative Biology 2017-08-17 R. S. van Bergen , J. F. M. Jehee

Stochastic systems have a control-theoretic interpretation in which noise plays the role of control. In the weak-noise limit, relevant at low temperatures or in large populations, this leads to a precise mathematical mapping: the most…

Molecular Networks · Quantitative Biology 2025-09-03 Eric De Giuli

Why is the spine of a neuron so small that only small numbers of molecules can exist and reactions inevitably become stochastic? Despite such noisy conditions, we previously showed that the spine exhibits robust, sensitive and efficient…

Subcellular Processes · Quantitative Biology 2017-03-02 Masashi Fujii , Kaoru Ohashi , Yasuaki Karasawa , Minori Hikichi , Shinya Kuroda

The particle-in-cell numerical method of plasma physics balances a trade-off between computational cost and intrinsic noise. Inference on data produced by these simulations generally consists of binning the data to recover the particle…

Plasma Physics · Physics 2022-02-03 John Donaghy , Kai Germaschewski

A new method is introduced to obtain a strong signal by the interference of weak signals in noisy channels. The method is based on the interference of 1/f noise from parallel channels. One realization of stochastic interference is the…

Chaotic Dynamics · Physics 2009-11-07 K. Svozil , D. Felix , K. Ehrenberger

We study the effect of intrinsic noise on the thermodynamic balance of complex chemical networks subtending cellular metabolism and gene regulation. A topological network property called deficiency, known to determine the possibility of…

Molecular Networks · Quantitative Biology 2015-11-12 Matteo Polettini , Artur Wachtel , Massimiliano Esposito

Recent research on the dynamics of certain fluid dynamical instabilities shows that when there is a slow invariant manifold subject to fast timescale instability the dynamics are extremely sensitive to noise. The behaviour of such systems…

adap-org · Physics 2009-10-30 G. D. Lythe , M. R. E. Proctor

Spikes are the currency in central nervous systems for information transmission and processing. They are also believed to play an essential role in low-power consumption of the biological systems, whose efficiency attracts increasing…

Neural and Evolutionary Computing · Computer Science 2020-05-05 Qiang Yu , Shenglan Li , Huajin Tang , Longbiao Wang , Jianwu Dang , Kay Chen Tan

A short review is presented of a recently developed computational approach which allows the study of the resistance noise over the full range of bias values, from the linear regime up to electrical breakdown. Resistance noise is described…

Disordered Systems and Neural Networks · Physics 2007-05-23 Cecilia Pennetta

Neuronal firing activities have attracted a lot of attention since a large population of spatiotemporal patterns in the brain is the basis for adaptive behavior and can also reveal the signs for various neurological disorders including…

Neurons and Cognition · Quantitative Biology 2017-03-13 Wenyuan Li , Igor V. Ovchinnikov , Honglin Chen , Zhe Wang , Albert Lee , Hochul Lee , Carlos Cepeda , Robert N. Schwartz , Karlheinz Meier , Kang L. Wang

Biological systems are characterized by the ubiquitous roles of weak, that is, non-covalent molecular interactions, small, often very small, numbers of specific molecules per cell, and Brownian motion. These combine to produce stochastic…

Cell Behavior · Quantitative Biology 2023-04-27 Michael W. Klymkowsky

In the current quantum computing paradigm, significant focus is placed on the reduction or mitigation of quantum decoherence. When designing new quantum processing units, the general objective is to reduce the amount of noise qubits are…

Quantum Physics · Physics 2026-02-17 Viacheslav Kuzmin , Wilfrid Somogyi , Ekaterina Pankovets , Alexey Melnikov

The correlated variability in the responses of a neural population to the repeated presentation of a sensory stimulus is a universally observed phenomenon. Such correlations have been studied in much detail, both with respect to their…

Neurons and Cognition · Quantitative Biology 2018-07-04 Volker Pernice , Rava Azeredo da Silveira
‹ Prev 1 8 9 10 Next ›