Search results

For a processor or computer designed to simulate a neural network SUPS is measured as the product of simulated neurons <math>N</math> ...networks of spiking neurons and dynamical synapses |series=Perspectives in Neural Computing |isbn=978-3-540-76263-8 |citeseerx=10.1.1.56.272 }}</ref> ...

...|leaky integrate-and-fire-model]] the potential <math> V(t) </math> of the synapse can be described by where <math>t_i </math> denotes the spike time of the i-th afferent synapse with synaptic efficacy <math>\omega _i</math> and <math>V_{rest} </math> ...

{{Short description|Seminal 1943 paper proposing artificial neural networks}} ...ginal paper is slightly different from the modern version. They considered neural networks that operate in discrete steps of time <math>t = 0, 1, \dots </mat ...

...illefumier |year=2019 |title=Replica-mean-field limits for intensity-based neural networks |class=math.DS |eprint=1902.03504 }}</ref> ...e spikes of only a finite subset of other neurons, thus modeling arbitrary synapse topologies. In particular, the GL model includes as a special case the gen ...

...ors=Jacobs AL, Fridman G, Douglas RM, etal |title=Ruling out and ruling in neural codes |journal=Proc. Natl. Acad. Sci. U.S.A. |volume=106 |issue=14 |pages=5 This article specifically refers to neural decoding as it pertains to the [[mammal]]ian [[neocortex]]. ...

{{distinguish|text=[[Bayesian neural network|Bayesian Neural Network (BNN)]]}} {{Short description|Artificial neural network}} ...

...describes the non-linear dynamics at many levels of the brain from single neural cells<ref>Izhikevich, E. ''Dynamical Systems in Neuroscience: The Geometry ...ere it evolved into the simple weighting function for coupled [[artificial neural network]]s. Neurobiologists call the critical voltage at which neurons fire ...

...e firing properties of the neuron and also the response of [[neuron]] to [[Synapse|synaptic]] inputs.<ref name="Mathematical foundations of neuroscience">{{ci ...a full blown compartmental cell, it is modelled as a simplified two layer neural network.<ref name="Information Processing" /> ...

{{Short description|Architectural motif in neural networks for aggregating information.}} ...re |chapter=7.5. Pooling |chapter-url=https://d2l.ai/chapter_convolutional-neural-networks/pooling.html}}</ref> It has several uses. It removes redundant inf ...

...both structure and function of biological nervous systems. The neurons and synapse connections are intentionally designed rather than iteratively changed as p ...which the user specifies the functions of the network and the synaptic and neural properties are learned over time.<ref name="Eliasmith-2005" /> SNS follows ...

{{Short description|Neural networks}} ...date=2016 |title=Dense Associative Memory for Pattern Recognition |journal=Neural Information Processing Systems |volume=29 |pages=1172–1180 |arxiv=1606.0116 ...

'''Models of neural computation''' are attempts to elucidate, in an abstract and mathematical f The rate of information processing in biological neural systems are constrained by the speed at which an action potential can propa ...

The '''neural encoding of sound''' is the representation of [[Hearing (sense)|auditory]] ...function is [[mechanotransduction]], or conversion between mechanical and neural signals. The relatively small number of the auditory hair cells is surprisi ...

...ast3=Laurent |first3=Gilles |date=2008-07-04 |title=Transient Dynamics for Neural Processing |url=https://www.science.org/doi/10.1126/science.1155564 |journa ...switching" is an important descriptor for natural phenomena, especially in neural dynamics'''.''' It has also been used as an approach for designing robotic ...

...]] to help model the large amounts of memory that mimics that of the human neural network.<ref name=psu>{{cite journal|title=Sparse Distributed Memory and Re ===As neural network=== ...

...levels of the brain's organisation: from [[neuron]]s, to [[neural assembly|neural assemblies]] and brain structures. Brain connectivity involves different co ...e connectivity may be defined as the direct or indirect influence that one neural system exerts over another.<ref>{{Cite journal|title=Discovering Brain Mech ...

...<ref>{{cite journal |pmid=18356248 |year=2008 |last1=Doe |first1=CQ |title=Neural stem cells: Balancing self-renewal with differentiation |volume=135 |issue= ...cted to a strong stimulus, and this results in strengthening of the neural synapse (i.e., less neurotransmitter signal is required for activation). ...

...= Gilman JM, Ramchandani VA, Crouss T, Hommer DW | title = Subjective and neural responses to intravenous alcohol in young adults with light and heavy drink ...>{{cite journal | vauthors = Lovinger DM | title = 5-HT3 receptors and the neural actions of alcohols: an increasingly exciting topic | journal = Neurochemis ...

...e learning]] that focuses on utilizing [[neural network (machine learning)|neural network]]s to perform tasks such as [[Statistical classification|classifica ...riz/imagenet_classification_with_deep_convolutional.pdf|journal=NIPS 2012: Neural Information Processing Systems, Lake Tahoe, Nevada|access-date=2017-05-24|a ...