Results 61 to 70 of about 40,549 (223)

Hardware Coupled Nonliear Oscillators as a Model of Retina [PDF]

, 1995
An electronic circuit consisting of coupled nonlinear oscillators⁴＇⁵ simulates the spatiotemporal processing in retina. Complex behavior recorded in vivo from ganglion cells in the cat retina 6 in response to flickering light spots is matched by setting ...
Gaudiano, P., Linsay, P.S., Przybyszewski, A.W>, Wilson, C.M.   +3 more
core   +1 more source

A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines

, 2017
Information in neural networks is represented as weighted connections, or synapses, between neurons. This poses a problem as the primary computational bottleneck for neural networks is the vector-matrix multiply when inputs are multiplied by the neural ...
Aimone, James B., Carlson, Kristofor D., Donaldson, Jonathon, Follett, David R., Follett, Pamela L., Hill, Aaron J., James, Conrad D., Naegle, John H., Smith, Michael R., Vineyard, Craig M.   +9 more
core   +1 more source

Discovery and Targeted Proteomic Studies Reveal Striatal Markers Validated for Huntington's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Clinical trials for Huntington's disease (HD) enrolling persons before clinical motor diagnosis (CMD) lack validated biomarkers. This study aimed to conduct an unbiased discovery analysis and a targeted examination of proteomic biomarkers scrutinized by clinical validation. Methods Cerebrospinal fluid was obtained from PREDICT‐HD and
Daniel Chelsky, Cara Joyce, H. Jeremy Bockholt, Paul A. Rudnick, William H. Adams, Fiona McAllister, Justin W. Smock, Michael A. Newton, Jane S. Paulsen   +8 more
wiley   +1 more source

A Transient Photoelectric Spiking Neuron Based on a Highly Robust MgO Composite Threshold Switching Memristor for Selective UV Perception

Advanced Electronic Materials
The biological photoreceptors in the retina convert light information into spikes, inspiring the emergence of artificial photoelectric spiking neurons. However, due to the lack of biocompatible and biodegradable characteristics, artificial photoelectric ...
Yaxiong Cao, Rui Wang, Saisai Wang, Tonglong Zeng, Wanlin Zhang, Jing Sun, Xiaohua Ma, Hong Wang, Yue Hao   +8 more
doaj   +1 more source

Gradient Descent Learning Algorithm for Spiking Neuron with Delay Adjustment [PDF]

Jisuanji gongcheng, 2019
The spiking neuron supervised learning algorithm adjusts the synaptic weight of the neuron by gradient descent method,but the accuracy gets low and the learning period gets long as the length of the target learning sequence increases.Therefore,a gradient
YANG Jing, XU Yan, ZHAO Xin
doaj   +1 more source

Supervised Learning in Multilayer Spiking Neural Networks [PDF]

, 2012
The current article introduces a supervised learning algorithm for multilayer spiking neural networks. The algorithm presented here overcomes some limitations of existing learning algorithms as it can be applied to neurons firing multiple spikes and it ...
André Grüning, Bohte S., Elias J. G., Gerstner W., Hebb D. O., Ioana Sporea, Maass W., Rostro-Gonzalez H., Rumelhart D. E., Thorpe S. T., Xin J.   +10 more
core   +2 more sources

Super‐Refractory Status Epilepticus (SRSE) in a Patient With Compound Heterozygous OPA1 Variants: Case Report and Literature Review

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi, Lara Basovic, Christopher Michael McGraw   +2 more
wiley   +1 more source

Engineering Spiking Neurons Using Threshold Switching Devices for High-Efficient Neuromorphic Computing

Frontiers in Neuroscience, 2022
Inspired by the human brain, the spike-based neuromorphic system has attracted strong research enthusiasm because of the high energy efficiency and powerful computational capability, in which the spiking neurons and plastic synapses are two fundamental ...
Yanting Ding, Yanting Ding, Yajun Zhang, Xumeng Zhang, Xumeng Zhang, Xumeng Zhang, Pei Chen, Pei Chen, Zefeng Zhang, Yue Yang, Yue Yang, Lingli Cheng, Lingli Cheng, Chen Mu, Chen Mu, Ming Wang, Ming Wang, Du Xiang, Du Xiang, Guangjian Wu, Guangjian Wu, Guangjian Wu, Keji Zhou, Keji Zhou, Keji Zhou, Zhe Yuan, Qi Liu, Qi Liu, Qi Liu   +28 more
doaj   +1 more source

Deep Neural Networks - A Brief History

, 2017
Introduction to deep neural networks and their history.Comment: 14 pages, 14 ...
AL Hodgkin, DH Hubel, DM Sala, EM Izhikevich, EM Izhikevich, GE Hinton, GE Hinton, HK Lim, JH Shin, K Fukushima, KJ Cios, T Kohonen, W Swiercz, WS McCulloch   +13 more
core   +1 more source

Real-Time Computing Platform for Spiking Neurons (RT-Spike)

IEEE Transactions on Neural Networks, 2006
A computing platform is described for simulating arbitrary networks of spiking neurons in real time. A hybrid computing scheme is adopted that uses both software and hardware components to manage the tradeoff between flexibility and computational power; the neuron model is implemented in hardware and the network model and the learning are implemented ...
Ros Vidal, Eduardo, Martínez Ortigosa, Eva, Agís, Rodrigo, Carrillo Sánchez, Richard Rafael, Arnold, Michael   +4 more
openaire   +3 more sources