Results 11 to 20 of about 13,938 (239)
STDP in the developing sensory neocortex [PDF]
Frontiers in Synaptic Neuroscience, 2010 Spike timing-dependent plasticity (STDP) has been proposed as a mechanism for optimizing the tuning of neurons to sensory inputs, a process that underlies the formation of receptive field properties and associative memories.
Rylan S Larsen +9 more
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Adaptive STDP-based on-chip spike pattern detection
Frontiers in Neuroscience, 2023 A spiking neural network (SNN) is a bottom-up tool used to describe information processing in brain microcircuits. It is becoming a crucial neuromorphic computational model.
Ashish Gautam, Takashi Kohno
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, 2016 A short introductory lecture on STDP covering biological background and computational approaches.Copyright for any images or text used remains with the original owners.
Humble James
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Representation learning using event-based STDP [PDF]
Neural Networks, 2018 Although representation learning methods developed within the framework of traditional neural networks are relatively mature, developing a spiking representation model remains a challenging problem. This paper proposes an event-based method to train a feedforward spiking neural network (SNN) layer for extracting visual features. The method introduces a
Amirhossein Tavanaei +2 more
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Modulating STDP Balance Impacts the Dendritic Mosaic [PDF]
Frontiers in Computational Neuroscience, 2017 The ability for cortical neurons to adapt their input/output characteristics and information processing capabilities ultimately relies on the interplay between synaptic plasticity, synapse location, and the nonlinear properties of the dendrite. Collectively, they shape both the strengths and spatial arrangements of convergent afferent inputs to ...
Nicolangelo Iannella, Thomas Launey
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STDP and STDP variations with memristors for spiking neuromorphic learning systems [PDF]
Frontiers in Neuroscience, 2013 ISSN:1662 ...
Serrano-Gotarredona, T. +4 more
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STDP in recurrent neuronal networks [PDF]
Frontiers in Computational Neuroscience, 2010 Recent results about spike-timing-dependent plasticity (STDP) in recurrently connected neurons are reviewed, with a focus on the relationship between the weight dynamics and the emergence of network structure. In particular, the evolution of synaptic weights in the two cases of incoming connections for a single neuron and recurrent connections are ...
Matthieu Gilson +6 more
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A stochastic approach to STDP [PDF]
2016 IEEE International Symposium on Circuits and Systems (ISCAS), 2016 We present a digital implementation of the Spike Timing Dependent Plasticity (STDP) learning rule. The proposed digital implementation consists of an exponential decay generator array and a STDP adaptor array. On the arrival of a pre- and post-synaptic spike, the STDP adaptor will send a digital spike to the decay generator.
Wang, Runchun +4 more
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Efficacy of Shexiang Tongxin Dropping Pills in a Swine Model of Coronary Slow Flow
Frontiers in Physiology, 2022 Objective: Preliminary clinical studies have confirmed that Shexiang Tongxin dropping pills (STDPs) could improve angina pectoris and attenuate vascular endothelial dysfunction in patients with slow coronary flow, but the underlying mechanism is not ...
Yupeng Bai +6 more
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Frontiers in Neuroscience, 2021 A Spiking Neural Network (SNN) is trained with Spike Timing Dependent Plasticity (STDP), which is a neuro-inspired unsupervised learning method for various machine learning applications.
Biswadeep Chakraborty +1 more
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