The effect of STDP temporal kernel structure on the learning dynamics of single excitatory and inhibitory synapses. [PDF]
PLoS ONE, 2014 Spike-Timing Dependent Plasticity (STDP) is characterized by a wide range of temporal kernels. However, much of the theoretical work has focused on a specific kernel - the "temporally asymmetric Hebbian" learning rules. Previous studies linked excitatory
Yotam Luz, Maoz Shamir
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An STDP-based encoding method for associative and composite data [PDF]
Scientific Reports, 2022 Spike-timing-dependent plasticity(STDP) is a biological process of synaptic modification caused by the difference of firing order and timing between neurons.
Hong-Gyu Yoon, Pilwon Kim
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Spike Timing-Dependent Plasticity at Layer 2/3 Horizontal Connections Between Neighboring Columns During Synapse Formation Before the Critical Period in the Developing Barrel Cortex [PDF]
CellsThe Hebbian type of spike timing-dependent plasticity (STDP) with long-term potentiation and depression (LTP and LTD) plays a crucial role at layer 4 (L4) to L2/3 synapses in deprivation-induced map plasticity.
Chiaki Itami, Fumitaka Kimura
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Resource-dependent heterosynaptic spike-timing-dependent plasticity in recurrent networks with and without synaptic degeneration [PDF]
Frontiers in Computational NeuroscienceMany computational models that incorporate spike-timing-dependent plasticity (STDP) have shown the ability to learn from stimuli, supporting theories that STDP is a sufficient basis for learning and memory.
James Humble
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Comparison and Regulation of Neuronal Synchronization for Various STDP Rules [PDF]
Neural Plasticity, 2009 We discuss effects of various experimentally supported STDP learning rules on frequency synchronization of two unidirectional coupled neurons systematically.
Yanhua Ruan, Gang Zhao
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Coincidence detection between apical and basal dendrites drives STDP in cerebellar Golgi cells [PDF]
Communications BiologyCerebellar Golgi cells (GoCs), segregate parallel fiber (pf), and mossy fiber (mf) inputs on apical and basal dendrites. Computational modeling predicted that this anatomical arrangement, coupled with a specific ionic channel localization, could be ...
Eleonora Pali +5 more
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Ultrastructural analysis of synapses after induction of spike-timing-dependent plasticity [PDF]
Cell Reports: MethodsSummary: Repeated sequential activation of connected neurons causes lasting changes in synaptic strength, a process known as spike-timing-dependent plasticity (STDP).
Rui Wang +4 more
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IEEE Access, 2022 Neuromorphic hardware is a system with massive potential to enable efficient computing by mimicking the human brain. The novel system processes information using neuron spikes (Action Potentials) and the synaptic connections between neurons are trained ...
Suman Hu +11 more
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Competitive Learning in a Spiking Neural Network: Towards an Intelligent Pattern Classifier
Sensors, 2020 One of the modern trends in the design of human−machine interfaces (HMI) is to involve the so called spiking neuron networks (SNNs) in signal processing. The SNNs can be trained by simple and efficient biologically inspired algorithms.
Sergey A. Lobov +4 more
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Intrinsic stability of temporally shifted spike-timing dependent plasticity. [PDF]
PLoS Computational Biology, 2010 Spike-timing dependent plasticity (STDP), a widespread synaptic modification mechanism, is sensitive to correlations between presynaptic spike trains and it generates competition among synapses.
Baktash Babadi, L F Abbott
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