Spatiotemporal learning in analog neural networks using spike-timing-dependent synaptic plasticity.
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Summary
Incorporating the spike-timing-dependent synaptic plasticity (STDP) into a learning rule, spatiotemporal learning in analog neural networks is study by deriving the dynamics of the order parameters and identifying the retrieval state that is stable in single- pattern learning but unstable in multiple-pattern learning.
- Type
- article
- Published
- 2007-05-29
- Cited by
- 15
- References
- 30
- OpenAlex
- https://openalex.org/W1991668099
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:24195252
Keywords
Computer science, Spike-timing-dependent plasticity, Learning rule, Artificial neural network, Stability (learning theory)
References
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- Cluster synchronization in an ensemble of neurons interacting through chemical synapses.
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- Perspectives on neural network models and their relevance to neurobiology
- Statistical mechanics for networks of graded-response neurons.
- Spike-timing-dependent learning rule to encode spatiotemporal patterns in a network of spiking neurons.
- Retrieval of spatio-temporal sequence in asynchronous neural network.
- Hebbian Imprinting and Retrieval in Oscillatory Neural Networks
- Self-consistent signal-to-noise analysis and its application to analogue neural networks with asymmetric connections
- Statistical neurodynamics of associative memory
- EFFECT OF RANDOM SYNAPTIC DILUTION IN OSCILLATOR NEURAL NETWORKS
- Phase Locking in a Network of Neural Oscillators
- Why spikes? Hebbian learning and retrieval of time-resolved excitation patterns
- Spin-glass models of neural networks.
Cited by
- A Biological Gradient Descent for Prediction Through a Combination of STDP and Homeostatic Plasticity
- Learning of spatiotemporal patterns in Ising-spin neural networks: analysis of storage capacity by path integral methods.
- Associative memory of phase-coded spatiotemporal patterns in leaky Integrate and Fire networks
- Effects of Poisson noise in a IF model with STDP and spontaneous replay of periodic spatiotemporal patterns, in absence of cue stimulation
- The role of spatiotemporal correlations in the encoding and retrieval of synaptic patterns by STDP in recurrent spiking networks
- Encoding and Replay of Dynamic Attractors with Multiple Frequencies: Analysis of a STDP Based Learning Rule
- Information capacity of a network of spiking neurons
- Capacity, Fidelity, and Noise Tolerance of Associative Spatial-Temporal Memories Based on Memristive Neuromorphic Networks
- Attractor networks and memory replay of phase coded spike patterns
- Effects of Pruning on Phase-Coding and Storage Capacity of a Spiking Network
- Dynamics and storage capacity of neural networks with small-world topology
- Dynamics and storage capacity of cortical networks with small-world topology
- Critical Behavior and Memory Function in a Model of Spiking Neurons with a Reservoir of Spatio-Temporal Patterns
- Spike-Timing-Dependent Synaptic Plasticity to Learn Spatiotemporal Patterns in Recurrent Neural Networks
- Frontiers in Synaptic Neuroscience Synaptic Neuroscience Storage of Phase-coded Patterns via Stdp in Fully-connected and Sparse Network: a Study of the Network Capacity
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