Learning Real-World Stimuli in a Neural Network with Spike-Driven Synaptic Dynamics

No abstract is available for this paper.

• Publication year

  2007

• Venue

  Neural Computation

• Publication date

  2007-11-01

• Fields of study

  Biology, Medicine, Computer Science

• Identifiers
  DOI 10.1162/neco.2007.19.11.2881PMID 17883345
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Perceptrons

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• Real-Time Classification of Complex Patterns Using Spike-Based Learning in Neuromorphic VLSI

  2009cited by this paper
• Phenomenological models of synaptic plasticity based on spike timing

  2008cited by this paper
• Spike-based learning in VLSI networks of integrate-and-fire neurons

  2007cited by this paper
• Limits on the memory storage capacity of bounded synapses

  2007cited by this paper
• Eluding oblivion with smart stochastic selection of synaptic updates.

  2006cited by this paper
• An aVLSI recurrent network of spiking neurons with reconfigurable and plastic synapses

  2006cited by this paper
• A VLSI spike-driven dynamic synapse which learns only when necessary

  2006cited by this paper
• The tempotron: a neuron that learns spike timing–based decisions

  2006cited by this paper
• Learning in realistic networks of spiking neurons and spike‐driven plastic synapses

  2005cited by this paper
• What Can a Neuron Learn with Spike-Timing-Dependent Plasticity?

  2005cited by this paper
• Stochastic properties of synaptic transmission affect the shape of spike time-dependent plasticity curves.

  2005cited by this paper
• Cascade models of synaptically stored memories.

  2005cited by this paper
• Multiple views of the response of an ensemble of spectro-temporal features support concurrent classification of utterance, prosody, sex and speaker identity

  2005cited by this paper
• Learning Only When Necessary: Better Memories of Correlated Patterns in Networks with Bounded Synapses

  2005influential reference
• Convergence of stochastic learning in perceptrons with binary synapses.

  2005cited by this paper
• Minimal Models of Adapted Neuronal Response to In VivoLike Input Currents

  2004cited by this paper
• Intracortical mechanism of stimulus-timing-dependent plasticity in visual cortical orientation tuning.

  2004cited by this paper
• Spike-Timing-Dependent Plasticity: The Relationship to Rate-Based Learning for Models with Weight Dynamics Determined by a Stable Fixed Point

  2004cited by this paper
• How the Shape of Pre- and Postsynaptic Signals Can Influence STDP: A Biophysical Model

  2004cited by this paper
• Optimal information storage and the distribution of synaptic weights: perceptron versus Purkinje cell.

  2004cited by this paper
• Neocortical pyramidal cells respond as integrate-and-fire neurons to in vivo-like input currents.

  2003cited by this paper
• An adaptive silicon synapse

  2003cited by this paper
• Best practices for convolutional neural networks applied to visual document analysis

  2003influential reference
• Spike-Driven Synaptic Dynamics Generating Working Memory States

  2003cited by this paper
• Reversal and Stabilization of Synaptic Modifications in a Developing Visual System

  2003cited by this paper
• Modelling the formation of working memory with networks of integrate-and-fire neurons connected by plastic synapses.

  2003influential reference
• Spike-driven Synaptic Plasticity for Learning Correlated Patterns of Mean Firing Rates

  2003influential reference
• Learning rules and network repair in spike-timing-based computation networks

  2003cited by this paper
• Spike-Based Synaptic Plasticity and the Emergence of Direction Selective Simple Cells: Mathematical Analysis

  2003influential reference
• A model of spike-timing dependent plasticity: one or two coincidence detectors?

  2002cited by this paper
• Context-enabled learning in the human visual system

  2002cited by this paper
• Neuromorphic Bisable VLSI Synapses with Spike-Timing-Dependent Plasticity

  2002cited by this paper
• Spike-timing-dependent synaptic modification induced by natural spike trains

  2002cited by this paper
• Neuromorphic Bistable VLSI Synapses with Spike-Timing-Dependent Plasticity

  2002cited by this paper
• Hebbian spike-driven synaptic plasticity for learning patterns of mean firing rates

  2002influential reference
• Probabilistic decision making by slow reverberation in cortical circuits.

  2002cited by this paper
• Shape Matching and Object Recognition Using Shape Contexts

  2002cited by this paper
• Circuits for bistable spike-timing-dependent plasticity neuromorphic VLSI synapses

  2002cited by this paper
• A unified model of NMDA receptor-dependent bidirectional synaptic plasticity

  2002cited by this paper
• Spike-Based Synaptic Plasticity and the Emergence of Direction Selective Simple Cells: Simulation Results

  2002influential reference
• Dynamical model of long-term synaptic plasticity

  2002cited by this paper
• Shape Matching and Object Recognition Using Shape Contexts

  2002cited by this paper
• Attractor Networks for Shape Recognition

  2001influential reference
• Spike-Timing-Dependent Hebbian Plasticity as Temporal Difference Learning

  2001cited by this paper
• Long and short-term synaptic plasticity and the formation of working memory: A case study

  2001cited by this paper
• An Algorithm for Modifying Neurotransmitter Release Probability Based on Pre- and Postsynaptic Spike Timing

  2001cited by this paper
• Stochastic synaptic plasticity in deterministic aVLSI networks of spiking neurons

  2001influential reference
• Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning

  2001cited by this paper
• Rate, timing, and cooperativity jointly determine cortical synaptic plasticity.

  2001influential reference
• A neuromorphic VLSI device for implementing 2D selective attention systems

  2001influential reference
• Long term memory: Encoding and storing strategies of the brain

  2001cited by this paper
• Synaptic plasticity: taming the beast

  2000cited by this paper
• Hebb and homeostasis in neuronal plasticity.

  2000cited by this paper
• Modeling Selective Attention Using a Neuromorphic Analog VLSI Device

  2000cited by this paper
• Timing-based LTP and LTD at vertical inputs to layer II/III pyramidal cells in rat barrel cortex.

  2000cited by this paper
• Equilibrium properties of temporally asymmetric Hebbian plasticity.

  2000cited by this paper
• Spike-Driven Synaptic Plasticity: Theory, Simulation, VLSI Implementation

  2000influential reference
• A pulse-coded communications infrastructure for neuromorphic systems

  1999cited by this paper
• Collective Behavior of Networks with Linear (VLSI) Integrate-and-Fire Neurons

  1999cited by this paper
• A Short Introduction to Boosting

  1999cited by this paper
• Priming-induced shift in synaptic plasticity in the rat hippocampus.

  1999influential reference
• A Computational Model for Visual Selection

  1999cited by this paper
• A critical window for cooperation and competition among developing retinotectal synapses

  1998cited by this paper
• All-or-none potentiation at CA3-CA1 synapses.

  1998cited by this paper
• Slow stochastic Hebbian learning of classes of stimuli in a recurrent neural network.

  1998cited by this paper
• Communicating neuronal ensembles between neuromorphic chips

  1998cited by this paper
• Neuromorphic Systems Engineering

  1998cited by this paper
• Shape Quantization and Recognition with Randomized Trees

  1997cited by this paper
• Regulation of Synaptic Efficacy by Coincidence of Postsynaptic APs and EPSPs

  1997cited by this paper
• A single-transistor silicon synapse

  1996cited by this paper
• A neuronal learning rule for sub-millisecond temporal coding

  1996cited by this paper
• Learning in Neural Networks with Material Synapses

  1994influential reference
• Introduction to the theory of neural computation

  1994cited by this paper
• Memory in the cerebral cortex

  1994cited by this paper
• Constraints on learning in dynamic synapses

  1992cited by this paper
• ASSOCIATIVE MEMORY IN NEURAL NETWORKS WITH BINARY SYNAPSES

  1990cited by this paper
• Neurocomputing: Foundations of Research

  1988cited by this paper
• A memory which forgets

  1986cited by this paper
• Networks of Formal Neurons and Memory Palimpsests

  1986cited by this paper
• Neural networks and physical systems with emergent collective computational abilities.

  1982cited by this paper
• A Theory of Cerebellar Function

  1971cited by this paper
• A theory of cerebellar cortex

  1969cited by this paper
• The perceptron: a model for brain functioning. I

  1962cited by this paper
• The perceptron: a probabilistic model for information storage and organization in the brain.

  1958influential reference

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• A neuromorphic processor with on-chip learning for beyond-CMOS device integration

  2025influential citation
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• Spiking neural networks for autonomous driving: A review

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  2024cites this paper
• Computational models of learning and synaptic plasticity

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  2024cites this paper
• TEXEL: A neuromorphic processor with on-chip learning for beyond-CMOS device integration

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  2023cites this paper
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  2023cites this paper
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  2023cites this paper
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  2023cites this paper
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  2023cites this paper
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  2023cites this paper
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  2023cites this paper
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  2023cites this paper
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  2023cites this paper
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  2023cites this paper
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  2023cites this paper
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  2023influential citation
• Darwin3: A large-scale neuromorphic chip with a Novel ISA and On-Chip Learning

  2023cites this paper
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  2022cites this paper
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  2022cites this paper
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  2022cites this paper
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