Temporally Asymmetric Hebbian Learning, Spike liming and Neural Response Variability
نویسندگان
چکیده
Recent experimental data indicate that the strengthening or weakening of synaptic connections between neurons depends on the relative timing of preand postsynaptic action potentials. A Hebbian synaptic modification rule based on these data leads to a stable state in which the excitatory and inhibitory inputs to a neuron are balanced, producing an irregular pattern of firing. It has been proposed that neurons in vivo operate in such a mode.
منابع مشابه
Learning temporal correlations in biologically-inspired aVLSI
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firing rates to drive learning, this new form of learning involves precise firing times. Hence, such algorithms can capture temporal spike correlations. We present circuits and methods to implement temporally-asymmetric Hebb...
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Recent experimental data indicate that the strengthening or weakening of synaptic connections between neurons depends on the relative timing of preand postsynaptic action potentials. A Hebbian synaptic modification rule based on these data leads to a stable state in which the excitatory and inhibitory inputs to a neuron are balanced, producing an irregular pattern of firing. It has been propose...
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