2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2012
DOI: 10.1109/embc.2012.6346045
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A superposable silicon synapse with programmable reversal potential

Abstract: Abstract-We present a novel log-domain silicon synapse designed for subthreshold analog operation that emulates common synaptic interactions found in biology. Our circuit models the dynamic gating of ion-channel conductances by emulating the processes of neurotransmitter release-reuptake and receptor binding-unbinding in a superposable fashion: Only a single circuit is required to model the entire population of synapses (of a given type) that a biological neuron receives. Unlike previous designs, which are str… Show more

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Cited by 11 publications
(4 citation statements)
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References 14 publications
(24 reference statements)
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“…Conductance-based synapses, active conductances, multiple dendritic compartments, spike back-propagation, and cortical cell types have been emulated in neuromorphic chips 29,[38][39][40][41][42][43][44][45] . Our focus here was on the next step: Deploying these in silico neuronal components in multiscale modeling.…”
Section: Discussionmentioning
confidence: 99%
“…Conductance-based synapses, active conductances, multiple dendritic compartments, spike back-propagation, and cortical cell types have been emulated in neuromorphic chips 29,[38][39][40][41][42][43][44][45] . Our focus here was on the next step: Deploying these in silico neuronal components in multiscale modeling.…”
Section: Discussionmentioning
confidence: 99%
“…Nearly every major research area in the DOE mission was affected by machine learning in the last decade. Today these applications run on existing parallel computers; however, as problems ale and dataset sizes increase, there will be huge opportunities for deep learning on neuromorphic hardware to make a serious impact in science and technology [27][28][29][30][31]. Neuromorphic computing may even play a role in replacing existing numerical methods where lower power functional approximations are used and could directly augment planned Exascale architectures [37, 38, 39, and 40].…”
Section: Neuromorphic Computingmentioning
confidence: 99%
“…This phenomenological description of synaptic current is of paramount importance in implementing the experimentally observed phenomenon of shunting or silent inhibition. A few [3,5,6] synaptic circuits incorporate the effect of synaptic reversal potential but their implementation is not biomimetic as the current generated in these circuits is unidirectional. In addition to incorporating this effect, special emphasis has been put in the design to minimize the static power consumption of the synaptic circuit.…”
Section: Introductionmentioning
confidence: 99%