Behavioral simulation and synthesis of biological neuron systems using synthesizable VHDL [PDF]
, 2011 Neurons are complex biological entities which form the basis of nervous systems. Insight can be gained into neuron behavior through the use of computer models and as a result many such models have been developed. However, there exists a trade-off between
Wilson, P.R. +7 more
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A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity [PDF]
, 2006 Indiveri G, Chicca E, Douglas RJ. A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity. IEEE Transactions on Neural Networks.
Rodney Douglas +5 more
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Effects of direct current stimulation on synaptic plasticity in a single neuron
Brain Stimulation, 2021 Background: Transcranial direct current stimulation (DCS) has lasting effects that may be explained by a boost in synaptic long-term potentiation (LTP). We hypothesized that this boost is the result of a modulation of somatic spiking in the postsynaptic ...
Forouzan Farahani +4 more
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Artificial cognitive systems: From VLSI networks of spiking neurons to neuromorphic cognition [PDF]
, 2009 Neuromorphic engineering (NE) is an emerging research field that has been attempting to identify neural types of computational principles, by implementing biophysically realistic models of neural systems in Very Large Scale Integration (VLSI) technology.
Douglas, R J +8 more
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Natural gradient learning for spiking neurons [PDF]
Proceedings of the Neuro-inspired Computational Elements Workshop, 2020 In many normative theories of synaptic plasticity, weight updates implicitly depend on the chosen parametrization of the weights. This problem relates, for example, to neuronal morphology: synapses which are functionally equivalent in terms of their impact on somatic firing can differ substantially in spine size due to their different positions along ...
Kreutzer, Elena +2 more
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A biophysically accurate floating point somatic neuroprocessor [PDF]
, 2009 Biophysically accurate neuron models have emerged as a very useful tool for neuroscience research. These models are based on solving differential equations that govern membrane potentials and spike generation.
Edward Regan +9 more
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Extracting non-linear integrate-and-fire models from experimental data using dynamic I–V curves [PDF]
, 2008 The dynamic I–V curve method was recently introduced for the efficient experimental generation of reduced neuron models. The method extracts the response properties of a neuron while it is subject to a naturalistic stimulus that mimics in vivo-like ...
Wulfram Gerstner +11 more
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An Ultrasonic Filterbank with Spiking Neurons [PDF]
2005 IEEE International Symposium on Circuits and Systems, 2005 To support our ongoing work in modeling bat echolocation, a binaural, ultrasonic cochlea-like filter bank has been designed with moderate quality (Q) factor (as high as 65) with spiking neurons that are driven by the filter outputs. The neuron addresses are reported off chip at the time of the spike in an unarbitrated fashion and in current-mode to ...
Timothy K. Horiuchi, Hisham Abdalla
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Maximum likelihood decoding of neuronal inputs from an interspike interval distribution [PDF]
, 2009 An expression for the probability distribution of the interspike interval of a leaky integrate-and-fire (LIF) model neuron is rigorously derived, based on recent theoretical developments in the theory of stochastic processes.
You, Gongqiang +3 more
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Dynamical Mean Field approximation of a canonical cortical model for studying inter-population synchrony [PDF]
, 2011 The goal of this paper is twofold. We propose and explore a model to study the synchronization among populations in the canonical model of the neocortex proposed previously by (R.J. Douglas, K.A.C. Martin, A functional microcircuit for cat visual cortex.
Roberto Carlos Sotero Diaz +2 more
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