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Published in 2018 at "Scientific Reports"
DOI: 10.1038/s41598-018-28999-2
Abstract: Spiking networks that perform probabilistic inference have been proposed both as models of cortical computation and as candidates for solving problems in machine learning. However, the evidence for spike-based computation being in any way superior…
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Keywords:
synaptic plasticity;
short term;
spiking networks;
term synaptic ... See more keywords
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Published in 2020 at "PLoS Computational Biology"
DOI: 10.1371/journal.pcbi.1008261
Abstract: An important problem in computational neuroscience is to understand how networks of spiking neurons can carry out various computations underlying behavior. Balanced spiking networks (BSNs) provide a powerful framework for implementing arbitrary linear dynamical systems…
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Keywords:
synaptic delays;
spiking networks;
realistic synaptic;
balanced spiking ... See more keywords
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Published in 2023 at "PLOS Computational Biology"
DOI: 10.1371/journal.pcbi.1011097
Abstract: Neural computations emerge from local recurrent neural circuits or computational units such as cortical columns that comprise hundreds to a few thousand neurons. Continuous progress in connectomics, electrophysiology, and calcium imaging require tractable spiking network…
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Keywords:
network;
spiking networks;
recurrent neural;
targeting operational ... See more keywords
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Published in 2021 at "eLife"
DOI: 10.7554/elife.66273
Abstract: Continuous adaptation allows survival in an ever-changing world. Adjustments in the synaptic coupling strength between neurons are essential for this capability, setting us apart from simpler, hard-wired organisms. How these changes can be mathematically described…
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Keywords:
evolving interpretable;
plasticity;
spiking networks;
plasticity rules ... See more keywords