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Optimal spatiotemporal spike pattern detection by STDP (Masquelier 2017)
 
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Model Information
Model File
Accession:
230138
We simulate a LIF neuron equipped with STDP. A pattern repeats in its inputs. The LIF progressively becomes selective to the repeating pattern, in an optimal manner.
Reference:
1 .
Masquelier T (2018) STDP Allows Close-to-Optimal Spatiotemporal Spike Pattern Detection by Single Coincidence Detector Neurons.
Neuroscience
389
:133-140
[
PubMed
]
Citations
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Model Information
(Click on a link to find other models with that property)
Model Type:
Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s):
Abstract integrate-and-fire leaky neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:
MATLAB;
Model Concept(s):
Coincidence Detection;
STDP;
Unsupervised Learning;
Hebbian plasticity;
Long-term Synaptic Plasticity;
Pattern Recognition;
Spatio-temporal Activity Patterns;
Implementer(s):
Masquelier, Tim [timothee.masquelier at alum.mit.edu];
Download the displayed file
/
STDP
src
batch.py
jitter_pattern.m
main.m
mean_perf.m
param.m
perf.m
plots.m
timedLog.m
*
Other models using timedLog.m:
Microsaccades and synchrony coding in the retina (Masquelier et al. 2016)
Optimal Localist and Distributed Coding Through STDP (Masquelier & Kheradpisheh 2018)
Relative spike time coding and STDP-based orientation selectivity in V1 (Masquelier 2012)
STDP allows fast rate-modulated coding with Poisson-like spike trains (Gilson et al. 2011)
timedLogLn.m
*
Other models using timedLogLn.m:
Microsaccades and synchrony coding in the retina (Masquelier et al. 2016)
Optimal Localist and Distributed Coding Through STDP (Masquelier & Kheradpisheh 2018)
Relative spike time coding and STDP-based orientation selectivity in V1 (Masquelier 2012)
STDP allows fast rate-modulated coding with Poisson-like spike trains (Gilson et al. 2011)
function timedLogLn(str) disp(' '); timedLog(str);