Optimal spatiotemporal spike pattern detection by STDP (Masquelier 2017)

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.

Model Type: Neuron or other electrically excitable cell

Cell Type(s): Abstract integrate-and-fire leaky neuron

Model Concept(s): Coincidence Detection; STDP; Unsupervised Learning; Hebbian plasticity; Long-term Synaptic Plasticity; Pattern Recognition; Spatio-temporal Activity Patterns

Simulation Environment: MATLAB

Implementer(s): Masquelier, Tim [timothee.masquelier at alum.mit.edu]


Masquelier T. (2018). STDP Allows Close-to-Optimal Spatiotemporal Spike Pattern Detection by Single Coincidence Detector Neurons. Neuroscience. 389 [PubMed]

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