Phenomenological spiking model of the cat early visual system. We show how natural vision can drive spike time correlations on sufficiently fast time scales to lead to the acquisition of orientation-selective V1 neurons through STDP. This is possible without reference times such as stimulus onsets, or saccade landing times. But even when such reference times are available, we demonstrate that the relative spike times encode the images more robustly than the absolute ones.
Model Type: Realistic Network; Synapse
Cell Type(s): Thalamus geniculate nucleus/lateral principal GLU cell; Neocortex L2/3 pyramidal GLU cell; Retina ganglion GLU cell; Retina photoreceptor cone GLU cell; Retina bipolar GLU cell; Abstract integrate-and-fire leaky neuron
Receptors: AMPA
Model Concept(s): Pattern Recognition; Coincidence Detection; Temporal Pattern Generation; Synchronization; Spatio-temporal Activity Patterns; Synaptic Plasticity; Long-term Synaptic Plasticity; Action Potentials; Learning; Unsupervised Learning; Winner-take-all; STDP; Development; Information transfer; Orientation selectivity; Vision
Simulation Environment: C or C++ program; MATLAB
Implementer(s): Masquelier, Tim [timothee.masquelier at alum.mit.edu]
References:
Masquelier T. (2012). Relative spike time coding and STDP-based orientation selectivity in the early visual system in natural continuous and saccadic vision: a computational model. Journal of computational neuroscience. 32 [PubMed]