gaiasilvestri/v1macrocolumns
MATLAB simulation of a v1 macrocolumn. The program allows you to set the connectivity of the macrocolumn as random, or as a distribution of one or more motifs. The network undergoes STDP changes.
A Matlab iterative version of Tarjan's algorithm to find strongly connected components in a directed graph (linear time). The input is an adjacency matrix, where non-zero cells indicate a synaptic connection in the neural network represented.
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MATLAB simulation of a v1 macrocolumn. The program allows you to set the connectivity of the macrocolumn as random, or as a distribution of one or more motifs. The network undergoes STDP changes.
This MATLAB program displays the number of reciprocal connections in a spiking neural network as synapses get increasingly added amongst its neurons.
A spiking neural network undergoes plastic changes based on the timing of neural spikes (MATLAB).
Modification of Izhikevich's spiking neural network model into a sparse motifs based network. The neurons in this network are connected as "bifan" motifs, not following random connectivity. We plot the LFP and firings of the spiking neural network.