NetSAP

Neuroscience
Python
Data-driven method for unsupervised identification of states from multi-neuron voltage recordings.
Published

January 1, 2019

NetSAP (Network States And Pathways) is a data-driven analysis method developed during my Ph.D. that recognizes multi-neuron voltage patterns (states). It infers the underlying functional neural network in a time-resolved manner with a sliding window approach, then identifies states from a reordering of the time series of inferred networks.

NetSAP outperforms PCA and k-means clustering on simulated recordings of 50 neurons, and is robust for networks with up to about 50% of the neurons spiking randomly.

Publication

Garolini D, et al. Journal of Neuroscience Methods, 318:104–117, 2019.