Compressive sensing of functional connectivity maps from patterned optogenetic stimulation of neuronal ensembles

Mapping functional connectivity between neurons is an essential step toward probing the neural computations mediating behavior. Accurately determining synaptic maps in populations of challenging terms yield, accuracy, and experimental time. Here, we developed a compressive sensing approach to reconstruct based on random two-photon cell-targeted optogenetic stimulation membrane voltage readout many putative postsynaptic neurons. Using biophysical network model interconnected excitatory inhibitory neurons, characterized mapping recall precision as function observability, sparsity, number stimulated, off-target stimulation, reliability, propagation latency, topology. We found that can be achieved with far fewer measurements than standard pairwise sequential approach, sparsity reliability serving primary determinants performance. Our results suggest rapid efficient method sparsely connected neuronal networks.