Tatjana Tchumatchenko (Max Planck Institute for Brain Research, Frankfurt am Main) | Inference of synaptic connectivity and input profiles from contrast invariant firing rates

Abstract

Despite recent technological advances in the development of experimental methods, understanding the functional connectivity in neural circuits remains one of the major challenges in neurobiology. Neural firing rates and their dependence on external inputs can be measured in individual neurons or neural populations. However, how exactly neural firing rates are determined by recurrent interactions with local surrounding neurons and feed-forward inputs from distant upstream cortical areas is difficult to investigate with the state-of-the-art experimental methods. We present a theoretical approach which enables to infer effective synaptic connectivity and input profiles from the firing rates of a recurrent neural network.