AuthorsM. E. Lepperød, T. Stöber, T. Hafting, M. Fyhn and K. Kording
TitleInferring causal connectivity from pairwise recordings and optogenetics
AfilliationScientific Computing
Project(s)Department of Computational Physiology
StatusSubmitted
Publication TypeJournal Article
Year of Publication2018
JournalbioRxiv
PublisherCold Spring Harbor Laboratory
Abstract

To study how the brain works, it is crucial to identify causal interactions between neurons, which is thought to require perturbations. However, when using optogenetics we typically perturb multiple neurons, producing a confound - any of the stimulated neurons can have affected the postsynaptic neuron. Here we show how this produces large biases, and how they can be reduced using the instrumental variable (IV) technique from econometrics. The interaction between stimulation and the absolute refractory period produces a weak, approximately random signal which can be exploited to estimate causal connectivity. When simulating integrate-and-fire neurons, we find that estimates from IV are better than naive techniques (R2=0.77 vs R2=0.01). The difference is important as the estimates disagree when applied to experimental data from stimulated neurons with recorded spiking activity. Presented is a robust analysis framework for mapping out network connectivity based on causal neuron interactions.

URLhttps://www.biorxiv.org/content/early/2018/11/20/463760
DOI10.1101/463760
Citation Key26313