Removing direct photocurrent artifacts in optogenetic connectivity mapping data via constrained matrix factorization

• DOI: 10.1371/journal.pcbi.1012053
• Publication Date: 2024-05-06T18:04:39Z
• Authors: Benjamin Antin; Masato Sadahiro; Marta Gajowa; Marcus A. Triplett; Hillel Adesnik; Liam Paninski
• Keywords: Photocurrent

Monosynaptic connectivity mapping is crucial for building circuit-level models of neural computation. Two-photon optogenetic stimulation, when combined with whole-cell recording, enables large-scale physiological circuit parameters. In this experimental setup, recorded postsynaptic currents are used to infer the presence and strength connections. For many cell types, nearby connections those we expect be strongest. However, expresses opsin, optical excitation cells can induce direct photocurrents in cell. These photocurrent artifacts contaminate synaptic currents, making it difficult or impossible probe cells. To overcome problem, developed a computational tool, Photocurrent Removal Constraints (PhoRC). Our method based on constrained matrix factorization model which leverages fact that kinetics less variable than currents. We demonstrate real simulated data PhoRC consistently removes while preserving despite variations across datasets. allows discovery would have been otherwise obscured by artifacts, may thus reveal more complete picture connectivity. runs faster time available as open source software.