Back

Raster photostimulation of large-scale neural populations

LaFosse, P. K.; Flickinger, D.; Jaindl, G.; Drinnenberg, A.; Grodem, S.; Lensjo, K. K.; Ramakrishnan, C.; Siverts, L.; Zeng, H.; Tasic, B.; Daigle, T. L.; Fyhn, M.; Deisseroth, K. L.; Stringer, C.; Pachitariu, M.

2026-04-24 neuroscience
10.64898/2026.04.21.719951 bioRxiv
Show abstract

Neural computations are implemented by distributed neural populations that often span multiple brain areas. Causal photo-activation experiments done simultaneously with neural recordings can greatly improve our understanding of these computations, but such methods are typically limited to small subsets of neurons in restricted fields of view. Here we describe a new system called raster photostimulation for photo-activating and recording thousands of neurons, over a short 300 ms time window and over a large 5 mm field-of-view on a two-photon mesoscope. The photo-activation is precisely matched to the neural recording configuration, as it uses the same optical path, although with a different laser that is independently gated. We demonstrate pixel-level precision, frame-by-frame mask updating, and single-frame photostimulation of thousands of neurons. While this method lacks the precise temporal control of alternative methods, it compensates with ease-of-use, spatial precision, cost of implementation and by pushing the limits on the number of near-simultaneously stimulated neurons.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.