Journal: Nature Communications
Article Title: Molecular layer interneurons in the cerebellum encode for valence in associative learning
doi: 10.1038/s41467-020-18034-2
Figure Lengend Snippet: a go–no go task. Left: Two-photon imaging of a head-fixed mouse responding to odorants by licking on a water spout in response to the rewarded odorant in the go–no go task. Center: Scoring of decision-making. Right: time course of the trial. For water reward in Hit trials the animal must lick at least once in each of the two 2 s lick segments. b – d The panels in b and c show two-photon microscopy images of GCaMP6f fluorescence recorded from MLIs in a mouse proficient in the go–no go task (basal activity: before trial start, Hit trial: during reinforced odorant application). The color image in d shows the regions of interest identified using CaImAn software . e Pseudocolor plots displaying the average per trial Δ F / F time course for Hit (left panel) and CR (right panel) odorants for all ROIs in this example. GLM analysis involving time periods pre-odorant (1 s before odorant onset), odorant (last second during odorant application) and reinforcement (1.5 s after reinforcement), and different events (Hits, Miss, CR and FA) yielded significant differences between reinforcement and pre-odorant ( p < 0.001), between odorant and pre-odorant ( p < 0.001), and between all interactions between these two period pairs and all events ( p < 0.01, 2040 observations, 2028 degrees of freedom, n = 170 ROIs, 1 mouse, GLM F-statistic 234, p < 0.001). *Post-hoc ranksum p < pFDR = 0.048. f Neural ensemble activity. Black traces are the GCaMP6f fluorescence (Δ F / F ) time courses for a subset of the ROIs identified in the FOV in ( d ). This mouse was proficient (≥80% correct trials). Vertical lines: orange start and end of S+ odorant application, light blue is S−. The blue trace at the bottom shows the licks. All trials were Hits or CRs with the exception of the trial identified with the arrow that was a FA. Data shown in panels ( b – f ) are from one session (one mouse).
Article Snippet: The data were then analyzed with CaImAn Matlab software that uses constrained nonnegative matrix factorization to define independent spatial and temporal components corresponding to changes in GCaMP fluorescence in individual MLIs .
Techniques: Imaging, Microscopy, Fluorescence, Activity Assay, Software
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