Fig. 5: Transformation of the functional connectivity of layer 2-3 network during motor learning and the role of ventral tegmental area (VTA) dopaminergic projections to M1 in the process.
a Schematic illustration of the analysis pipeline. Construction of correlation matrices of the activity between pairs of neurons per trial, used to evaluate the Riemannian centroid representing the functional connectivity of the network in a given training session. b Example of a two-dimensional diffusion embedding of trial-based correlation matrices (each dot represents a trial and colors indicate the training sessions) and their Riemannian centroids (black diamond) for a control (left) mouse and a manipulated mouse (right, CNO sessions 2, 3, 4). c A schematic description of subsequent analysis in three levels: Micro, Riemannian similarity accounting for pairwise relations between all ROI pairs; Mezzo, degree calculation expressing the strength of connectivity of each cell to all other cells; Macro, mean degree expressing the global connectivity of the network. d Riemannian similarity extracted from centroid matrices across different training sessions. Left, heat maps indicate similarity between pairwise sessions, averaged across animals. Right, Riemannian similarity (mean ± SEM) comparing all training sessions to the 7th session, for the control group. e Same as D for the manipulated group. f Same as D for degree vectors through training sessions for control group. g Same as F for the manipulated group. For D-G, dots are population data (per animal), orange and blue are mean ( ± SEM) across animals, n = 12 for controls and n = 10 for manipulated mice. See also supplementary fig. 7. Shaded data in the blue box indicate the manipulated session. Source data are provided as a Source Data file.
