Fig. 2: Using Canonical Correlation Analysis (CCA) to capture population interactions.
a Relating activity across two neuronal populations. Each circle represents the population activity recorded on a given trial. For each activity point observed in the V1 population (left panel; gray dots), there is a corresponding, simultaneously recorded activity point observed in V2 (right panel, gray dots). The red axes represent the first pair of canonical dimensions, identified using CCA. Neuronal activity projected onto the first pair of canonical dimensions (red dots) is highly correlated across the two areas (bottom panel). b Spike counts across the recorded neurons are taken in specified time windows (gray boxes), which may either be positioned at the same time in both areas (i.e., t1 = t2) or with a delay between areas (t1 ≠ t2). The activity in each gray box is represented by a circle in panel (a). c The population correlation function corresponds to the correlation between areas returned by CCA (the correlation associated with the first pair of canonical dimensions), as a function of the time delay between areas (t2 − t1).
