Fig. 7

Fig. 7

Population Analysis of Global Zebrafish CNS Activity Recorded by SPED Light Sheet Microscopy

Principal component analysis (PCA) and independent component analysis (ICA) were used to analyze the population dynamics of neurons spread across the entire zebrafish larval CNS. The dataset was acquired using a 4×/0.28 NA objective at 6.23 volumes/sec (as in Figure 6A). ΔF/F activity profiles of all cells were first filtered to identify active neurons by choosing a noise level corresponding to 5% false positive rate as the cutoff, followed by PCA and ICA; early time points that may represent nonspecific responses to initial laser illumination were excluded from analysis.

(A) Number of co-active neurons as a function of time across the recording duration.

(B) Temporal traces of top three principal components (PC) shown in red, green and magenta respectively. y axis represents arbitrary units in PCA space.

(C) Temporal traces of 6 recovered independent components (IC) out of 10 (filtered to retain traces in which the sum of minimum and maximum values was greater than zero); units are arbitrary. The dotted lines across panels indicate peaks in the ICs that correspond to the peaks in PCA and cellular activity.

(D) Eigenvalues for the top 100 dimensions of cellular (top) and time points (bottom) principal components. Dashed lines mark the top 3 cellular and the top 20 temporal PCA dimensions, which were used in (B) and for data “whitening” before ICA (methods) in (C).

(E) Spatial plots of each PC coefficient (absolute value) and each IC (absolute value) were generated to visualize the locations and identities of the neurons associated with each component.

Different components were combined into multi-color images (each color corresponding to coloring of the temporal traces in B and C) after scaling for contrast. Images shown are maximum intensity projections through x, y or z. Fb, Forebrain; Mb, midbrain, Hb, Hindbrain.