Figure 2.

State-dependence of spontaneous cortical propagation. (A) Imaging field with a 464-channel photodiode array covering V1 and V2M. Selected detectors within V1 are highlighted in yellow. (B) Representative single-trial examples of spontaneous cortical waves obtained by VSD imaging. Vertical lines and lower-case labels indicate time periods for which frames are drawn. Inset frames: frames show propagation of activity within the imaging field (normalized scale, variable scaling). Note that in the desynchronized state, propagation patterns are more spatially fragmented as compared to the synchronized state. Black contour frames: Rose plots indicating flow trajectories for each example wave a-f as obtained by the temporospatial correlation algorithm described below (arbitrary scaling). (C) Local velocity of lateral propagation of spontaneous cortical waves as obtained by a temporospatial correlation algorithm applied to a hexagonal ring of detectors as indicated in A. Data from a representative animal are shown. Note that spontaneous waves in the desynchronized state tend to propagate faster than spontaneous waves in the synchronized state. (D) Statistical evaluation of the state-dependence of propagation velocity indicated in C. Medians of the respective non-Gaussian distributions from nine animals are shown (circles). Different colors indicate different animals. Means of the medians are indicated by black rectangles (± SEM). Matched-pairs signed-ranks test (**p < 0.02). (E) Rose histograms showing propagation preferences of spontaneous cortical waves (colored outlines, same color coding by animal as in D). Histograms were normalized to the maximum bin count for each state separately. Detectors were the same as in C. Note that the average flow histogram (transparent blue and red) indicates highly anisotropic propagation in both states, the axis of which is approximately equivalent in both states. The preferred trajectories of propagation within that axis are clearly state-dependent (Kuiper’s test, *** p < 0.001 for every animal).

Wanger et al. BMC Neuroscience 2013 14:78   doi:10.1186/1471-2202-14-78
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