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Learning brain dynamics for decoding and predicting individual differences

Fig 3

Low-dimensional trajectories.

(A) Trajectories for all clips. Solid line: mean trajectory averaged across participants (line thickness is scaled by variance, which was highest at the end of the clip). All trajectories progressed away from the center (see sample arrows). The inset provides clip abbreviations. (B) Euclidean distance between trajectories. The Euclidean distance between the clip trajectory while watching Home Alone and the mean trajectory across participants for a second clip was computed. The thicker line corresponds to the distance of participants’ Home Alone trajectories to the mean of this clip. The same results are shown for all clips in S1 Fig. (C) Clip prediction accuracy and fraction of variance captured after reconstruction using low-dimensional models. Error bars correspond to the standard error of the mean across participants.

Fig 3

doi: https://doi.org/10.1371/journal.pcbi.1008943.g003