Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI
Fig 8
Exemplary DS reconstruction in a sample subject.
A. Top: Latent trajectories generated by the prior model projected down to the first 3 principle components for visualization purposes in a model including external inputs and M = 6 latent states. Task separation is clearly visible in the generated state space (color-coded as in the legend), i.e. different cognitive demands are associated with different regions of state space (hard step-like changes in state are caused by the external inputs). Bottom: Observed time series (black) and their predictions based on the generated trajectories (red, with 90% CI in grey) for the same subject. See also S1 Video. B. Same as A for the same subject in a PLRNN without external inputs. *BA = Brodmann area, Le/Re = left/right, CRT = choice reaction task, CDRT = continuous delayed response task, CMT = continuous matching task.