  A critical question for cognitive neuroscience regards how transitions
between cognitive states emerge from the dynamic activity of functional brain
networks. However, current methodologies cannot easily evaluate both the
spatial and temporal changes in brain networks with cognitive state. Here we
combine a simple data reorganization with spatial ICA, enabling a
spatiotemporal ICA (stICA) which captures the consistent evolution of networks
during onset and offset of a task. The technique was applied to FMRI datasets
involving alternating between rest and task and to simple synthetic data.
Starting and finishing time-points of periods of interest (anchors) were
defined at task block onsets and offsets. For each subject, the ten volumes
following each anchor were extracted and concatenated spatially, producing a
single 3D sample. Samples for all anchors and subjects were concatenated along
the fourth dimension. This 4D dataset was decomposed using ICA into
spatiotemporal components. One component exhibited the transition with task
onset from a default mode network (DMN) becoming less active to a
fronto-parietal control network (FPCN) becoming more active. We observed other
changes with relevance to understanding network dynamics, e.g., the DMN showed
a changing spatial distribution, shifting to an anterior/superior pattern of
deactivation during task from a posterior/inferior pattern during rest. By
anchoring analyses to periods associated with the onsets and offsets of task,
our approach reveals novel aspects of the dynamics of network activity
accompanying these transitions. Importantly, these findings were observed
without specifying a priori either the spatial networks or the task time
courses.
