When: 12 PM, noon.
A major question for neuroscience concerns understanding the dynamics of neuronal networks. In human neuroscience one of the most widely used tools to examine neural networks is fMRI. Although this tool has successfully revealed static images of whole-brain neural networks, it has been limited in revealing their whole-brain temporal dynamics. Here we introduce a new analytical technique that yields a dynamic view of whole-brain fMRI activity. This new method differs radically from the existing gold-standard method in that it permits a high temporal-resolution view of the fMRI signal. We present a validation of the method and an illustration of some exploratory results.
Specifically, we collected data from 30 participants doing a visual language task (picture naming) interspersed with resting trials in a
slow event-related design. We show that both statistical maps representing static network activity as well as information about the
dynamics of the fMRI signal do not quantitatively differ from those obtained with gold standard methods. We further illustrate the utility
of the new technique by revealing the whole-brain dynamics of network activity underlying the naming of a picture, the dynamics of spontaneous resting state activity, and the dynamical transition from resting state to naming network, all at high temporal-resolutions.