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"From whole brain network dynamics to functional connectome" Joana Cabral (Video)
Mini-course
Over the last decade, computer simulations of whole-brain network dynamics have shown that the brain’s complex network structure of long axonal projections connecting brain areas – the so-called structural Connectome - not only mediates long-range communication between brain areas but also shapes brain activity in space and time.
The lecture will be divided in two parts.
Whole-brain network dynamics: models and mechanisms
Whole-brain network dynamics: models and mechanisms
- Over the last decade, computer simulations of whole-brain network dynamics have shown that the brain’s complex network structure of long axonal projections connecting brain areas – the so-called structural Connectome - not only mediates long-range communication between brain areas but also shapes brain activity in space and time. Indeed, using different degrees of biophysical realism, whole-brain network models have revealed the emergence of spatio-temporal patterns similar to the ones captured on a ultra-slow time scale (<0.1Hz) with functional Magnetic Resonance Imaging (fMRI) from human brains. Given their phenomenological value for understanding the physiological mechanisms shaping brain activity at the macroscopic scale, whole-brain network models emerge as powerful tools for linking neuroimaging observations with the underlying biophysical principles, both in health and disease. In the first part of my lecture I will present a whole-brain network developed with my group.
- Growing evidence suggests that functional connectivity at rest is a multi-stable process exhibiting the transient activation of recurrent connectivity patterns. In other words, when evaluated over time, it appears that functional connectivity (FC) passes through multiple relatively stable network configurations rather than varying in a continuous sense. However, due to several methodological limitations, the best way to assess meaningful FC patterns and characterize the transitions between them remains under debate. Recently, new methods have been proposed to analyze FC dynamics at high temporal resolution (i.e. single volume / TR), focusing either on BOLD co-activation patterns, or on BOLD phase coherence patterns. These methods are fundamentally different because while the first considers a functional connection only when the BOLD signals are simultaneously increased, the latter is sensitive to the transient phase synchronization of BOLD signal fluctuations, not distinguishing between co-activations and co-deactivations. In the second part of my lecture, I will demonstrate how to reduce the dimensionality of phase coherence patterns and extract meaningful functional subsystems that appear altered in different neuropychiatric disorders or under the effect of neuromodulators.
Dates
Created on May 16, 2019