Sergio Pequito, Asst. Professor, Industrial & Systems Engineering, RPI

Sergio Pequito, Asst. Professor, Industrial & Systems Engineering, RPI

In this talk, I will address one fundamental problem in the interface between neuroscience, network science, and dynamics and control systems. Specifically, we address the problem of understanding the relationship between the dynamics of neural processes and the anatomical substrate of the brain -- a central question in neuroscience. On the one hand, modern neuroimaging technologies, such as diffusion tensor imaging, can be used to construct structural graphs representing the architecture of white matter streamlines crisscrossing the cortex.

On the other hand, temporal patterns of neural activity can be used to construct functional graphs representing temporal correlations between brain regions. Although some studies provide evidence that whole-brain functional connectivity is shaped by underlying anatomy, the observed relationship between function and structure is weak, and the rules by which anatomy constrains the brain’s dynamics remains a mystery. Therefore, we introduce a high accuracy methodology to predict the functional connectivity of a subject at rest from his or her structural graph and unveil the role of indirect structural paths in the formation of functional correlations.

Next, we provide an overview of future challenges to be addressed, and how the outcome of this research can generate a paradigm shift. This paradigm will impact the way that analysis is conducted in neuroscience, and in brain-comper and brain-machine-brain interfaces. Furthermore, it will lead to new diagnostics and treatments of neural disorders, that ultimately will improve people’s life quality.


Download the paper here.