IAS-Seminar "Higher brain functions emerging from large scale data-driven modeling of brain regions"

Anfang
19.05.2017 12:00 Uhr
Ende
19.05.2017 13:00 Uhr
Veranstaltungsort
Jülich Supercomputing Centre, Rotunde, Geb. 16.4, R. 301

Referent:

Michele Migliore, Director of the Institute of Biophysics, National Research Council, Palermo, Italy

Abstract:

Understanding the neural basis of brain functions and dysfunctions has a huge impact on a number of scientific, technical, and social fields. Experimental findings have given and continue to give important clues at different levels, from subcellular biochemical pathways to behaviors involving many brain regions. However, most of the underlying mechanisms and the related computational and functional processes are still largely unknown or poorly understood. This mainly depends on the practical impossibility to obtain detailed simultaneous in vivo recordings

from an appropriate set of cells, making it nearly impossible to decipher and understand the emergent properties and behavior of large neuronal networks. We are addressing this problem using large scale computational models of biologically inspired cognitive architectures, which require substantial resources for storage, computing, and scientific visualization that can be available only through large international research infrastructures. In this talk, I will present and discuss the main results and techniques, used in my lab and within the Human Brain Project, to design and use realistic models of neurons and networks implemented following their natural 3D structure. To illustrate our approach and its relevance to understand computational and functional processes, I will show the results obtained for a variety of regions, such as the hippocampus, the olfactory bulb, and the heart. The main goal is to uncover the mechanisms underlying higher brain functions, to help the development of innovative therapies to treat brain diseases. Through movies and interactive simulations, I will show how and why the dynamical interaction among neurons can predict new results and account for a variety of puzzling experimental findings.

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Letzte Änderung: 30.04.2022