You are cordially invited to the SCL seminar of the Center for the Study
of Complex Systems, which will be held on Thursday, 10 October 2019 at
14:00 in the library reading room “Dr. Dragan Popović” of the Institute
of Physics Belgrade. The talk entitled
Computational Modeling of the Brain & Hidden Structure of Human
Connectomes
will be given by Prof. Dr. Bosiljka Tadić (Department of Theoretical
Physics, Jozef Stefan Institute Ljubljana, Slovenia and Complexity
Science Hub, Vienna, Austria).
ABSTRACT OF THE TALK:
The modern science of the brain explores how the brain’s anatomical
parts and complex pathways between them govern human activity,
psychology and behaviour. A network that maps the organization of
neuronal connections between brain regions is known as the human
connectome. Currently, a large amount of experimental data has been
collected within the Human Connectome Project (HCP) to enable different
aspects of brain research. However, the procedure to extract the
network from the fMRI or another brain imaging methods, as well as the
analysis of whole-brain networks, requires specific computational
modelling approaches. In this seminar, we briefly review the necessary
procedures preceding the construction of a brain network and describe
some parameters that affect the outcome. Further, we discuss in detail
[1] the consensus connectomes, that we generate for a specified set of
parameters on the Budapest Conenctome Server [2] based on HCP data. By
analyzing higher-order connections, we show how the consensus
connectomes of female subjects systematically differ from the one for
male subjects. Meanwhile, their standard graph-theoretic properties
remain self-similar. These robust gender differences within the
higher-order connectivity in human brain networks imply their different
functional properties; whereas, the understanding of the origin and
interpretation of these differences remain beyond the mathematical
modelling framework.
[1] B. Tadić, M. Andjelković, R. Melnik, Functional geometry of human
connectomes, Scientific Reports 9:12060 (2019).
[2] B. Szalkai, C. Kerepesi, B. Varga, V. Grolmusz, Parameterizable
Consensus Connectomes from the Human Connectome Project: The Budapest
Reference Connectome Server v3.0, Cognitive Neurodynamics, (2016).