Regensburg 2019 – scientific programme

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SYCZ: Symposium Czech Republic as Guest of Honor

SYCZ 1: Czech Republic as Guest of Honor

SYCZ 1.5: Invited Talk

Thursday, April 4, 2019, 11:45–12:15, H4

Occam's razor and complex networks from brain to climate — •Jaroslav Hlinka — Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic

Brain dynamics constitute one of the archetypal complex systems showing a plethora of rich emergent phenomena. To understand the mechanisms behind the observed properties, computational modeling and sophisticated data analysis approaches are increasingly adopted. However, the complexity of the applied approaches may lead into a new set of problems related to the ambiguity of the appropriate interpretation of the analysis or modeling results. In such cases, it may be suitable to apply the general heuristic principle of parsimony, known as the Occam's razor. In this contribution we shall demonstrate how some rich and complex properties of brain dynamics and connectivity structure can be explained from relatively simple principles and models such as purely linear stochastic dynamics. The specific examples include small-world property of brain networks [1], detecting brain states [2] and (non)linear network inference utility [3]. Relevance to other complex systems (climate dynamics, stock networks) will be highlighted on examples.

[1] Hlinka, J. et al., M. Small-world bias of correlation networks: From brain to climate Chaos, 2017, 27, 035812

[2] Hlinka, J. & Hadrava, M. On the danger of detecting network states in white noise. Front. Comp. Neurosci., 2015, 9, 11

[3] Hlinka, J. et al. Functional connectivity in resting-state fMRI: Is linear correlation sufficient? NeuroImage, 2011, 54, 2218-2225