Welcome to the website of the complex networks and brain dynamics group. The workgroup is a part of the Department of Complex Systems of the Institute of Computer Science of the Czech Academy of Sciences.


Research areas

We focus on the development and application of methods of analysis and modelling of real-world complex networked systems, with particular interest in the structure and dynamics of human brain function. Our main research areas are:

  • Brain networks
    • Neuroimaging data analysis
    • Brain dynamics modelling
  • Causal interaction inference
    • Causality and information flow inference
    • Nonlinearity and nonstationarity
  • Complex network analysis
    • Graph theory
    • Machine learning and multivariate statistics
    • Application in neuroscience, climate research, economics, ...

Selected publications

Loss of neuronal network resilience precedes seizures and determines the ictogenic nature of interictal synaptic perturbations
WC Chang, J Kudlacek, J Hlinka, J Chvojka, M Hadrava, V Kumpost, ...
Nature neuroscience, 2018, 21 (12), 1742

Small-world bias of correlation networks: From brain to climate
J Hlinka, D Hartman, N Jajcay, D Tomeček, J Tintěra, M Paluš
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2017, 27 (3), 035812

Identifying causal gateways and mediators in complex spatio-temporal systems
J Runge, V Petoukhov, JF Donges, J Hlinka, N Jajcay, M Vejmelka, D Hartman, ...
Nature communications, 2015, 6, 8502

Reliability of inference of directed climate networks using conditional mutual information
J Hlinka, D Hartman, M Vejmelka, J Runge, N Marwan, J Kurths, M Paluš
Entropy, 2013, 15 (6), 2023-2045

Functional connectivity in resting-state fMRI: Is linear correlation sufficient?
J Hlinka, M Paluš, M Vejmelka, D Mantini, M Corbetta
Neuroimage, 2011, 54 (3), 2218-2225


Institute of Computer Science
The Czech Academy of Sciences
Pod Vodárenskou věží 271/2
182 07 Praha 8