Anna Pidnebesna is working on modelling and analysis of the real-world complex systems. Her main work is concerned about the development and application of data analysis methods, frequently using the sparse linear approaches. The application part is mainly concerned with the human brain investigation.

Contact:

ICS CAS (room 155)
Pod Vodarenskou vezi 271/2,
11800, Prague, Czech Republic

e-mail: pidnebesna[at]cs.cas.cz
phone: (+420) 266 052 081

Selected publications:

  • Caputi, L., Pidnebesna, A., and Hlinka, J. (2021+). Promises and pitfalls of Topological Data Analysis for brain connectivity analysis. NeuroImage. Submitted. here
  • Pidnebesna, A., Fajnerová, I., Horáček, J., and Hlinka, J. (2021+). Recovering Neuronal Signal from Hemodynamic Response: the Mixture Components Inference Approach. Human Brain Mapping. Submitted. here
  • Kopal, J., Pidnebesna, A., Tomeček, D., Tintěra, J., and Hlinka, J. (2020). Typicality of Functional Connectivity robustly captures motion artifacts in rs-fMRI across datasets, atlases and preprocessing pipelines. Human Brain Mapping, 41:5325–5340. here
  • Pidnebesna, A., Tomeček, D., and Hlinka, J. (2018). BRAD: Software for brain activity detection from hemodynamic response. Computer Methods and Programs in Biomedicine, 156:113 – 119, here
  • Pidnebesna, A., Helisová, K., and Staněk, J. (2018). Statistical analysis of dependencies among submissions to municipalities in the Czech Republic. Information Bulletin of the Czech statistical society, 29(3):1–19.
  • Pidnebesna, A., Helisová, K., Dvořák, J., Lechnerová, R., and Lechner, T. (2016). Statistical analysis and modelling of submissions to municipalities in the Czech Republic. Information Bulletin of the Czech statistical society, 27(4):1–18.

Dissertation:

Pidnebesna, A. (2020). Statistical analysis of the spatiotemporal processes here