Anna Pidnebesna is working on modeling and analysis of real-world complex systems. Her main work is connected with developing and applying data analysis methods, frequently using connectivity matrices and sparse linear approaches. The human brain investigation is the main application part.
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