- Daniel Novák, PhD - group leader
- Tomáš Sieger, PhD - researcher
- Eduard Bakštein, PhD - researcher
- Jakub Schneider - PhD student
- Igor Varga - PhD student
- Jiří Wild - researcher
- Jiří Vošmik - Master student
Daniel Novák, PhD - head
He is a senior researcher at the Department of Cybernetics, CTU, Faculty of Electrical Engineering. Currently he reads lectures on Artificial Intelligence, Biometrics and Neuroinformatics. He publishes contributions in the field of neuroscience, ICT healthcare and ambient assisted living systems. See more at my linkedIn profile
J.Macías; A-Duque; C. Tobón; V. Kremen; D. Novak; J. Saiz; T. Oesterlein; C. Schmitt; A.Luik; J. Bustamante , Dynamic approximate entropy electroanatomic maps detect rotors in a simulated atrial fibrillation model. PLOS One, 9(12), 2014
P. Vostatek, D. Novak, T. Rychnovský, S. Rychnovská, Diaphragm Postural Function Analysis Using Magnetic Resonance Imaging, Plos One, 2013
D. Novak, F.Albert, D.Cuesta, 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Discrimination of Deep Brain Nuclei using Regularity Measure, 2012
D. Novak, J. Wild, T.Sieger and R.Jech, Identifying Number of Neurons in Extracellular Recording, 4th International IEEE EMBS Conference on Neural Engineering,Antalya, Turkey, 2009
Spaniel F, Vohlídka P, Hrdlicka J, Kožený J, Novák T, Motlová L, Cermák J, Bednarík J, Novák D, Höschl C.,ITAREPS: Information Technology Aided Relapse Prevention Programme in Schizophrenia, Schizophrenia Research, 98(1-3),2008
Tomáš Sieger, PhD - researcher
Tomáš Sieger is a researcher at the Dept. of Cybernetics at the FEE, CTU and the Dept. of Neurology and Center of Clinical Neuroscience at the Charles University in Prague. He studied computer science at the Charles University in Prague and (bio)statistics at the Charles University and the University of Hasselt, Belgium. He received his PhD from FEE, CTU in 2014, defending a thesis on Processing and Statistical Analysis of Single-Neuron Recordings. Focused on biomedical data analysis and modeling, he works primarily to understand the functioning of the human brain. He also buids models of flow-cytometry data and develops software for data analysis (he wrote idendro, an interactive dendrogram exploration tool, and contributed to ggplot2, a popular R data visualization package). He is/was leading TA for courses on Logic programming, Data mining, and Statistics. See his ResearchGate profile for more information.
E-mail: tomas.sieger(at)seznam.cz, siegetom(at)fel.cvut.cz
Research projetcs for students
Please see https://k13133.felk.cvut.cz/dp/list.phtml?v=323&s=3.
Forejtová, Z., Serranová, T., Sieger, T., Slovák, M., Nováková, L., Věchetová, G., . . . Edwards, M. (2022). The complex syndrome of functional neurological disorder. Psychological Medicine, 1-11. doi:10.1017/S0033291721005225
Neumann, W. J., Memarian Sorkhabi, M., Benjaber, M., Feldmann, L. K., Saryyeva, A., Krauss, J. K., Contarino, M. F., Sieger, T., Jech, R., Tinkhauser, G., Pollo, C., Palmisano, C., Isaias, I. U., Cummins, D. D., Little, S. J., Starr, P. A., Kokkinos, V., Gerd-Helge, S., Herrington, T., Brown, P., … Denison, T. (2021). The sensitivity of ECG contamination to surgical implantation site in brain computer interfaces. Brain stimulation, 14(5), 1301–1306. https://doi.org/10.1016/j.brs.2021.08.016
Dusek P, Lescinskij A, Ruzicka F, Acosta-Cabronero J, Bruha R, Sieger T, Hajek M, Dezortova M. Associations of Brain Atrophy and Cerebral Iron Accumulation at MRI with Clinical Severity in Wilson Disease. Radiology. 2021 Jun;299(3):662-672. doi: 10.1148/radiol.2021202846. Epub 2021 Mar 23. PMID: 33754827.
Modrák M, Bürkner PC, Sieger T, et al. Disease progression of 213 patients hospitalized with Covid-19 in the Czech Republic in March-October 2020: An exploratory analysis. PLoS One. 2021;16(10):e0245103. Published 2021 Oct 6. doi:10.1371/journal.pone.0245103
Serranová T, Sieger T, Růžička F, Bakštein E, Dušek P, Vostatek P, Novák D, Růžička E, Urgošík D, Jech R. Topography of emotional valence and arousal within the motor part of the subthalamic nucleus in Parkinson's disease. Sci Rep. 2019 Dec 27;9(1):19924. DOI: 10.1038/s41598-019-56260-x.
Sieger T, Hurley CB, Fišer K, Beleites C. Interactive Dendrograms: The R Packages idendro and idendr0. Journal of Statistical Software 76(10), doi: 10.18637/jss.v076.i10
Sieger T., Serranová T., Růžička F., Vostatek P., Wild J., Štastná D., Bonnet C., Novák D., Růžička E., Urgošík D., Jech R. Distinct populations of neurons respond to emotional valence and arousal in the human subthalamic nucleus, Proceedings of the National Academy of Sciences of the United States of America, 2015 112 (10) 3116-3121; published ahead of print February 23, 2015, doi:10.1073/pnas.1410709112. PDF
Sieger T., Bonnet C., Serranová T., Wild J., Novák D., Růžička F., Urgošík D., Růžička E., Gaymard B., Jech R. Basal ganglia neuronal activity during scanning eye movements in Parkinson’s disease. PLoS ONE, 8(11):e78581, 2013. PDF
Serranová T., Sieger T., Dušek P., Růžička F., Urgošík D., Růžička E., Valls-Solé J., Jech R. Sex, food and threat: startling changes after subthalamic stimulation in Parkinson's disease. Brain Stimul, 6(5):740–745, Sep 2013.
Serranová T., Jech R., Dušek P., Sieger T., Růžička F., Urgošík D., Růžička E. Subthalamic nucleus stimulation affects incentive salience attribution in Parkinson’s disease. Mov. Disord., 26(12):2260–2266, Oct 2011.
Fišer K., Sieger T., Schumich A., Wood B., Irving J., Mejstříková E., Dworzak M. N. Detection and monitoring of normal and leukemic cell populations with hierarchical clustering of flow cytometry data. Cytometry A, 81(1):25–34, Jan 2012.
Emotivní neurony v hloubi lidského mozku (at MLMU meet-up, in Czech)
Eduard Bakštein, PhD - researcher
Eduard Bakstein is a researcher at the compNeuroGroup, Dept. of Cybernetics at the FEE, CTU and the National Institute of Mental Health. He studied cybernetics and biomedical engineering at FEE CTU, where he also defended his PhD in 03/2017.
He is currently working on the problem of nuclei identification and atlas fitting to the microelectrode EEG and artifact/change-point detection in microelectrode EEG and other time-series data. He is the author of the sigInspect (GitHub) toolbox for automatic artifact detection. His other research interests include other machine learning, signal processing and data analysis problems.
He teaches courses on Computational neuroscience and Biometric identification, previously also Artificial Intelligence and Data Analysis.
Bakštein, E., Sieger, T., Wild, J., Novák, D., Schneider, J., Vostatek, P., Urgošík, D., Jech, R. (2017). Methods for automatic detection of artifacts in microelectrode recordings. In: Journal of Neuroscience Methods, 290, 39–51. [PDF, supplementary: PDF, matlab codes, data (18MB)]
Bakštein, E. - Burgess, J. - Warwick, K. - Ruiz, V. - Aziz, T. - et al.: Parkinsonian Tremor Identification with Multiple Local Field Potential Feature Classification. Journal of Neuroscience Methods. 2012, vol. 2, no. 209, p. 320-330. ISSN 0165-0270.
Bakštein, E.; Sieger, T.; Novák, D.; Jech, R.
Probabilistic model of neuronal background activity in deep brain stimulation trajectories
In: Information Technology in Bio- and Medical Informatics. Basel: Springer, 2016, pp. 97-111. LNCS 9832
Carmen, C. - Isasi, P. - Warwick, K. - Ruiz, W. - Aziz, T. - Stein, J. - Bakstein, E.: Resting tremor classification and detection in Parkinson's disease patients. Biomedical Signal Processing and Control. 2015, vol. 16, p. 88-97. ISSN 1746-8094.
Bakstein, E., Schneider, J., Sieger, T., Novak, D., Wild, J., Jech, R.
Supervised segmentation of microelectrode recording artifacts using power spectral density
(2015) Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2015-November, pp. 1524-1527.
Bakštein, E. - Burgess, J. - Warwick, K. - Stavdahl, O. - Aziz, T.: Features for Detection of Parkinson's Disease Tremor from Local Field Potentials of the Subthalamic Nucleus. In Proceedings of 2010, 9th IEEE International Conference on Cybernetic Intelligent Systems. Piscataway: IEEE, 2010, p. 39-44. ISBN 978-1-4244-9023-3.
Jakub Schneider - PhD student
Jakub Schneider is a PhD student at the compNeuroGroup. His current topic is optimization of DBS parameters settings and progression of PD based on stimulation. He is also interested in computational neuroscience and neurology. He also works as teacher in classes of Biometrics (biological means of person identification and authorization) and Cybernetics and Artificial Intelligence.
Schneider, J. - Novák, D. - Jech, R.: Optimization of Parkinson Disease Treatment Combining Anti-Parkinson Drugs and Deep Brain Stimulation Using Patient Diaries, In proceedings of 2015, 37th IEEE Internation Conference in Engineering in Medicine and Biology Society. 2015, p. 3444-3447
Bakštein, E. - Schneider, J. - Sieger, T. - Wild, J. - Novák, D. - Jech, R.: Supervised Segmentation of Microelectrode Recording Artifacts Using Power Spectral Density, 37th IEEE Internation Conference in Engineering in Medicine and Biology Society. 2015, p. 1524-1527
Igor Varga is a PhD student in the field of Computational Neuroscience. His topic is topographic analysis of MRI data and fusion with microelectrode recordings. He worked with brightfield microscopy and image analysis previously. Currently his research interests include Neuron Stem Cells, Neuronal Cell signalling, Neuronal proliferation. Neuroimaging, Brain-computer interfaces, Neuronal physiology.
Contacts: email@example.com Twitter @realVargaIgor
Jiří Wild, PhD - researcher
Past PhD student at the compNeuroGroup, working on the problem of trade off between UPDRS score and microelectrode EEG signal assessment. Other research interests include signal processing, data exploration and machine learning.
J.Wild, Z.Prekopcsak, T.Sieger, D.Novak, ,R.Jech, Performance comparison of spike sorting algorithms for single-channel recordings, Journal of Neuroscience Methods, 203(2), 2012
Jiří Vošmik - Master student
Jirka Vošmik studied the Master degree programme Biomedical Engineering and Informatics at the FEE, CTU. He successfully defended his master thesis focused on processing microelectrode recordings and assessing couplings between MER-derived signals. His general interests are brain-computer interfaces and machine learning.