google scholar | WoS

Journal articles

• Jajcay, N. & Hlinka, J. (2023). Towards a dynamical understanding of microstate analysis of M/EEG data. NeuroImage, 281, 120371.
  
• Dallmer-Zerbe, I., Jajcay, N., Chvojka, J., Janca, R., Jezdik, P., Krsek, P., Marusic, P., Jiruska, P. & Hlinka, J. (2023). Computational modeling allows unsupervised classification of epileptic brain states across species. Scientific Reports, 13, 13436.
  
• Bohm, A., Lauko, V., Dostalova, K., Balanova, I., Varga, I., Bezak, B., Jajcay, N., Moravcik, R., Lazurova, L., Slezak, P., Mojto, V., Kollarova, M., Petrikova, K., Danova, K. & Zeman, M. (2023). In-vitro antiplatelet effect of melatonin in healthy individuals and patients with type 2 diabetes mellitus. Journal of Endocrinological Investigation, , 8.
  
• Jajcay, N., Bezak, B., Segev, A., Matetzky, S., Jankova, J., Spartalis, M., El Tahlawi, M., Guerra, F., Friebel, J., Thevathasan, T., Berta, I., Polzl, L., Nagele, F., Pogran, E., Cader, F. A., Jarakovic, M., Gollmann-Tepekoylu, C., Kollarova, M., Petrikova, K., Tica, O., Krychtiuk, K. A., Tavazzi, G., Skurk, C., Hubert, K. & Bohm, A. (2023). Data processing pipeline for cardiogenic shock prediction using machine learning. Frontiers in Cardiovascular Medicine, 10, 1132680.
  
• Jajcay, N., Cakan, C. & Obermayer, K. (2022). Cross-Frequency Slow Oscillation-Spindle Coupling in a Biophysically Realistic Thalamocortical Neural Mass Model. Frontiers in Computational Neuroscience, 16, 769860.
  
• Cakan, C., Jajcay, N. & Obermayer, K. (2021). neurolib: A Simulation Framework for Whole-Brain Neural Mass Modeling. Cognitive Computation, 15, 1132-1152.
  
• Bohm, A., Snopek, P., Tothova, L., Bezak, B., Jajcay, N., Vachalcova, M., Uher, T., Kurecko, M., Kissova, V., Danova, K., Olejnik, P., Michalek, P., Hlavata, T., Petrikova, K., Mojto, V., Kyselovic, J. & Farsky, S. (2021). Association Between Apelin and Atrial Fibrillation in Patients With High Risk of Ischemic Stroke. Frontiers in Cardiovascular Medicine, 8, 742601.
  
• Jajcay, N., Kravtsov, S., Sugihara, G., Tsonis, A. A. & Paluš, M. (2018). Synchronization and causality across time scales in El Niño Southern Oscillation. npj Climate and Atmospheric Science, 1(1), 33.
  
• Krakovská, A., Jakubík, J., Chvosteková, M., Coufal, D., Jajcay, N. & Paluš, M. (2018). Comparison of six methods for the detection of causality in a bivariate time series. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 97(4), 042207.
  
• Coufal, D., Jakubík, J., Jajcay, N., Hlinka, J., Krakovská, A. & Paluš, M. (2017). Detection of coupling delay: A problem not yet solved. Chaos, 27(8), 083109.
  
• Hlinka, J., Hartman, D., Jajcay, N., Tomeček, D., Tintěra, J. & Paluš, M. (2017). Small-world bias of correlation networks: From brain to climate. Chaos, 27(3), 035812.
  
• Hlinka, J., Jajcay, N., Hartman, D. & Paluš, M. (2017). Smooth information flow in temperature climate network reflects mass transport. Chaos, 27(3), 035811.
  
• Jajcay, N., Hlinka, J., Kravtsov, S., Tsonis, A. A. & Paluš, M. (2016). Time scales of the European surface air temperature variability: The role of the 7 – 8 year cycle. Geophysical Research Letters, 43, 902–909.
  
• Runge, J., Petoukhov, V., Donges, J. F., Hlinka, J., Jajcay, N., Vejmelka, M., Hartman, D., Marwan, N., Paluš, M. & Kurths, J. (2015). Identifying causal gateways and mediators in complex spatio-temporal systems. Nature Communications, 6, 8502.
  
• Vejmelka, M., Pokorná, L., Hlinka, J., Hartman, D., Jajcay, N. & Paluš, M. (2014). Non-random correlation structures and dimensionality reduction in multivariate climate data. Climate Dynamics, 44, 2663–2682.
  
• Hlinka, J., Hartman, D., Jajcay, N., Vejmelka, M., Donner, R., Marwan, N., Kurths, J. & Paluš, M. (2014). Regional and inter-regional effects in evolving climate networks. Nonlinear Processes in Geophysics, 21(2), 451-462.
  

Conference proceedings

• Jajcay, N. & Paluš, M. (2016). Information transfer across temporal scales in atmospheric dynamics. In A. Banerjee, W. Ding, J. Dy, V. Lyubchich & A. Rhines (Eds.), Proceedings of the 6th International Workshop on Climate Informatics: CI 2016, Boulder, CO, USA (pp. 113-116). Boulder, CO, USA: NCAR.
• Jajcay, N. & Paluš, M. (2016). Statistical Modelling in Climate Science. In B. Brejová (Ed.), Proceedings of the 16th ITAT Conference Information Technologies - Applications and Theory, Tatranské Matliare, Slovakia (pp. 102-109). CEUR Workshop Proceedings vol. 1649: CEUR.

Books / book chapters

• Jajcay, N. (2024). Výpočetní psychiatrie jako vysvětlení mechanismu psychiatrických poruch (in Czech). In J. Horáček , L. Kesner , C. Höschl & T. Nekovářová (Eds.) Mozek a jeho člověk, mysl a její nemoc (pp. 276-284). Prague, CZ: Galén.
• Jajcay, N. (2017). Chaos — psilocybin v mozku (in Czech). In F. Tylš (Ed.) Fenomén psychedelie (pp. 37-40). Prague, CZ: dybbuk.