List of selected publications
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KNOCIKOVÁ J. 2024. Approximate Entropy: An Algorithm for Quantifying Brain Complexity. In Advances in Signal Processing and Artificial Intelligence. International Frequency Sensor Association (IFSA) Publishing, S. L, 2024, s. 166-169. ISBN 978-84-09-60540-8.
also published In 6th International Conference on Advances in Signal Processing and Artificial Intelligence, Funchal (Madeira Island), Portugal, 2024
KNOCIKOVÁ, J. 2023. Approximate entropy as a diagnostic biomarker in neuropsychiatric diseases. In International Conference on Mathematical Modeling in Physical Sciences, Belgrade, 2023.
KNOCIKOVÁ, J. 2023. Wavelet implications in neuroscience: Time-frequency analysis of non-stationary data. International Conference on Mathematical Modeling in Physical Sciences, Belgrade, 2023.
KNOCIKOVÁ, J. 2023. Computational Biomarkers for Major Depressive Disorder. In Neurology World Conference, Miami, 2023
PÁLENÍČEK T. et al. 2022. Psilocybin induced changes in approximate entropy and microstates predict long term positive effects on mood in healthy volunteers. In ANT NeuroMeeting, Berlin 2022.
PÁLENÍČEK T. et al. 2022. Can phenomenology of psilocybin experience and induced changes in the brain activity predict long-term effect on mood? In Meeting of pychiatric association, Mikulov, 2022.
KNOCIKOVÁ, J. et al. 2021. Quantitative electroencephalographic biomarkers behind major depressive disorder. In Biomedical signal processing and control, 2021, vol. 68, 102596.
KNOCIKOVÁ, J. et al. 2020. Nonlinear Measure of EEG Complexity in the Eker Rat model of Autism Disorder: a Pilot Study. In Association for Computing Machinery (ACM) International Proceeding, 2020, p. 49-53. ISBN 978-1-4503-7541-2.
also published In 3rd International Conference on Mathematics and Statistics, Paris, 2020.
