https://studiegids.vu.nl/en/courses/2024-2025/AM_1003The course "Rhythms of the Brain" is focused on measuring, analyzing, and interpreting the functional role of neuronal oscillations in humans. At the end of the course the student should be able to: 1. Explain how the human brain generates scalp electroencephalographic (EEG) signals, both ongoing oscillations and event-related potentials (ERPs). 2. Acquire practical experience with EEG (i.e., measure EEG, perform quantitative and statistical analysis to draw conclusions about the relation between brain activity and cognition/behavior, and present the results on a poster). 3. Explain key concepts of complex-systems science that have gained acceptance in the cognitive and behavioral neurosciences. 4. Apply state-of-the-art complexity-analysis techniques to EEG data and perceptual/ behavioral time series, and 5. …understand how these techniques can be applied in fundamental science and applied medical fields, e.g., for clinical trials and personalized medicine. 6. Explain the advanced techniques that estimate brain sources from the EEG signals, and outline the possibilities and limitations based on own experiences. 7. Explain the rationale of so-called "integrated biomarkers" based on machine learning, use specialized toolboxes to compute them and critically reflect on the pros and cons of this approach to functionally assess the state of a human brain based on the rhythms that it generates.Understanding the complexity of the human brain and mind is one of thegreatest scientific challenges of the 21st century. To address these challenges, researchers increasingly adopt theories and methods used to study complexity in other natural systems. In this course, we give you a solid conceptual understanding of "complexity" and tools to study the complexity of the human brain through quantitative analysis of the brain rhythms that it generates and the variability in cognitive and behavioral tasks. We consider it critical that students gain an in-depth understanding of the analytical tools in order to properly use and interpret the outcome of the different analysis techniques. This is achieved by covering the theory in the lectures followed by tutorials in the computer rooms. The concepts of "critical dynamics" and power-law scaling behavior are carefully explained in the context of time-series analysis tools, generating mechanisms, and functional implications. Key concepts of complex networks and analytical tools to characterize them based on M/EEG data are also covered. Another important component of the course is to teach you how to perform high-density EEG recordings of spontaneous brain activity during resting-state conditions and cognitive tasks and to analyze these signals with classical as well as modern complexity algorithms. You will work in small groups to record, analyze and present both data on EEG and its cognitive/behavioral correlates at the end of the course. Finally, the importance of non-stimulus driven brain activity and cognition for brain-related disorders such as depression, dementia, insomnia or attention deficit and hyperarousal disorder is discussed in the context of normal variation in biomarkers and the associated challenges in objective diagnosis, prognosis, and treatment selection. We explain how data mining and -classification techniques from artificial intelligence can be used to integrate information from multiple biomarker algorithms to increase the accuracy of clinically relevant functional assessments. While the course is focused on understanding variability in human cognition and behavior in health and disease, the concepts and tools equally apply to research on common animal models.The study credits amount to 168 hours of study, which are divided approximately as follows: Activity Hours of study Lectures (l) 20 Self study (literature and lecture sheets) 38 Practicals in EEG lab (Prac) 8 Computer practicals and project assignment (A) 36 Journal club (Pres) 8 Poster preparation (A) 18 Preparation for exams (poster and written) 40 Total 168Analysis and making research poster (R, 15%)Presentation of research poster (Pres, 25%)Written examination (E: 60%)Compensation is not possible for any of these assessments.Nikulin VV, Linkenkaer-Hansen K, Nolte G, Lemm S, Müller KR, IlmoniemiRJ, Curio G. A novel mechanism for evoked responses in the human brain.Eur J Neurosci. 2007;25:3146–54.Mazaheri A, Jensen O. Asymmetric amplitude modulations of brainoscillations generate slow evoked responses. J Neurosci 2008;28:7781–7.Jensen O, van Dijk H, Mazaheri A. Amplitude asymmetry as a mechanism forthe generation of slow evoked responses. Clin Neurophysiol 2010.Nikulin VV, Linkenkaer-Hansen K, Nolte G, Curio G. Non-zero mean andasymmetry of neuronal oscillations have different implications forevoked responses. Clin Neurophysiol 2010;121:186–93. Hardstone R, Poil S-S, Schiavone G, Jansen R, Nikulin VV, Mansvelder HD, Linkenkaer-Hansen K. Detrended fluctuation analysis: A scale-free view on neuronal oscillations. Frontiers in Physiology. 3:450. doi:10.3389/fphys.2012.00450. 2012. Annotated sheets from lecturesMasters and PhD students with interest in human brain function in general and EEG methodology in particular.dr. K. Linkenkaer Hansen with guest lectures of dr. D.J.A. Smit