Advanced Human Neurophysiology

Course objective

1. Insight in how the human brain generates scalp
electroencephalographic (EEG) signals, both ongoing oscillations and
event-related potentials (ERPs).
2. Practical skills in the measurement of EEG and ERP signals, in the
analysis of these data, and the use of MATLAB toolboxes for these
purposes.
3. The application of these techniques in various scientific and medical
fields, including sleep research, brain-computer interfacing, and
genetics.
Course content

In plenary lectures we will cover
- An introductory lecture on Math to enable students of different
backgrounds to follow theoretical aspects of the course.
- The generating mechanisms of EEG oscillations and ERPs.
- The theory behind digital signal processing routines. This will
include frequency decomposition of the EEG (Fourier analysis), time-
frequency analysis (wavelet), filtering, and methods to quantify
temporal and spatial correlations (Detrended Fluctuation Analysis and
cross-channel synchrony).
- Source localization techniques of EEG/ERP signals.
- Insights from EEG/ERP research into sleep, psychophysiology, and
genetics of human brain function.
Form of tuition

The lectures are interspersed with practicals, where the students will
learn:
- To record data with state-of-the-art high-density EEG systems.
- Advanced data analysis techniques to remove non-brain noise form EEG
signals (Independent Component Analysis).
- Signal analysis techniques such as filtering, Fourier and Hilbert
transforms.
- Data analysis techniques to quantify peaks and latencies in ERPs.
- To quantify EEG with standard measures (EEG power, ERP amplitude and
latency) and more advanced measures (wavelet-based time-frequency
transforms, detrended fluctuation analysis, Granger causality and
synchronization).
- To control a computer with your mind using a brain–computer interface.