The participants of this practical course will set up an EEG cap for one of the participants. Then a Brain-Computer Interface (BCI) system is first calibrated to the individual brain signals of that user, before s/he can make use of the system to slowly write a few letters. With the BCI, the user can write even though muscles or peripheral nerves are not involved in producing the necessary control signals, which renders the approach feasible for severely motor-impaired users. (Background: This BCI relies on so-called event-related potentials of the EEG, which are elicited by external, auditory stimuli. The BCI user makes a choice of one out of several possible decisions by focusing his spatial auditory attention to one of several tones. Even though the tones are presented to him in quick succession, an attended tone will elicit a different ERP response compared to an un-attended one. This difference can exploited with the BCI using machine learning methods.)
The BBCI Toolbox offers a flexible framework for online processing of multimodal neuroimaging data. This software will be made available as open source. Participants will learn to implement different kinds of BCIs within this framework, and to simulate and analyze online classification in practical exercises.
The students will be given a short introduction into practical aspects of measuring somatosensory responses, especially those produced by the electrical nerve stimulation. Multichannel EEG recordings will be performed and the obtained data will be analyzed for the presence of conventional and high-frequency responses. In another part of the practical session the student will learn about cortico-muslcar coherence (CMC) – a noninvasive phenomenon, which allows studying causal cortico-muscular interactions with a millisecond precision. Corresponding experiments and data analysis will also be presented for CMC.
The practical session about Low Field NMR/MRI wiil have the following parts:
- low field NMR - techniques and requirements
- low field NMR measurement of a head phantom
- low field NMR signal analysis
- low field NMR measurement of a tissue signal
- low field MRI - techniques and requirements
The workshop “Introduction to fMRI: acquisition and analysis” is addressed to students who have no or little experience with fMRI data analysis. In this workshop, we will introduce you to some basic theoretical aspects of fMRI, as well as designing good fMRI experiments. Most of the course will cover standard fMRI analyses (mainly GLM, first and second level statistics) and the necessary preprosessing steps (motion correction, spatial smoothing, etc.). Depending on time and interest we might also cover some advanced topics like multivariate pattern classification. Throughout the course, we will use the free software package SPM with the commercial software MATLAB. We will provide computers with the necessary software installed on them. However, if you prefer to use your own computer, please make sure that both Matlab and SPM8 (download here: http://www.fil.ion.ucl.ac.uk/spm/software/spm8/) are properly working on your laptop.
In this experimental session we will explain the principles of a NIRS scanner and demonstrate its use and the preparation of a typical experimental setup. We will perform a physiological experiment of measuring the hemodynamic changes caused by executed and imaginary hand-gripping. The experimental results will then be analyzed using methods commonly applied to NIRS signals.
Participants will photograph and segment some visual scenes for object search. We will apply our toolbox to control for confounding psychophysical parameters in a set of stimuli. Participants will take part in an experiment on visual search and analyze their own results.
Pyff is a Pythonic Framework for writing Feedback- and Stimulus applications for BCI experiments. It allows for writing such applications in Python with minimal effort, as it was specifically designed with the needs of non-computer scientists in mind. Pyff is free- and open source software available under the terms of the GPL. In the first part of the session, the participants will get an introduction to Pyff and learn how the framework works and how they can use it to implement their own Feedback- and Stimulus applications. In the second part, the participants will implement their own complete Feedback application, ready for a BCI experiment.
This workshop will give an overview on usability and quality testing as well as some practical experience on how to conduct quality tests following international standards specified e.g. by the /International Telecommunication Union (ITU)/. We will show how we deploy psychophysiologcial measures, mainly the EEG, for assessing audio and audiovisual quality important for telephone or video conferences. Depending on the interest of the participants, we can also include a brief overview on our research regarding mobile phone usage, and discuss with them how neurotechnology could be used in this context
Participants will have to opportunity to perform (as experimenter and as user) an EEG-based BCI experiment. The application will be a Speller (like http://iopscience.iop.org/1741-2552/8/6/066003/) that is based on ERPs to visual stimuli. Since all stimuli are presented at central position of the screen, no eye movements are required for operation, and the BCI system solely operates on modulated attention. Participants will learn how to conduct the EEG experiment, analyze the ERPs and run the online experiment with the BBCI software (which will be available as open source by then).