BI3BC17-Brain Computer Interfaces
Module Provider: School of Biological Sciences
Number of credits: 10 [5 ECTS credits]
Level:6
Terms in which taught: Spring term module
Pre-requisites: BI1PR17 Programming BI1EE17 Electronics BI2SP17 Signal Processing
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2020/1
Email: y.hayashi@reading.ac.uk
Type of module:
Summary module description:
The module aims at providing real experience of developing and performing Brain Computer Interfaces – decoding the relaxation state and motor intention. Electronics (BI1EE17) and Signal Processing (BI2SP17) must be completed in priori.
Aims:
A Brain Computer Interface (BCI) opens up a communication channel to control external devices via detecting and decoding intention from brain activity. Brain activity can be measured as electric signals which are generated by firing of neuronal population. As a most well-known noninvasive method, Electroencephalography (EEG) is an electrophysiological method to record electrical activity of the brain.
The module aims at providing real experience of developing and performing Brain Computer Interfaces - decoding the relaxation state and motor intention. In the lab practical sessions, EEG experiments are performed, and EEG signals are recorded to understand the relaxation state and motor intention of participants. Practically speaking, we will develop signal processing to decode the relaxation state and motor intention, using the commercial headset.
Lectures will provide the fundamental knowledge with the focus on the spectrum analysis to decompose the oscillatory behaviour of neuronal populations across the cortical regions. The rest of the module focuses on the overview of the technologies enabling direct brain-computer communication including the main components of the closed loop system and applications.
Assessable learning outcomes:
1. Functional and practical understanding of neuroscience
2. Learning of procedure to perform EEG experiments
3. Signal processing to decode the relaxation state and motor intention
4. Knowledge of the state of art in BCI including its application
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Additional outcomes:
The students will become familiar with the potential applications of BCI. They will also learn advanced signal processing, starting from the bandpass filter to extract mono-frequency of the EEG signal.
Outline content:
1. Introduction to Neurodynamics
2. Dynamics of Cognition
3. Analysis of multivariate point process data (spike trains) and continuous time series (EEG, LFP)
4. BCI technologies
5. BCI applications in neurorehabilitation
Brief description of teaching and learning methods:
The module comprises lectures (8 hours), practical sessions (12 hours) and a major coursework. The lectures introduce the basic concepts, methodologies and tools for BCI. During the practical sessions the students will carry out hands-on activities on BCI technologies and test cases. A final project allows the students to apply the concepts to a practical case.
Autumn | Spring | Summer | |
Lectures | 10 | ||
Practicals classes and workshops | 10 | ||
Guided independent study: | 80 | ||
Total hours by term | 0 | 0 | |
Total hours for module | 100 |
Method | Percentage |
Report | 100 |
Summative assessment- Examinations:
Summative assessment- Coursework and in-class tests:
Formative assessment methods:
Penalties for late submission:
The Module Convenor will apply the following penalties for work submitted late:
- where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day[1] (or part thereof) following the deadline up to a total of five working days;
- where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.
Assessment requirements for a pass:
40%
Reassessment arrangements:
Individual report.
Additional Costs (specified where applicable):
1) Required text books:
2) Specialist equipment or materials:
3) Specialist clothing, footwear or headgear:
4) Printing and binding:
5) Computers and devices with a particular specification:
6) Travel, accommodation and subsistence:
Last updated: 27 May 2020
THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.