CE171-4-SP-CO:
Neural Engineering Research Methods
2023/24
Computer Science and Electronic Engineering (School of)
Colchester Campus
Spring
Undergraduate: Level 4
Current
Monday 15 January 2024
Friday 22 March 2024
15
16 June 2022
Requisites for this module
(none)
(none)
(none)
(none)
CE225, CE246
BENGH169 Neural Engineering with Psychology,
BENGH170 Neural Engineering with Psychology (including Placement Year),
BENGH171 Neural Engineering with Psychology (including Year Abroad),
BENGH172 Neural Engineering with Psychology (Including Foundation Year),
BSC H167 Neural Technology with Psychology,
BSC H168 Neural Technology with Psychology (including Year Abroad),
BSC H176 Neural Technology with Psychology (including Placement Year)
This module provides an introduction to neural-engineering research, design and methodology, including ethical aspects, and a step-by-step introduction to essential statistical research techniques. Students will be introduced to the basic principles of research design, and to a variety of experimental and correlational techniques for studying neural and physiological measurements of human mental activities and behaviours.
Appropriate techniques of statistical analysis will be applied (using Python libraries) to experimental data that will be either provided or collected. With these tools to hand, students will be able to make objective observations and draw sound conclusions from the data. Students will learn how to present such findings and observations in laboratory reports.
In the Neural Engineering Research Methods module you will:
1. be introduced to the main research methods and designs used in Neural Engineering,
2. learn how to conduct controlled experiments, following good laboratory practice and ethical guidelines,
3. become familiar with techniques for analysing experimental data and make statistically sound inferences,
4. learn to write concise scientific reports of your findings.
At the end of the module you should:
1. understand the relationships between hypotheses, data and conclusions,
2. be able to use simple statistical tests to investigate hypotheses arising from empirical studies,
3. be able to distinguish between the major types of research design, and to discuss the appropriateness of each for a particular investigation or application,
4. be able to design a simple experiment or study to carry out a particular kind of investigation,
5. be able to write competent lab reports.
1. Basic concepts of probability
2. Formulating and testing hypotheses and experimental design (e.g., variables, experimental designs, etc.).
3. Describing data and displaying data (e.g., measures of central tendency and variability; the normal distribution and z-scores; scatterplots, boxplots; etc.)
4. Parametric statistical tests (e.g., t-tests, ANOVAs, etc.)
5. Non-parametric statistical tests (e.g., Wilcoxon's, Kruskal-Wallis, Friedman, etc.)
6. Correlation and regression
7. Implementing experimental designs, collecting data and conducting statistical analyses
8. Consulting literature, interpreting data and writing lab reports
9. Ethics
The module is a full year module comprising a 1hr lecture and a 1hr practical laboratory each week. In laboratories, which link with the module “Introduction to Programming”, students will be taught how to design experiments and do statistical data analysis by using dedicated Python packages.
The above list is indicative of the essential reading for the course.
The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students.
Further reading can be obtained from this module's
reading list.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Coursework |
Moodle Quizzes - weekly |
|
10% |
| Coursework |
Lab Report 1 |
|
40% |
| Coursework |
Lab Report 2 |
|
50% |
| Exam |
Main exam: In-Person, Open Book (Restricted), 120 minutes during Summer (Main Period)
|
| Exam |
Reassessment Main exam: In-Person, Open Book (Restricted), 120 minutes during September (Reassessment Period)
|
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
Dr Caterina Cinel, email: ccinel@essex.ac.uk.
Dr Caterina Cinel
School Office, email: csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770
Yes
No
No
No external examiner information available for this module.
Available via Moodle
Of 40 hours, 20 (50%) hours available to students:
20 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.
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