Neural Engineering Research Methods

The details
Computer Science and Electronic Engineering (School of)
Colchester Campus
Undergraduate: Level 4
Monday 13 January 2025
Friday 21 March 2025
16 June 2022


Requisites for this module


CE225, CE246

Key module for

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)

Module description

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.

Module aims

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.

Module learning outcomes

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.

Module information

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

Learning and teaching methods

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.



Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Weekly Moodle Lab Tasks    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

Coursework Exam
50% 50%


Coursework Exam
50% 50%
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



External examiner

No external examiner information available for this module.
Available via Moodle
No lecture recording information available for this module.


Further information

* Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.

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