Cognitive Neuroscience

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Course overview
(MSc) Master of Science
Cognitive Neuroscience
University of Essex
University of Essex
Colchester Campus
MSC C85012

Professional accreditation


Admission criteria

A high 2.2 degree in Psychology, Cognitive Science or a related subject .

If you hold a degree in Psychology it would be preferable, though not essential, if this was British Psychological Society accredited.

Applications from students with a 2:2 or equivalent will be considered dependent on any relevant professional or voluntary experience, previous modules studied and/or personal statement.

IELTS (International English Language Testing System) code

IELTS 7.0 overall with a minimum component score of 5.5

If you do not meet our IELTS requirements then you may be able to complete a pre-sessional English pathway that enables you to start your course without retaking IELTS.

Additional Notes

The University uses academic selection criteria to determine an applicant’s ability to successfully complete a course at the University of Essex. Where appropriate, we may ask for specific information relating to previous modules studied or work experience.

Course qualifiers


Rules of assessment

Rules of assessment are the rules, principles and frameworks which the University uses to calculate your course progression and final results.

Additional notes


External examiners

External Examiners provide an independent overview of our courses, offering their expertise and help towards our continual improvement of course content, teaching, learning, and assessment. External Examiners are normally academics from other higher education institutions, but may be from the industry, business or the profession as appropriate for the course. They comment on how well courses align with national standards, and on how well the teaching, learning and assessment methods allow students to develop and demonstrate the relevant knowledge and skills needed to achieve their awards. External Examiners who are responsible for awards are key members of Boards of Examiners. These boards make decisions about student progression within their course and about whether students can receive their final award.

eNROL, the module enrolment system, is now open until Monday 27 January 2020 8:59AM, for students wishing to make changes to their module options.


Core You must take this module.
You must pass this module. No failure can be permitted.
Core with Options You can choose which module to study.
You must pass this module. No failure can be permitted.
Compulsory You must take this module.
There may be limited opportunities to continue on the course/be eligible for the degree if you fail.
Compulsory with Options You can choose which module to study.
There may be limited opportunities to continue on the course/be eligible for the degree if you fail.
Optional You can choose which module to study.
There may be limited opportunities to continue on the course/be eligible for the degree if you fail.

Year 1 - 2019/20

Exit Award Status
Component Number Module Code Module Title Status Credits PG Diploma PG Certificate
01 PS934-7-FY Research Project (MSc) Core 60 Compulsory Compulsory
02 PS901-7-AU Fundamentals of Neuroscience and Neuropsychology Compulsory 15 Compulsory Compulsory
03 PS929-7-AU Methods in Cognitive Neuroscience Compulsory 15 Compulsory Compulsory
04 PS930-7-FY Numerical Methods for Cognitive Neuroscience Compulsory 15 Compulsory Compulsory
05 Option(s) from list Optional 30 Optional Optional
06 Option(s) from list Optional 30 Optional Optional
07 Option from list Optional 15 Optional Optional

Exit awards

A module is given one of the following statuses: 'core' – meaning it must be taken and passed; 'compulsory' – meaning it must be taken; or 'optional' – meaning that students can choose the module from a designated list. The rules of assessment may allow for limited condonement of fails in 'compulsory' or 'optional' modules, but 'core' modules cannot be failed. The status of the module may be different in any exit awards which are available for the course. Exam Boards will consider students' eligibility for an exit award if they fail the main award or do not complete their studies.

Programme aims

The MSc degree in Cognitive Neuroscience is a 1-year programme of study.

Its main teaching aims are:

To provide an advanced education in core subjects of cognitive neuroscience

To provide an advanced knowledge of cognitive neuroscience research techniques and instrumentation, and appropriate statistical methodology.

To provide a suitable foundation for graduates wishing to proceed to a programme of further postgraduate study

To provide training in transferable skills necessary to meet the current requirements of graduate employers.

To provide knowledge and skills (critical evaluation and argument, quantitative empirical methods, effective communication) that will prepare students for academic careers as well as a wide range of alternative careers, and will be widely sought by employers.

Learning outcomes and learning, teaching and assessment methods

On successful completion of the programme a graduate should demonstrate knowledge and skills as follows:

A: Knowledge and understanding

A1: Graduates will demonstrate an advanced knowledge and understanding of statistics appropriate for cognitive neuroscience

A2: Graduates will demonstrate an advanced knowledge and understanding of psychological theory within the core domains of cognitive neuroscience

A3: Graduates will demonstrate an advanced knowledge and understanding of functional localisation within the brain and the neural structures supporting cognitive capacity

A4: Graduates will demonstrate an advanced knowledge and understanding of research methods, instrumentation and experimental design appropriate for cognitive neuroscience

A5: Graduates will demonstrate an advanced knowledge and understanding of specialist knowledge, principles and techniques in a substantive area of cognitive neuroscience and cognitive neuropsychology in which the student has chosen to develop special expertise.

A6: Acquire advanced knowledge and understanding of fundamental theoretical issues in the natural, social and cognitive sciences, and the philosophy of mind

Learning methods

Learning methods The scheme has been designed to incorporate a range of core and specialist topics within Cognitive Neuroscience.

Understanding of the core topics is provided by modules in core areas within Cognitive Neuroscience and supplemented by a range of options in Cognitive Neuropsychology and related topics.

Deeper understanding of specialist topics is provided primarily by completing an independent research project under supervision (A4).

While lectures are the principal method of delivery for the concepts and principles outlined in A1-A3, A5 and A6 the department encourages learning through the integration of other teaching activities, including tutorials or discussion groups (A1-A3), laboratory research classes (A1, A3, A4), project research and supervision (A4), and directed reading (A1-A4).

Assessment methods

A2, A5, A6 are assessed by 2000-word coursework essays.

A1, A3, A4, are assessed by practical exercises, by statistical examination and the 10,000-word dissertation.

A1, A3 and A4 are also assessed through the dissertation.

B: Intellectual and cognitive skills

B1: Graduates will show evidence of enhanced ability to evaluate the theoretical issues and experimental techniques of cognitive neuroscience

B2: Graduates will show evidence of enhanced ability to employ evidence-based reasoning to develop coherent research plans and hypotheses

B3: Assemble and integrate evidence from a variety of sources, especially primary sources.

B4: Graduates will show evidence of enhanced ability to analyse and interpret quantitative information in graphs, figures, tables, and determine what the appropriate statistical tests would be

Learning methods

Learning methods The basis for intellectual skills is provided in lectures and laboratory classes.

B1 is developed in both lecture-based and laboratory-based courses.

B2 Is taught and developed by the research project completed under individual supervision.

B3 is developed through lectures, guided reading and tutor led discussion groups.

B4 is a key element of statistics and methods courses, and of the supervised research project

Assessment methods

Evaluation and integration skills are assessed through coursework essays (B1, B3).

Statistical knowledge and quantitative skills are assessed by practical exercises and an unseen examination (B4).

All intellectual and cognitive skills are assessed by the dissertation (B2).

C: Practical skills

C1: Graduates will be able to deploy research skills, including use of scientific databases, referencing packages, and modelling packages

C2: Graduates will be able to deploy writing skills, including use of academic conventions for publication

C3: Graduates will be able to effectively test research hypotheses using appropriate statistical techniques.

C4: Present quantitative data in tabular and graphical form.

C5: Graduates will be able to use a range of psychological tools related to cognitive neuropsychology, such as specialist software, laboratory equipment and psychological assessment tests.

Learning methods

Lectures, seminars, practical classes and computer workshops are used to teach research and writing skills (C1-C2).

C3 is developed through class exercises using a range of statistical software and during the supervision of the research project.

C4 and C5 are acquired in laboratory-based project work and the research project.

Assessment methods

Research and writing skills and use of psychological tools are assessed through the coursework essays and practical exercises, and the dissertation (C2, C3, C5).

Statistical skills are assessed by a 2-hr statistical examination, the practical exercises, and the dissertation (C3 - C5).

Data collection skills are assessed by the dissertation.

D: Key skills

D1: A graduate will show evidence of enhanced ability to communicate ideas effectively. Communicate information, arguments and ideas cogently and effectively in a range of different contexts using a range of different aids or resources

D2: A graduate will show enhanced ability to be computer literate. (i) Use appropriate IT facilities to prepare and present laboratory reports & essays. (ii) Use statistical software to analyse quantitative data.

D3: A graduate will show evidence of enhanced ability to handle data and be numerate. i) Analyse and present numerical data. ii) Use statistical techniques in the process of experimental analysis and design

D4: A graduate will show enhanced ability to problem solve and reason scientifically

D5: A graduate will show evidence of the ability to work with others in a research context

D6: (i) Produce work that is properly presented against strict deadlines. (ii) Reflect on their own performance and make constructive use of feedback. (iii) Work independently, and plan work effectively

Learning methods

Students are introduced to appropriate statistical software from the first term, and thereafter the further development of key skills forms an integral part of their learning activity.

In particular, D1(i) is developed in laboratory classes, tutorials, and the supervised research project.

D2 (i) and D2 (ii) are developed through the use of an extensive computer laboratory with access to the internet.

These key skills are taught in laboratory courses and statistics courses throughout the year.

D3 (i) and D3 (ii) are developed primarily in laboratory courses and in the supervised research project.

D4 is developed in practical exercises and laboratory classes.

D5 is addressed through the development of ideas and methods along side the supervisor in the research project.

D6 (i) and D6 (ii) is emphasised throughout the programme and is developed by means of rigid deadlines, feedback on assignments, and discussions with class tutors.

Assessment methods

D1 (i) is directly assessed throughout the course.

All coursework must be word-processed, and laboratory-classes require statistics that are performed with dedicated computer software packages, such that students must demonstrate basic competence in computer literacy (D2 (i)).

Students are also assessed on their ability to use a dedicated statistical package (D2 (ii)).
Statistical analyses are assessed in coursework and end of year examinations, such that students must demonstrate advanced competence in numeracy (D3).

Problem solving is assessed in all courses in the programme (D4) in terms of the ability to generate cogent arguments and answers to novel questions in course-work essays.

The ability to generate convincing hypotheses, to work with other, and to develop an appropriate experimental design to answer a question is mostly assessed in the research dissertation (D3, D4, D5).

Improvement of students' own learning and performance is assessed by awarding marks in coursework and examinations for evidence of additional reading (D6 (ii)) and by imposing strict deadlines for coursework assignments (D6 (i).


The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include a change of law or regulatory requirements, industrial action, lack of demand, departure of key personnel, change in government policy, or withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications.

The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.

Should you have any questions about programme specifications, please contact Course Records, Quality and Academic Development; email: