MSc in Computational Cognitive Neuroscience

Understanding the relationship between brain, cognition and behaviour is one of the main challenges the scientific community is currently facing. Which neural processes underlie “free” decisions, the formation of new memories, the emergence of conscious experience? Computational cognitive neuroscience is a young and exciting discipline that tackles these long-standing research questions by integrating computer modelling with experimental research.

This Masters programme will foster a new generation of scientists who will be trained in both neurocomputational modelling as well as cognitive neuroscience.Its core topics include theory and practice of biologically constrained models of neurons, cortical circuits, and higher cognitive functions (memory, decision making, language), and fundamentals of cognitive neuroscience (brain mechanisms and structures underlying cognition and behaviour, as well as modern neuroimaging and data analysis techniques). The programme is suitable for students from a variety of disciplines (including psychology, computing, neuroscience, engineering, biology, maths, physics, or related subjects), and students with no prior programming experience are welcome. Thanks to the highly multidisciplinary and cutting-edge nature of the programme, graduates of this Masters will acquire a unique set of complementary skills that will make them extremely competitive in securing research or analyst positions in both academia and industry.

Why study this course:

1. The programme is cutting edge, being at the forefront of a new, rapidly emerging field of research.
2. It is multidisciplinary, conveying theoretical aspects and experimental techniques from both computational and cognitive neurosciences.
3. The novelty of this Masters is that it combines, in a single programme, topics which are typically covered separately (e.g., the brain basis of human cognitive functions, neural modelling and programming techniques).
4. The unique, cross-disciplinary and cutting-edge profile that graduates of this programme will acquire will give them a competitive edge in the job market over graduates of other, standard programmes in related fields.
5. Big data companies are branching out into the area of computational neuroscience and explicitly searching for scientists with the above knowledge and skills.

Modules & structure

You will study the following modules:

TERM 1

• Foundations of Neuroscience (PS74005D), which covers brain anatomy and functions and modern experimental techniques to study the neural basis of behaviour.
• Statistical Methods (PS71020D). This module covers primary statistical analyses used in psychology and neuroscience (including multivariate data screening and cleaning; power and sample size determination; factor analysis; multiple regression; analysing contrasts; univariate and multivariate repeated measures; ANCOVA; MANOVA and psychometrics).
• A choice between Data Programming (IS71068A) or a new PG MATLAB module which is due to be offered by Psychology in 2018.

TERM 2

• A new module called “Cortical Modelling”: this will cover theory and practice of computational neuroscience (including computational models of neurons, synapses, simple cortical circuits and networks). Students will learn how to implement simple models of biologically-realistic neural systems.
• A new module called “Cognitive Neuroscience”, which will cover the current state of knowledge in the field of cognitive neuroscience. It covers lower-level, fundamental cognitive processes, such as perception, attention, action, vision, audition, and motor control, as well as higher functions such as memory, speech, language, executive functions and cognitive control.
• A new module called “Modelling cognitive and higher brain functions”: fundamental principles of current computational models of human cognitive and brain functions and their emergence (including vision, attention, memory, decision making, and language).
• Advanced Quantitative Methods (PS71082A): Theory and practice in the application of advanced quantitative methods across multiple areas of psychology and neuroscience.

TERM 3

• Research Project which will be carried out by combining the computational, experimental and data analysis skills that students will acquire over Term 1 and 2.

OPTIONAL MODULES:

In Term 1, students will have to choose one amongst the following 4 options (each one 15 CATS, level 7):

• Neural Networks (IS57002A)
• Machine Learning (IS71071A)
• Natural Computing (IS71072A)
• Data and Machine Learning for Artistic Practice (IS71074A)

Please note that the new modules may change subject to approval

Please note that due to staff research commitments not all of these modules may be available every year.

Skills & careers

Graduates of this programme will have the following assets in their portfolio:

• A sound understanding of brain mechanisms and structures underlying cognition and behaviour; knowledge or experience of experimental cognitive neuroscience methods; skills in statistical data analysis; as well as
• Knowledge of theory and practice of biologically constrained neural models for the simulation of human brain function; programming skills.

Such a cross-disciplinary profile will make students who complete this Master particularly competitive on the job market, especially when applying for positions that require complementary expertise and skills, such as international collaborative projects, Universities and research institutes. The above multidisciplinary knowledge and assets will also make them ideal candidates for large and successful enterprises which have a focus on the development of advanced systems able to exhibit human-like intelligent behaviour (e.g., web-search engines, systems for natural language processing, information extraction, data mining and human-computer interaction).

Entry requirements

First- or upper second-class honours degree (or equivalent undergraduate degree) in a relevant discipline.

Applicants might also be considered if they aren’t a graduate or their degree is in an unrelated field, but have relevant experience and can demonstrate the ability to work at postgraduate level.

A-levels in Computer science or Science or Maths.

Equivalent qualifications

We accept a wide range of international qualifications. Find out more about the qualifications we accept from around the world.

English language requirements

If English isn’t your first language, you’ll need to meet our English language requirements to study with us.

For this programme we require:

IELTS 6.5 with a 6.5 in writing and no element lower than 6.0.

If you need assistance with your English language, we offer a range of courses that can help prepare you for postgraduate-level study.