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.
Foundations of Neuroscience, which covers brain anatomy and functions and modern experimental techniques to study the neural basis of behaviour.
Statistical Methods. 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 (subject to approval).
An option module: students will have to choose one amongst the following 4 options :
' Neural Networks
' Machine Learning
' Natural Computing
' Data and Machine Learning for Artistic Practice
A new module called “Cortical Modelling” (subject to approval): 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” (subject to approval), 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” (subject to approval): 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: Theory and practice in the application of advanced quantitative methods across multiple areas of psychology and neuroscience.
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.
*Please note that due to staff research commitments not all of these modules may be available every year.
|Duration & Attendance||Qualification||Tuition fees||Fee type|
|Master of Science - MSc (PG)|
- An 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. Including Computer science or Science or Maths at an appropriate level.