Course summary
Understanding the relationship between brain, cognition and behaviour is one of the biggest challenges for the scientific community. This established Masters course, integrating computer modelling with experimental research, equips students with a solid theoretical basis and practical experience of advanced data analysis and experimental techniques in computational and cognitive neuroscience. Computational cognitive neuroscience is a young and exciting discipline that attempts to understand how the human brain works by integrating computer modelling with experimental cognitive neuroscience research. Building on the multi-disciplinary and strong research profiles of academics from our departments of Computing and Psychology, this degree will develop a new generation of scientists, trained in both neuro-computational modelling and cognitive neuroscience. Core topics you’ll study include:
- Creating computational/mathematical models of neurons, circuits and cognitive functions
- The fundamentals of cognitive neuroscience (brain mechanisms and structures underlying cognition and behaviour)
- Advanced data analysis and neuroimaging techniques
- This cutting-edge programme is at the forefront of a new, rapidly emerging field
- It is highly multidisciplinary, covering the theory and practice of computational and cognitive neurosciences; areas of application range from machine learning to brain-computer interfaces, to research in cognitive and clinical neuroscience
- We have strong links with industry. You can decide to carry out your final research project in collaboration with one of our industry partners and collaborators, paving the way for employment and post-Masters internship opportunities.
Modules
You will study the following compulsory modules: Foundations of Neuroscience 15 credits Statistical Methods 15 credits Cortical Modelling 15 credits Cognitive Neuroscience 15 credits Modelling Cognitive Functions 15 credits Advanced Quantitative Methods 15 credits You will also undertake a 60 credit research project investigating an aspect of cognitive neuroscience using computational modelling, advanced data analysis methods, or a combination of these techniques. Culminating in a 10,000 word dissertation, the project will be carried out by combining the computational, experimental and data analysis skills that students will acquire over Term 1 and 2. Optional modules You'll then have the option to take one, or both of the following optional modules. If you choose just one of these modules, then you can also choose an additional option from a list which is published on an annual basis. Introduction to coding with MATLAB 15 credits Data Programming 15 credits Please note that due to staff research commitments not all of these modules may be available every year.
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. Applications will be reviewed on a case-by-case basis. Depending on previous background and experience, applicants may be required to take one or more pre-sessional courses (for example in programming, statistics, or maths) prior to the start of the programme. These courses will be free to MSc offer holders. If English isn’t your first language, you will need an IELTS score (or equivalent English language qualification) of 6.5 with a 6.5 in writing and no element lower than 6.0 to study this programme.
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
Provider information
Goldsmiths, University of London
New Cross
Lewisham
SE14 6NW