Course summary
This unique interdisciplinary course combines aspects of psychology, mathematics and computer science. It uses computational models and artificial intelligence to further the understanding of the brain. You will learn how:
- the brain is believed to work on the cellular, network and systems level
- to develop mathematical models of brain function and use them in simulations
- cognitive phenomena relate to brain activity
- current AI algorithms are based on neuroscience findings
- a range of experimental approaches are used to measure and analyse brain function.
- memories are stored and organised in the brain
- networks of neurons perform computations
- visual illusions find their origins in neural circuits.
Modules
Our core modules will introduce you to the main concepts and methods of machine learning. You will study how neural processes can be understood in computational terms and how they can be analysed using mathematical and computational methods. You will explore cognitive psychology, with a focus on how cognition can be understood in computational terms, simulation and how it compares to AI approaches. You will conduct a research project. In a typical project, you will either: (a) develop an experimental design, prepare stimuli, and to run a study in a small group of subjects, with technical support provided depending on the complexity of the measurement methods, or (b) evaluate an existing set of, for example, fMRI, MEG, EEG or TMS data and interpret the results Through our optional modules, you can learn how to:
- extract useful information about a physical situation from individual and sets of images
- use some of the more advanced or specialised techniques of data collection, organisation and analysis in psychological research. These include eye-tracking, EEG, fMRI, TMS, computational modeling, diary methodologies and workshops
- think about artificial neural networks and deep learning from the perspective of physics
Assessment method
You will be assessed using exams, coursework, and project reports.
Entry requirements
- 2:1 (or international equivalent) - 2:2 (or international equivalent) may be considered provided the applicant has at least one year of relevant work experience or another supporting factor; for quantitatively minded students with a background in psychology, neuroscience, or biosciences as well as those with training in physics, engineering, mathematics, or computer science; no specific biology or computer knowledge required
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
Terms apply, see our website for the most up to date fees www.nottingham.ac.uk/fees
Provider information
University of Nottingham
University Park
Nottingham
NG7 2RD