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    Cognitive Neuroscience and Human Neuroimaging

    School of Psychology, Faculty of Science

    Gain in-depth training in core aspects of cognitive neuroscience and human neuroimaging, enabling you to generate and interpret neurobiological data in order to draw conclusions from healthy and unhealthy brains. You'll develop skills in neuroimaging, neurophysiological data collection and analysis techniques.

    Course description

    This 12-month course is designed to provide you with in-depth training in the core aspects of cognitive neuroscience and human neuroimaging, enabling you to generate and interpret neurobiological data in order to draw conclusions from healthy and unhealthy brains.

    We will also train you in neuroimaging and neurophysiological data collection and analysis techniques, allowing you to investigate and understand the brain-behaviour interrelationship.

    Throughout your course, our neuroscientists will introduce you to key investigative techniques which may include functional and structural MRI, EEG, neuropsychology, transcranial magnetic stimulation and transcranial direct current stimulation. Once you have mastered the techniques you need, you will have opportunities to apply these throughout your course to test hypotheses in areas including attention, executive functioning, Alzheimer’s disease, autism and ADHD.

    Over six months, you will work on your research project in cognitive neuroscience with one of our world-leading experts in the Department of Psychology. Your research topic could range from theoretical to basic and to more applied cognitive neuroscience. You may have the opportunity to collect and analyse real-life cognitive brain science data, using state-of-the-art equipment, before presenting your findings at our summer postgraduate students' conference. This project gives you the opportunity to put your new techniques in experimental neuroscience into practice, while exploring ideas at the cutting-edge of cognitive neuroscience. MSc research projects often form the basis of publications in peer-reviewed journals.

    Example research projects
    • The role of vascular damage in Alzheimer’s disease: Altering brain structure and cognitive function
    • Neurovascular coupling in ageing
    • Investigating the effects of transcranial direct current stimulation (tDCS) on brain activity, neurovascular coupling and neuroimaging signals in an animal model
    • Investigating the neuroanatomical correlates of depression and anxiety in Alzheimer’s disease: a voxel-based morphometry study.
    • Neural activity correlates of working memory
    • Examining plasticity of the visual cortex using high-frequency visual stimulation and EEG
    Example past papers published, including student authors
    • Brooke JM, James SS, Jiminez-Rodriguez A, Wilson SP (2022) Biological action at a distance: Correlated pattern formation in adjacent tessellation domains without communication. PLoS Computational Biology. doi:10.1371/journal.pcbi.1009963
    • Wilson SP, James SJ, Whiteley DJ, Krubitzer LA (2019) Limit cycle dynamics can guide the evolution of gene regulatory networks towards point attractors. Scientific Reports 9: 16750. doi:10.1038/s41598-019-53251-w
    • Bruyns-Haylett M, Luo J, Kennerley AJ, Harris S, Boorman L, Milne E, Vautrelle N, Hayashi Y, Whalley BJ, Jones M, Berwick J, Riera J & Zheng Y (2016) The neurogenesis of P1 and N1: a concurrent EEG/LFP study. NeuroImage.
    • Dickinson A, Jones M & Milne E (2016) Measuring neural excitation and inhibition in autism: different approaches, different findings and different interpretations. Brain Research.
    • Slack R, Boorman L, Patel P, Harris S, Bruyns-Haylett M, Kennerley A, Jones M & Berwick J (2016) A novel method for classifying cortical state to identify the accompanying changes in cerebral haemodynamics. Journal of Neuroscience Methods, 267, 21-34

    If you have a passion for understanding the brain and behaviour, whether your background stems from biology, engineering, physics, mathematics, psychology or medicine, this interdisciplinary course has been designed to ensure that you'll gain in-depth knowledge of the fundamentals of neuroscience and research methods in cognitive neuroscience, ready for an exciting career in research or industry.

    The University is home to the Neuroscience Institute which brings together internationally-recognised expertise in medicine, science and engineering to improve the lives of patients and families affected by neurological, sensory and developmental disorders.

    Other courses in cognitive neuroscience

    We offer MSc courses that cover the full breadth of cognitive neuroscience, from the biological basis to imaging and simulation, allowing you to discover the area that you’re most interested in:

    Do you have a question? Talk to us

    Book a 15-minute online meeting with our director of postgraduate recruitment to find out more information and ask further questions.

    Book an appointment with Dr Vanessa Loaiza


    A selection of modules is available each year - some examples are below. There may be changes before you start your course. From May of the year of entry, formal programme regulations will be available in our Programme Regulations Finder.

    You'll study:

    Fundamentals of Cognition

    The module provides an overview of the fundamental issues in cognitive neuroscience and its contributory disciplines. The approach taken is in terms of its development over the past 50 years, providing an overview of the key concepts in the information processing approach and in cognitive science, followed by an analysis of the advances that have been made recently using cognitive neuroscience techniques. Topics include: fundamental issues in cognition (memory, attention, learning, language); theoretical approaches including cognitive neuropsychology, symbolic and sub-symbolic modelling; and methodological issues.

    15 credits
    Fundamentals of Neuroscience

    The module provides an introduction to core aspects of contemporary neuroscience, and it will consider the current state of knowledge in the field, central theoretical issues and key practical approaches. Topics that are discussed include: neural signalling, sensation and sensory processing, movement and its central control, the 'changing brain' (development and plasticity in the nervous system) and complex brain functions.

    15 credits
    Neuroimaging 1

    This module provides an overview of neuroimaging techniques and fundamental data analysis methodologies. Specifically, it will focus on the functional imaging techniques of electrophysiology, optical methods and calcium imaging, each of which will be introduced in the lecture component of the module. In the associated lab classes, students will gain first-hand experience of analysing and processing data sets arising from these techniques.

    15 credits
    Research Methods in Cognitive Neuroscience

    Researchers in Cognitive Neuroscience use a range of different methods and techniques to better understand the biological processes underpinning cognition. An understanding of the differences between these methods, and their advantages and disadvantages when addressing different research questions, is critical for being able to understand existing research as well as designing and conducting novel research projects. 

    This module provides an introduction to a range of state-of-the-art methods used in cutting-edge cognitive neuroscience research, such as EEG, eye-tracking, and tDCS. The module comprises a mix of lectures introducing each technique, demonstrations where students will gain hands-on exposure to cognitive neuroscience equipment, and seminars where students present a recent scientific article using that method. By the end of the module, students will have acquired the knowledge and understanding of a range of cognitive neuroscience methods, their benefits and pitfalls, and be able to use that gained understanding to critically evaluate published research and design new studies. 

    15 credits
    Neuroimaging 2

    This module provides an overview of neuroimaging techniques and fundamental data analysis methodologies employed, specifically those based around functional magnetic resonance imaging (fMRI). The two aspects of neuroimaging (techniques and data analysis) will be taught over the semester. For neuroimaging techniques, after introducing the physical principles underlying fMRI, a description of fMRI-based methods for mapping brain structure and function will follow. For neuroimaging data analysis, the general linear model methodology will be introduced based on the software SPM (Statistical Parametric Mapping), which is one of the most widely used packages for fMRI data analysis. Issues concerning fMRI experimental de-sign and efficiency will also be discussed and taught in depth.

    15 credits
    Research Project in Cognitive Neuroscience

    The module allows students to work on an extended research project within computational neuroscience and/or cognitive neuroscience and/or systems neuroscience and/or analysis of brain imaging data. Students will learn and apply appropriate research techniques, analyse and interpret the results, and write up the research findings using recognised journal frameworks. Students will receive guidance and regular feedback from their supervisors. The project culminates in an oral presentation and a written dissertation.

    75 credits

    You'll study one module from this group (15 credits):

    Scientific programming in computational and cognitive neuroscience

    This module develops practical skills in scientific programming in the context of computational and cognitive neuroscience. The course begins with an introduction to basic programming concepts and visualisation techniques. The rest of the module covers advanced skills relevant to contemporary computational and cognitive neuroscience, such as analysis of neural data and running simulations. Techniques introduced include probabilistic methods, dimensionality reduction, classification, and time series analysis. Emphasis is placed on practical skills developed during lab classes.

    15 credits
    Data Analysis and Visualisation

    This module provides basic skills in computational data analysis. Students will learn how to import/export scientific data sets in different formats, how to process and transform them, and how to visualise results. Teaching will be hands-on and computer lab-based. Teaching will focus on the programming language R and associated scientific software. No prior programming experience will be necessary.

    15 credits

    You'll study one module from this group (15 credits):

    Neurocognitive Modelling

    This module concerns inferring and modelling neural and cognitive processes underlying human behaviour using computational means. One part of the module will cover normative models, which allow us to solve problems optimally along with their neural or cognitive representations. The other part of the module will focus on cognitive models, which involve fitting models to behavioural data to estimate latent parameters that are assumed to underlie the data and allow us to make inferences about their properties.

    15 credits
    Systems Neuroscience

    The module provides an advanced understanding of the brain's major computational systems and the theoretical or model-driven approaches to research of these topics. Major processing units of the brain will be described and, where appropriate, emphasis will be placed on understanding each of these structures in terms of both their micro- and macro-circuitry. One focus of the module will be to impart an appreciation of how many fundamental questions relating to brain function requires study at a range scales, from single cell to whole brain and behaviour. The various strategies adopted for investigating and modelling brain-circuits, and the consideration of circuits as the defining feature of brain systems, will be presented.

    15 credits

    The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.

    Open days

    An open day gives you the best opportunity to hear first-hand from our current students and staff about our courses.

    You may also be able to pre-book a department visit as part of a campus tour.Open days and campus tours


    1 year full-time


    You’ll learn through hands-on laboratory sessions, problem-solving classes, lectures, seminars and individual projects.

    Your individual research project will account for 75 credits of your course, where you’ll be working alongside PhD students and experienced postdoctoral researchers. Here you’ll gain extensive first-hand experience as a researcher, and will have access to the outstanding research facilities in Sheffield.


    You’ll be assessed through formal examinations and coursework which may include essays, poster presentations, coding assignments, and a dissertation.

    Regular feedback is provided, so students can understand their own development throughout the course.

    Your career

    With the valuable skills and knowledge that you’ll develop throughout your research training, including computational modelling, imaging, and analysis expertise, you’ll be well equipped for careers including:

    • analysis and visualisation of data within hospitals, other healthcare providers or the pharmaceutical industry
    • roles within deep learning, machine learning or artificial intelligence
    • pursuing a career in research, understanding major diseases like stroke, Alzheimer’s, Parkinsons and epilepsy within academia or governmental organisations.

    If you choose to continue your research training, this course is great preparation for a PhD in areas including neuroscience, artificial intelligence, and brain interfaces or to begin clinical training.


    School of Psychology

    Lecturer demonstrating an EEG is a test to a class. A student wears a headpiece used to evaluate the electrical activity in the brain

    The School of Psychology at Sheffield is focused on exploring the science behind the human brain and human behaviour.

    Our teaching is informed by cutting-edge scientific research, which ranges from neuroscience through to child development and understanding why psychological therapies are effective. All of this has an impact on wider society.

    Our work explores health and wellbeing, lifestyle choices, cognitive behavioural therapy, safe driving, mother-baby interaction, autism, Parkinson's disease, and reducing prejudice and inequality. It’s research like this that our students are able to get involved in throughout their course.

    Entry requirements

    Minimum 2:1 undergraduate honours degree in either a life science (including psychology) or a mathematical/physical science (including engineering).

    We also accept medical students who wish to intercalate their studies. 

    We also consider a wide range of international qualifications:

    Entry requirements for international students

    Overall IELTS score of 6.5 with a minimum of 6.0 in each component, or equivalent.

    Pathway programme for international students

    If you're an international student who does not meet the entry requirements for this course, you have the opportunity to apply for a pre-masters programme in Science and Engineering at the University of Sheffield International College. This course is designed to develop your English language and academic skills. Upon successful completion, you can progress to degree level study at the University of Sheffield.


    We accept medical students who wish to intercalate their studies. Find out more on the School of Medicine and Population Health website.

    If you have any questions about entry requirements, please contact the department.

    Fees and funding

    Department bursaries

    Each year we offer two bursaries to students on this course. If you're awarded a bursary you'll receive a £1,500 reduction in your tuition fees. These bursaries are awarded on a competitive basis, based on:

    • academic performance as indicated by a grade point average and transcript
    • other relevant skills and knowledge (for example, programming courses outside the degree or relevant work experience)
    • research activity (co-authoring papers, conference presentations, etc)
    • personal statement, which should include information on why you want to do the course you have applied for and how it fits with your aspirations

    To be considered for a bursary in the year that you intend to start your course, submit your application to study with us by 31 May. All applications received before this deadline will automatically be considered for a bursary.


    You can apply now using our Postgraduate Online Application Form. It's a quick and easy process.

    Apply now


    +44 114 222 6533

    Any supervisors and research areas listed are indicative and may change before the start of the course.

    Our student protection plan

    Recognition of professional qualifications: from 1 January 2021, in order to have any UK professional qualifications recognised for work in an EU country across a number of regulated and other professions you need to apply to the host country for recognition. Read information from the UK government and the EU Regulated Professions Database.