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MSc(Res) Cognitive Neuroscience and Human Neuroimaging

Programme code: PSYT23

This course is for students who want to pursue a research career in cognitive neuroscience. It includes a 20 week neuroimaging- or neuromodulation-themed research project based in the Department of Neuroscience, so there is more time devoted to independent research than on our MSc Cognitive and Computational Neuroscience course.

Department of Neuroscience

You will collect and analyse data, or analyse pre-existing data sets, in areas including functional MRI and neurophysiological recording (skin conductance response, transcranial magnetic stimulation or transcranial direct current stimulation). Applicants from life science backgrounds will be able to learn neuroimaging and neurophysiological data collection and analysis techniques (eg, statistical parametric mapping), and students from physical sciences, mathematics or engineering will be able to apply their technical knowledge to "real-life" cognitive brain science data.


To apply for this course, complete the University of Sheffield's postgraduate online application form.

Postgraduate online application form

You can find more information about the application process on the University's postgraduate webpages.

How to apply: applying essentials


Course Director: Dr Hannes Saal

If you would like to know anything else about this course, contact Postgraduate Taught Administrator, Linsey Chaplin.

Telephone: +44 (0)114 222 6534

You can also visit us throughout the year:
Postgraduate open days, visit afternoons and online chats

About the course

This course has two pathways for you to choose from. Lectures and seminars on both pathways teach you about the relationship between brain function and the cognitive, perceptual and motor mechanisms that underpin behaviour. There is also a focus on how cognitive neuroscience relates cognitive and behavioural function to its underlying neural substrate.

Teaching is based in the Department of Psychology, where we have a strong track record in both computational neuroscience and cognitive neuroscience, led by the Centre for Signal Processing in Neuroimaging and Systems Neuroscience. Your research project will be based in the Department of Neuroscience, where there is significant expertise in using neuroimaging and neurophysiological recording techniques in the biological investigation of neurological and psychiatric disorders. Research in both departments also includes modulation of neural systems by novel treatments such as transcranial magnetic stimulation and transcranial direct current stimulation.

Investigative techniques covered: Functional MRI, structural MRI, skin conductance response recording, neuropsychology, transcranial magnetic stimulation, transcranial direct current stimulation

Areas of interest covered: Alzheimer's disease, epilepsy, motor neuron disease, perception, social cognition and communication (particularly theory of mind, empathy and emotion regulation)m executive functioning, EEG and autism, eye-tracking and visual attention, decision-making, development of cognition, emotional influences on behaviour

Depending on the pathway chosen, this degree will give you:

  • A broad and critical understanding of the latest cognitive and computational neuroscience
  • An appreciation of different approaches to understanding brain function
  • An in-depth knowledge of practical neuroanatomy
  • A range of computational and analytic skills relevant to the modelling of brain function
  • The ability to generate and test specific experimental hypotheses which incorporate constraints derived from psychophysics, cognitive neuroscience, and behavioural studies.
  • An appreciation of an academic scientific environment that rewards innovation, fosters a sense of community, and encourages students to direct their own learning.
  • The opportunity to conduct an extended research project involving neuroimaging / neurophysiological data which will put you in an excellent position to pursue an research career in a wide range of neuroscience fields
Technical content on Pathway 1

Pathway 1 of this course use mathematical concepts, but a large amount of teaching time is devoted to these areas, so the main thing we ask for is a willingness to learn. For example, you will learn about:

  • probability theory, probability density functions, Bayes' theorem and maximum likelihood estimation
  • calculus, differential equations, and finding extrema of functions
  • the general linear model for regression and parameter estimation
  • programming MatLab to test computational models

Application advice: If you intend to take Pathway 1 of this course, you should include one or two paragraphs of text when completing your application form, giving evidence of your mathematical experience or qualifications, to show us that you will be able to tackle this type of material. Please note that previous experience in statistics, rather than mathematics, will not usually cover these areas.

To get some idea of the sort of technical knowledge you'll be aiming to have at the end of your course, take a look through the following PDF documents.

Entry requirements

For this course, we usually ask for an upper second class (2:1) degree or equivalent in either a life science, a physical science or mathematics. If you intend to take Pathway 1 of this course, you should also include one or two paragraphs of text when completing your application form, giving evidence of your mathematical experience or qualifications, to show us that you will be able to tackle the type of material listed under the 'Technical content' tab.

If your background is in life sciences, you can take specially-designed mathematics and programming classes during your degree. Relevant mathematics teaching is built into individual modules.

If you have a qualification in mathematics, engineering, or the physical sciences, there is an introductory neuroscience course to ensures all students have the same key knowledge.

We can also accept qualifications from other countries. You can find out which qualifications we accept from your country on the University's webpages for international students.

Prospective international students: Your country

English Language Requirements

If you have not already studied in a country where English is the majority language, it is likely that you will need to have an English language qualification. We usually ask for:

  • International English Language Testing Service (IELTS): Overall grade of of 7.0 with no less than 7.0 in writing and no less than 6.0 in reading, speaking and listening

You can find out whether you need to have an english language qualification, and which other English language qualifications we accept, on the University's webpages for international students.

English language requirements

The English Language Teaching Centre offers English language courses for students who are preparing to study at the University of Sheffield.

English Language Teaching Centre

Fees and funding

Up-to-date fees and funding opportunities can be found on the University of Sheffield's webpages for postgraduate students. These may include scholarships for home and international students and a 10% discount for University of Sheffield graduates.

Postgraduate taught course fees and funding

Departmental Taught Postgraduate Bursaries

Each year we offer seven bursaries to students on one of our masters courses. Students who are awarded a bursary get a £1,500 reduction in their tuition fees. These bursaries are awarded on a competitive basis, based on:

  • Academic performance as indicated by GPA 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 for a course you intend to start in 2017, submit your application by Monday 1 May 2017. All applications received before this deadline will be considered for a bursary.

What our graduates say

After finishing my undergraduate studies in biomedical engineering, my next step was to pursue a master’s degree focusing towards my passion for cognitive neuroscience. The course provided me with a broad range of modules helping me to gain a deep insight into the different areas of the cognitive neuroscience and brain imaging. The intensive master’s project helped me to develop my technical and critical thinking skills whilst increasing my knowledge and understanding of the field. The combination of lab-based and theoretical modules provided during the course qualified me for pursuing my ambition in research and land my desired PhD position at UCL. Studying the CNHN course was the best choice I made during my studies. I would strongly recommend this course to anyone interested in pursuing their interest in cognitive neuroscience research!

Mahtab Farahbakhsh

Current modules

The modules listed below are examples from the current academic year. Students choose to follow one of two pathways. There may be some changes before you start your course.

Pathway 1 is more focused on mathematical techniques and programming, computational neuroscience and MR-physics. There is an emphasis on how computational neuroscience uses neuroscientific data to construct rigorous computational models of brain function.

Pathway 2 is more focused on neuroanatomy (including a five-week, practical human-brain dissection course), neuroradiology, clinical neurology and ethics.

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.

Core modules:

PSY6305: Fundamentals of Cognitive Neuroscience (15 credits)

Module leader: Professor Rod Nicolson

This module provides an overview of the fundamental issues in cognitive neuroscience and its contributory disciplines. Topics include: fundamental issues in cognition (memory, attention, learning, perception, affect). Developmental processes from neuroscience, psychology and dynamic systems perspectives. Theoretical approaches including cognitive neuropsychology, symbolic and sub-symbolic modelling, and methodological issues.

Assessment: Examination

PSY6306: Fundamentals of Neuroscience (15 credits)

Module leader: Professor Paul Overton

This module provides an introduction to core aspects of contemporary neuroscience, and describes 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.

Assessment: Examination

MED624: Applied Neuroimaging, Neurophysiology and Psychiatry (15 credits)

Module leader: Dr Tom Farrow

This module provides an overview of neuroimaging techniques (mainly fMRI), neurophysiology (SCR, EEG, TMS and tDCS) and an introduction to psychiatry. Complementary to the 'Brain Imaging' module, this teaching block will address clinical applications and their use in human subjects. Through, lectures, practical classes and tutorials the module begins with an overview of human brain anatomy and then examines the uses and limitations of techniques for examining and modulating brain activity. The neuroethics of brain imaging will also be discussed. Topics covered in the psychiatry component include: schizophrenia, neuropsychological testing, the neural and molecular bases of psychiatric disorders, psychiatric genetics and animal models of psychiatric disorders.

Assessment: Coursework

MED634: Research Project (90 credits)

Module leader: Dr Tom Farrow or Dr Myles Jones

This module will provide the opportunity to learn and apply research methodologies to test a specific scientific hypothesis. Projects will involve collection and analysis of data or analysis of pre-existing data sets in areas including fMRI and neurophysiological recording (skin conductance response [SCR], transcranial magnetic stimulation [TMS] or transcranial direct current stimulation [tDCS]). Students will carry out a 20 week research project, culminating in an oral presentation and dissertation describing their research. Students will be expected to join in with the Departmental seminars, journal clubs and supervisor meetings, to learn and experience the role of a scientific researcher. The extended project is sufficiently long to allow students to gain extensive experience of independent research.

Assessment: 12,000 word dissertation

Pathway 1 modules:

PSY6307: Computational Neuroscience 1: Biologically Grounded Models (15 credits)

Module leader: Dr Stuart Wilson

This module provides an introduction to methods in computational neuroscience from two different, but complementary perspectives. First, a high-level or ‘top-down’ view explores how neurons encode and decode sensory information. Second a ‘bottom-up’ or mechanistic approach looking at single neuron models at different levels of abstraction – from a simple ‘integrate-and-fire’ approximations to full conductance-based compartmental models. Throughout this module, the emphasis is on the use of mathematical and computational models of single neuronal function.

Assessment: Examination

PSY6309: Mathematical Modelling and Research Skills (15 credits)

Module leader: Dr Hannes Saal and Dr Robert Schmidt

This module develops basic skills required to understand and participate in research in computational and cognitive neuroscience. The course begins with a refresher course in reading and writing skills, understanding of quantitative data and basic algebra and calculus. The course moves on to cover more advanced mathematical material such as matrix algebra, ordinary differential equations, concepts in probability and statistics, and optimisation methods. Programming skills are introduced via the MatLab modelling language. All topics are illustrated by application to concrete modelling examples relevant to contemporary neuroscience.

Assessment: Coursework

PSY6310: Brain Imaging and its Physical Foundations

Module leader: Dr Liat Levita and Dr Aneurin Kennerley

This module provides an overview of neuroimaging techniques, especially those based on functional magnetic resonance imaging (fMRI). After introducing the physical principles underlying fMRI, a description of fMRI-based methods for mapping brain structure and function will follow. Methods for analysis of MRI data will be presented based on the program SPM, which is one of the most widely used packages for fMRI data analysis. Other topics include optical imaging spectroscopy and the simultaneous use of electrophysiological recording with imaging.

Assessment: Examination

Pathway 2 modules:

BMS6054: Ethics and Public Awareness of Science

Module leader: Dr Andrew Furley

This unit introduces an outline of the legislative limitations and ethical influences on biomedical science. It will address how these are influenced by public attitudes and explore how these, in turn, are influenced by the scientific community. The unit will contain a factual and objective core, however students will be encouraged to explore, develop and express their own beliefs and value systems.

Assessment: Poster presentation and debate

MED661: Neuroanatomy and Neuroradiology

Module leader: Dr Tom Farrow

This module comprises studying practical neuroanatomy (human brain dissection) and an overview of neuroradiology (mainly magnetic resonance imaging [MRI] and computed tomography [CT]). The two complementary components of neuroanatomy and neuroradiology will be taught in parallel over the semester. For neuroanatomy, a five-session programme involving practical brain dissection and detailed coverage of the structural and functional units of the human brain will be undertaken. For neuroradiology a series of lectures will be given. Both components will be supported by tutorials.

Assessment: Practical spotter exam

PSY6319: Brain Imaging and Clinical Neurology (15 credits)

Module leader: Dr Liat Levita and Dr Tom Farrow

This module comprises studying specific aspects of clinical neurology (neuroinflammation and neurodegeneration) and an overview of neuroimaging data analysis methodologies employed, specifically those based around functional magnetic resonance imaging (fMRI). The two complementary components of clinical neurology and neuroimaging data analysis will be taught in parallel over the semester. The clinical neurology lectures will cover disorders including multiple sclerosis, ataxia, motor neurone disease, Huntington’s Chorea, Alzheimer’s Disease and Parkinson’s Disease. 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 design and efficiency will also be introduced.

Assessment: Coursework and examination