MSc Cognitive Neuroscience and Human Neuroimaging
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Understanding how brain structure, function, and development shape human behaviour is one of the most important challenges in current science. Addressing this challenge will lead to fundamental insights into human cognition and will suggest new treatments for brain disease and disorder. To get there, we need to make use of cutting edge tools and technologies for visualising brain dynamics, we need to leverage new techniques from psychological science, and we need to make sense of experimental data with smart new approaches to data analysis. The MSc Cognitive Neuroscience and Human Neuroimaging programme provides you with training in neuroanatomy, neuroimaging, neurophysiological data collection, and analysis techniques, allowing you to investigate and understand human behaviour, ready to make discoveries at the frontier of modern cognitive neuroscience. Throughout your course, you’ll use pre-existing data sets and have the opportunity to collect your own neuroimaging and neurophysiological data, giving you the chance to put your new technical knowledge of cognitive brain science into practice and draw conclusions from healthy and unhealthy brains. 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 all students gain in-depth knowledge of the fundamentals of neuroscience, ready for an exciting career in research or industry. |
Explore the breadth of cognitive neuroscienceAt Sheffield, we have a strong research track-record in computational neuroscience, cognitive neuroscience, and systems neuroscience. Because of these expertise, our courses cover the full breadth of cognitive neuroscience, from the biological basis, to imaging and simulation, allowing you to discover and focus on the area that you’re most interested in as you progress through your course. Other courses in cognitive neuroscience: |
ApplyingTo apply for this course, complete the University of Sheffield's postgraduate online application form. Programme codes: You can find more information about the application process on the University's postgraduate webpages. |
ContactCourse Director: Dr Hannes Saal If you would like to know anything else about this course, contact: psy-pg-admissions@sheffield.ac.uk | +44 (0)114 222 6533 You can also visit us throughout the year: Pathway programme for international students |
| About the course |
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. Throughout your course, our neuroscientists will introduce you to key investigative techniques including functional and structural MRI, skin conductance response recording, neuropsychology, transcranial magnetic stimulation and transcranial direct current stimulation. Once you’ve mastered the techniques you need, we’ll give you plenty of opportunities to apply these throughout your course to test hypotheses in areas including emotional influences on behaviour, executive functioning, Alzheimer’s disease, epilepsy, motor neuron disease and more. In semester one, you’ll build on your existing knowledge, giving you a thorough understanding of the cognitive neuroscience, computational neuroscience, mathematical modelling and simulation. Once you’ve developed a solid foundation in these areas at the core of cognitive neuroscience and human neruroimaging, semester two will be devoted to advanced modules where you’ll tailor your learning and choose to specialise in one of two distinct routes of study: pathway 1 or pathway 2. Pathway 1 will give you an in-depth knowledge of practical neuroanatomy, training you in cutting-edge neuroimaging techniques whilst also introducing you to the brain’s major computational systems and how they're modelled. Pathway 2 will build on your technical skills in computational neuroscience, exploring advanced mathematical and computational models alongside neuronal information processing. Whichever route you choose, this training will develop your transferable skills in critical reading, writing, project management, computational modelling, data analysis and visualisation, and scientific programming using the languages Python and MATLAB. The biggest part of your course is the Research Project in Cognitive Neuroscience. Over three months you’ll work with one of our world-leading experts based in the Department of Psychology. Research topics could range from theoretical, to basic neuroscience, with 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 student-led conference. These projects give you the opportunity to put your new techniques in experimental neuroscience into practice whilst exploring ideas at the cutting-edge of cognitive neuroscience. It's common for MSc research projects to form the basis of publications in peer-reviewed journals. Example research projects include:
Example past papers published including student authors:
In addition to technical skills and specialist knowledge of cognitive and computational neuroscience, throughout your course you’ll also develop transferable skills around critical thinking and communication, sought after by employers around the globe. In order to build these skills, you’ll learn through small-group teaching in a mixture of seminars and lectures, and problem solving, programming and laboratory classes. You’ll be assessed through formal examinations and coursework which may include essays, presentations and a dissertation. Read more about this course on the University of Sheffield's webpages for postgraduate students: |
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After your degree |
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Entry requirements |
For this course, we usually ask for a 2:1 honours degree or equivalent qualification in either a life science (including psychology) or mathematical/physical science (including engineering). If your background is in life sciences, we will teach you any relevant mathematics and basic coding skills. If you have a qualification in mathematics, engineering, or the physical sciences, this degree includes is an introductory neuroscience course to ensure that all students have the same key knowledge. We also accept medical students who wish to intercalate their studies. 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 International pathway programmes If you are an international student who does not meet our entry requirements, the University of Sheffield International College offers a Pre-Masters in Science and Engineering programme. This programme is designed to develop your academic level in your chosen subject, introduce you to the study skills that will be vital to success and help with language if you need it. Upon successful completion, you can progress to this degree at the University of Sheffield. 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.
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. The English Language Teaching Centre offers English language courses for students who are preparing to study at the University of Sheffield. |
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| Funding and scholarships |
Funding is available, depending on your fee status, where you live and the course you plan to study. You could also qualify for a repayable postgraduate masters loan to help fund your studies. Funding your postgraduate course
Up-to-date fees can be found on the University of Sheffield's webpages for postgraduate students: Departmental Taught Postgraduate Bursaries Each year we offer two bursaries to students on this program. 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:
To be considered for a bursary in the year that you intend to start your course, submit your application by 31 May. All applications received before this deadline will automatically be considered for a bursary. |
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Nora’s research project was the highlight of her studies and has inspired her to pursue a PhD in the field of Multiple Sclerosis in the future.
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Georgia initially came to Sheffield to study BSc Psychology which gave her the perfect foundation to progress onto this masters.
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OUR RESEARCH Active Touch Laboratory
We're using methods in animal behaviour, neuroethology, human psychophysics, computational modelling and robotics to investigate tactile sensing in animals, people and intelligent machines. |
OUR RESEARCH The University of Sheffield Neuroscience Institute
We aim to deepen our understanding of function and dysfunction of the nervous system, through translational neuroscience, computational and systems neuroscience and sensory and developmental neuroscience to improve the lives of patients and families affected by devastating disorders of the nervous system. |
Current modules
All students will study:
| Fundamentals of Cognition (15 credits) |
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, and theoretical approaches including cognitive neuropsychology, symbolic and sub-symbolic modelling, and methodological issues. Assessment: Examination |
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| Fundamentals of Neuroscience (15 credits) |
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 |
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Neuroimaging 1 (15 credits) |
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 design and efficiency will also be discussed and taught in depth. |
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Neuroimaging 2 (15 credits) |
This module further develops on the foundational material in Neuroimaging 1 and provides an overview of neuroimaging techniques and fundamental data analysis methodologies. Specifically, it will focus on the techniques of electrophysiology, EEG, and MEG, 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. |
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Data Analysis and Visualization (15 credits) |
This module will train students in 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 and will focus on the programming language Python and associated scientific software. No prior programming experience will be necessary. |
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Research Project in Cognitive Neuroscience (75 credits) |
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. |
Students will also study two modules in either pathway 1 or pathway 2.
Pathway 1:
| Applied Neuroanatomy and Clinical Neuroscience (15 credits) |
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 |
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| Systems Neuroscience (15 credits) |
The module provides an advanced understanding of the brain's major computational systems and how they have been modelled. Major processing units of the brain (e.g, cerebellum and basal ganglia) will be described and, where appropriate, emphasis will be placed on understanding each of these structures as a series of repeating micro- or macrocircuits. The various strategies adopted for modelling these circuits and their interactions with other brain systems will be presented and their predictions for biology considered. |
Pathway 2:
| Computational Neuroscience 1 (15 credits) |
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. |
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| Computational Neuroscience 2 (15 credits) |
This module is based on the themes of information theory, Bayes' theorem, and learning algorithms. Information theory places limits on how much Shannon information can be transmitted/received by any communication channel, Bayes' theorem provides a method for interpreting incomplete or noisy information, and learning algorithms provide a mechanism for acquiring/storing/retrieving information about the environment. These three related ideas will be explored in the context of neuronal information processing. |
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.
We timetable teaching across the whole of our campus, the details of which can be found on our campus map. Teaching may take place in a student’s home department, but may also be timetabled to take place within other departments or central teaching space.