Advanced Topics in Neuroimaging – Practical Aspects
Run by School of Human and Behavioural Sciences
10.000 Credits or 5.000 ECTS Credits
Organiser: Prof Paul Mullins
Overall aims and purpose
This course provides an intensive practical experience in the MRI techniques used to study the structure, connectivity and metabolism of the brain. The Lab based structure provides training in the application and analysis of advanced imaging techniques. Given that most of these techniques find application in the detection and characterization of pathological changes in the brain, the applications to the study of disease processes is highlighted throughout the course. The ethical implications that are raised by modern neuroimaging techniques and findings and the possible implications of each technique are also discussed alongside the technical implications. As the state of the COVID crisis for Semester 2 is not yet known, it is not clear as yet what method of delivery will be pursued. Some on-campus activity will be inolved though.
Students will carry out most of the work in the Imaging Computer Lab where students will analyse imaging data acquired at the Bangor Imaging Unit. These will include a dataset of 20 young and 20 older, healthy participants, who underwent structural and resting state scans, diffusion tensor and perfusion imaging, as well as magnetic resonance spectroscopy. Where convenient data from publicly accessible databases will also be used. The students will spend the initial 9 weeks analysing different image sequences, in the process familiarizing themselves with a number of imaging techniques and analytical pathways. In the final two weeks, the students will carry out a group level analysis or a patient based analysis, either using data previously processed by themselves and other students in the class, or an entirely novel dataset.
Structural Imaging. T1 and T2 weighted structural scans will be used for multi-spectral tissue classification. Students will need to co-register multispectral images and normalize them using an atlas representative target image. They are expected to generate classified volumes and provide basic statistics concerning CSF. white and grey matter volumes. (Analytical package: FSL and SPM).
Diffusion Tensor Imaging (DTI). Physical principles of DTI will be reviewed. Students will need to register DTI images to structural images using non-linear warping to correct for Eddy currents and susceptibility artefacts. Mean diffusity and anisotropy maps will be computed and seed based white matter tract highlighted. (Analytical package: FSL).
Functional connectivity. Neuro-physiological correlates of slow BOLD fluctuations and spatial-temporal BOLD coherence will be reviewed. Analysis of BOLD coherence: seed- based correlation approach and independent components analysis will be carried out on pre-processed BOLD time-series acquired in the resting state. The aim is to compute resting state networks, including default mode, attention and language networks. (Analytical package: FSL and SPM).
Perfusion imaging. Overview of PET based techniques for estimation of cerebral blood flow. Contrast based vs. non-contrast based estimation of local cerebral blood flood. ASL Images will be analysed to estimate cerebral blood flow. (Analytical package: FSL and SPM).
Spectroscopy. Physical principles. Students will be expected to compute the concentrations of main neuro-metabolites, including glutamate and GABA in a single voxel. Analysis will include corrections for partial volume effects. (Analytical package: SPM and Tarquin/jMRUI).
Ethical implications regarding incidental findings, and possible impact of advanced techniques are introduced and discussed. Discussion will include the ethical implications that arise from the ability to map brain pathways, patterns and metrics of neural connectedness and how these measures may be used in diagnosis, the potential for incidental findings of clinical importance in research participants and how to deal with these findings, and the wider implications of neuroimaging findings and how it may be applied in the wider community.
Links to B Grades • Strong Knowledge • Understands most but not all of subject area • Evidence of background study • Focused answer with good structure • Arguments presented coherently • Mostly free of factual/computational errors • Some limited original interpretation • Well known links described between topics • Problems addressed by existing methods/approaches • Good presentation, accurate communicatoon
Links to C grades. • Knowledge of key areas/principles only; • Limited evidence of background study; • Answer only poorly focused on question & with some irrelevant material & poor structure; • Attempts to present relevant and coherent arguments; • Has several factual/computational errors; • No original interpretation; • Only major links between topic are described; • Limited problem solving; • Many weaknesses in presentation & accuracy
Links to A grades • Comprehensive knowledge; • Detailed understanding of the subject area; • Extensive background study; • Highly focused answer & well-structured; • Logically presented & defended arguments; • No factual/computational errors; • Original interpretation; • New links to topic are presented; • New approach to a problem; • Excellent presentation with very accurate communication
3) Able to process structural, functional connectivity, perfusion and spectral MR data
4) Ability to choose imaging protocols and analysis techniques adequate to study a specific physiological or disease process (e.g. age related atrophy vs. traumatic bleeds)
6) Ability to choose proper analytic tool to determine MR correlates of disease markers
2) Understanding the physical principles underlying structural and metabolic MRI
1) Knowledge of imaging relevant aspects of neuroanatomy, neurophysiology and neuropathology
5) Ability to think clearly and critically about the ethical issues raised by advances in neuroimaging
|Full analysis of a full NeuroImaging Data Set||60.00|
Teaching and Learning Strategy
|Practical classes and workshops||
By working through problems in their own time students experience what neuroimaging analysis is really like. This also provides them with the opportunity to solve problems and errors that occur in their analysis pipeline, and to find solutions themselves - something that is very much expected in the real world of employment. This is perhaps the most valuable part of the module, enabling the students to learn by doing.
- Numeracy - Proficiency in using numbers at appropriate levels of accuracy
- Computer Literacy - Proficiency in using a varied range of computer software
- Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
- Exploring - Able to investigate, research and consider alternatives
- Information retrieval - Able to access different and multiple sources of information
- Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
- Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
- Safety-Consciousness - Having an awareness of your immediate environment, and confidence in adhering to health and safety regulations
- Presentation - Able to clearly present information and explanations to an audience. Through the written or oral mode of communication accurately and concisely.
- Teamwork - Able to constructively cooperate with others on a common task, and/or be part of a day-to-day working team
- Argument - Able to put forward, debate and justify an opinion or a course of action, with an individual or in a wider group setting
Subject specific skills
- Understand the scientific underpinnings of psychology as a discipline.
- Communicate psychological concepts effectively in written form.
- Be computer literate for the purpose of processing and disseminating psychological data and information.
- Retrieve and organise information effectively.
- Handle primary source material critically.
- Engage in effective teamwork for the purpose of collaborating on psychological projects.
- Use effectively personal planning and project management skills.
- Work effectively under pressure (time pressure, limited resources, etc) as independent and pragmatic learners.
- Problem-solve by clarifying questions, considering alternative solutions, making critical judgements, and evaluating outcomes.
- Reason scientifically and demonstrate the relationship between theory and evidence.
- Understand and investigate the role of brain function in all human behaviour and experience.
- Use a range of statistical methods with confidence.
- Use a variety of psychological tools, including specialist software, laboratory equipment and psychometric instruments.
Pre- and Co-requisite Modules
Courses including this module
Compulsory in courses:
- C8CU: MSc Neuroimaging year 1 (MSC/N)