PSYC60122
Advanced Image Analysis
15
Semester 2
Postgraduate Taught
Level 6
Jason Taylor
Unit coordinator
School of Psychological Sciences
1
FHEQ level (Framework for Higher Education Qualifications) ' Masters/Integrated Masters P4 '
European Credit Transfer & Accumulation System Rating : 7.5
<p>The course will provide theoretical and practical background to a number of key advanced methods in image analysis including connectivity, diffusion tensor imaging, and EEG/ERP source localisation.</p><p>This will be complemented by a series of lectures focusing on theoretical issues underlying the methodology such as Bayesian inference and probabilistic modelling, signal detection, connectivity, coherence analysis, synchronisation and phase analysis, and the relationship between the BOLD fMRI signal and variables such as blood flow and blood volume. The practicalities, strengths and limitations of combined concurrent EEG/ERP and fMRI acquisition will also be explored.</p><p>Lectures will be linked to practical sessions providing introductory hands-on training in a number of advanced image analysis methods. The course builds on the Image Analysis unit by exploring advances in techniques and proposed solutions to specific problems and challenges.</p>
<p>The course will provide theoretical and practical background to a number of key advanced methods in image analysis including connectivity, diffusion tensor imaging, and EEG/ERP source localisation.</p><p>This will be complemented by a series of lectures focusing on theoretical issues underlying the methodology such as Bayesian inference and probabilistic modelling, signal detection, connectivity, coherence analysis, synchronisation and phase analysis, and the relationship between the BOLD fMRI signal and variables such as blood flow and blood volume. The practicalities, strengths and limitations of combined concurrent EEG/ERP and fMRI acquisition will also be explored.</p><p>Lectures will be linked to practical sessions providing introductory hands-on training in a number of advanced image analysis methods. The course builds on the Image Analysis unit by exploring advances in techniques and proposed solutions to specific problems and challenges.</p>
<ul>
<li>
To provide students with an introduction to, and a working knowledge of, a selection of advanced imaging techniques, focusing on both acquisition and analysis methodology.</li>
<li>
To provide some advanced mathematical, statistical, and neurophysiological background to these methods.</li>
</ul>
<p>At the end of this unit students will:</p>
<ul>
<li>
have a solid grasp of a selection of advanced imaging techniques and how they can be used to contribute to research;</li>
<li>
understand some of the mathematical, statistical and neurophysiological factors underlying these advanced methods;</li>
<li>
understand the neurophysiological issues that need to be addressed by the advanced techniques;</li>
<li>
be able to evaluate the use of advanced image analysis techniques to answer specific questions about brain function;</li>
<li>
be able to select the most appropriate technique to address the question in hand;</li>
<li>
be able to discuss some of the mathematical and statistical models and assumptions that underlie the methods;</li>
<li>
have some specialised analysis skills.<br />
</li>
</ul>
<p>The course will be taught through a combination of linked lectures and lab sessions; 12 x two-hour sessions over six weeks. Teaching will be complemented by the availability of notes, slides and recommended reading.</p>
0
Other
100%
<ul>
<li>
Examination worth 40% of the overall mark.</li>
<li>
Two lab reports each worth 30% of the overall mark.</li>
</ul>
<p> </p>
MSc Neuroimaging for Clinical
MSc Neuroimaging for Clinical
PGDT Taught Component
Mandatory
N
Lectures
24
0
126