Prior to starting my PhD, I essentially had no programming or image processing experience (including in
analysis). Fortunately, I’ve had the opportunity to attend many excellent courses to help learn the skills
necessary to perform the analysis described in the imaging tutorial. Here are a selection of my favourites:
needless to say, this list is not intended to be exhaustive, but rather a pointer in the right direction for
those new to the field.
Dutch Connectome Course
Cognitive and Brain Sciences Unit (CBU), Cambridge
UCS/GSLS, University of Cambridge
Cambridge Coding Academy
Outstanding introduction to the principles and practicalities of performing multi-modal neuroimaging
Rare connectome only course, this is full of high profile speakers and a perfect setup to running
Comprehensive training programmes in matlab, signal processing, computing
Thorough introduction to the workhorses of neuroimaing: shell scripting, python, and R
Run by enthusiastic and highly knowledgeable computer scientists this provides a slightly different
spin on what one what one can do with your data, including advanced visualisation and machine
Handbook of Functional MRI Data Analysis
Olaf Sporns books I&II
Mathematics for Biological Scientists
Matlab for Neuroscientists
Comprehensive, clear explanations, practical examples, well organized. A superb introduction to
One of the original authors to coin the term ‘connectome’ and still a 'figurehead' for the
Excellent refresher of A-level maths with a biological emphasis. Excellent background for
What more is there to say? Matlab is massively popular for all manner of analyses within
and with good reason. This book provides a comprehensive review of how to use it properly.
Barabasi 'Network Science'
Algebra (BBC, SOS math, etc)
Probably the leader in the network analyses: detailed yet approachable, professional yet
An excellent example of a 'pure' matlab course: vital skills to running analyses and a nice learning
Internationally recognized educational site, with a great module on FMRI and statistical appraisal
of the GLM too.
What can I say? The more knowledgeable one has of linear algebra, the easier some many things become
graph theory, signal processing, neuroimaging in general). Get as much as you can.