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Prior to starting my PhD, I essentially had no programming or image processing experience (including in connectome 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.

#courses

FSL course

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 experiments

Rare connectome only course, this is full of high profile speakers and a perfect setup to running analyses

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 learning

#books

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 FMRI.

One of the original authors to coin the term ‘connectome’ and still a 'figurehead' for the field.

Excellent refresher of A-level maths with a biological emphasis. Excellent background for matlab.

What more is there to say? Matlab is massively popular for all manner of analyses within neuroscience, and with good reason. This book provides a comprehensive review of how to use it properly.

#online resources

Barabasi 'Network Science'

MIT matlab

Coursera

Algebra (BBC, SOS math, etc)

Probably the leader in the network analyses: detailed yet approachable, professional yet entertaining.

An excellent example of a 'pure' matlab course: vital skills to running analyses and a nice learning gradient.

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 (matlab, graph theory, signal processing, neuroimaging in general). Get as much as you can.