Basics of MRI

These YouTube videos from Paul Callaghan are great!

Statistical Inference and Dynamical Systems

  1. Cristopher Bishop book on Pattern Recognition and Machine Learning is a great place to start and it is free to download.

  2. Steven Strogatz book on Nonlinear Dynamics and Chaos provides a very good introduction to those uninitiated on the topic; it is not a free download though. But he has his lectures on YouTube.

  3. This review paper on variational inference is a must read for anyone interested in the topic. It has several references which can be really handy to build basic concepts and then go towards more advanced topics.

  4. Will Penny's course slides on Bayesian Inference and Dynamical Systems are one of the best if you are to go towards Dynamic Causal Modelling. All of his lecture slides, available on his website, are worth going through.

  5. Cosma Shalizi’s notebooks have so much of great stuff packed in them. Bookmark it!

  6. For lifelong learning and insights, you cannot go wrong with Richard Feyman’s lectures on physics and you can also watch the master delivering them here.

Statistical Parametric Mapping

  1. SPM course website has powerpoint slides from previous year courses which are very useful to go through. It also lists video recordings of course material (end of the page) which may be especially handy

  2. Methods for Dummies: This is an introductory course which runs at FIL, for those starting afresh in neuroimaging

  3. SPM wikipages provide information on various topics in SPM; it is maintained by international SPM community

  4. SPM book. The latest version (3rd Edition) is for purchase but you can find earlier editions free as pdf.

  5. SPM manual is always handy, isn’t it?

  6. SPM email list archives are an enormous resource, hardly anything not being asked there!

Dynamic Causal Modelling

  1. There are several introductory, non-mathematical papers, see here and here and a gentle introduction to systems theory as applied to functional neuroimaging.

  2. The beginnings in 2003: DCM for functional MRI

  3. Stefan Kiebel’s review paper on DCM extensions to EEG and MEG

  4. The first paper that introduced DCM for resting state fMRI i.e. the spectral DCM

  5. We revisited DCM recently.

Active Inference and Free Energy Principle

Note: I am not linking early formulations of FEP as they are outdated.

  1. Start with a standard text for e.g. Rich Sutton’s Introduction to Reinforcement Learning, to get a handle on Markov Decision Processes. David Silver’s lecture notes are also very useful.

  2. This is a (very) long paper that gets to the heart of active inference and this paper that cast it as a ‘process theory’.

  3. This monograph is the most comprehensive treatment of the free energy principle to date.

  4. Thomas Parr webpage has a lot of useful resources.

  5. This python package and accompanying paper are really great to get started with building your acive inference agents.