fMRI researchers with beginning to intermediate skill levels. For those who are just getting started with fMRI, the course gives you a comprehensive set of tools and software to get started with your own studies. For those who are more advanced, the course provides advanced training in ICA and techniques for maximizing study validity, efficiency, and power, and discussion of best practices and advanced topics.
We pair interactive lectures with hands-on demonstrations and work-through sessions. Each participant works on their own laptop. Software will be installed on each student's laptop during the beginning of the course, including Matlab (a trial version), SPM12, the Group ICA of fMRI Toolbox (GIFT), and related toolboxes, including CANlab Core Tools for interactive fMRI analysis, statistical nonparametric mapping (SnPM), and the multi-level mediation fMRI toolbox (M3). Alongside the lectures, participants will be trained to analyze sample fMRI data on their laptops using these tools. The course will be small and interactive, with many opportunities to work closely with the faculty.
Registration will be on a first-come, first-served basis; we apologize in advance if we cannot accommodate all who wish to attend, but we will admit as many people as possible given the interactive nature of the course.
MRI Physics
Optimizing human factors: Running a high-quality MRI study
Equipment and timing considerations in the MR environment
Signal processing basics and pitfalls to avoid
SPM12 software
Basic and advanced General Linear Model analysis for fMRI
Thresholding and multiple comparisons
False positive neuroscience, circular inference, and avoiding pitfalls
Experimental design - design choices, considerations, and technical optimization
Independent Component Analysis: Fundamentals and practice
GIFT ICA software
Advanced ICA: Variations, advanced extensions, and integration with machine learning
Resting-state connectivity
Mediation analysis and path modeling
Machine learning and pattern recognition: Fundamentals and practical implementation
Websites:
• fMRI for newbies
http://culhamlab.ssc.uwo.ca/fmri4newbies/
• SPM manual and documentations
http://www.fil.ion.ucl.ac.uk/spm/doc/ and
http://merlin.psych.arizona.edu/~dpat/Public/Imaging/SPM/spm2docs/SPM2_eng.pdf
• SPM short course notes
http://www.fil.ion.ucl.ac.uk/spm/course/
• Introduction to SPM stats
http://www.mrc-cbu.cam.ac.uk/Imaging/Common/spmstats.shtml
• ICA of fMRI overview
http://mialab.mrn.org/software/gift/publications.html
• GIFT website and manual
http://mialab.mrn.org/software/gift
http://mialab.mrn.org/software/gift/docs/v1.3h_GIFT_Walk_Through.pdf
• Statistical Nonparametric Mapping (SnPM)
http://www2.warwick.ac.uk/fac/sci/statistics/staff/academic-research/nichols/software/snpm
• Experimental design (Rik Henson)
http://www.mrc-cbu.cam.ac.uk/Imaging/Common/fMRI-efficiency.shtml
Selected fMRI Methods Papers and Chapters:
Wager, T. D. & Lindquist, M. A. This book provides comprehensive coverage of the key concepts involved in current fMRI acquisition and analysis. Available online at https://leanpub.com/principlesoffmri.
V. D. Calhoun and T. Adalı, "Multi-subject Independent Component Analysis of fMRI: A Decade of Intrinsic Networks, Default Mode, and Neurodiagnostic Discovery," IEEE Reviews in Biomedical Engineering, vol. 5, pp. 60-73, 2012
E. Erhardt, S. Rachakonda, E. Bedrick, T. Adalı, and V. D. Calhoun, "Comparison of multi-subject ICA methods for analysis of fMRI data," Human Brain Mapping, vol. 12, pp. 2075-2095, 2011
V. D. Calhoun, R. Miller, G. D. Pearlson, and T. Adalı, "The chronnectome: Time-varying connectivity networks as the next frontier in fMRI data discovery," Neuron, vol. 84, pp. 262-274, 2014
Wager, T. D., Hernandez, L., Jonides, J., & Lindquist, M. (2007). "Elements of functional neuroimaging," J. T. Cacioppo, L. G. Tassinary & G.G. Berntson (Eds.), Handbook of Psychophysiology (4th ed., pp. 19-55). Cambridge: Cambridge University Press."
Wager. T. D., Lindquist, M., and Hernandez, L. (2009). "Essentials of functional neuroimaging," Handbook of Neuroscience for the Behavioral Sciences.
Wager, T. D., & Lindquist, M. A. (2011). "Essentials of functional magnetic resonance imaging," Handbook of Social Neuroscience.
Lindquist, M. A. & Wager, T. D. (2014) "Principles of functional Magnetic Resonance Imaging," Handbook of Neuroimaging Data Analysis. London: Chapman & Hall, CRC Press.
(Find links to Prof. Wager's suggested readings here):
https://sites.dartmouth.edu/canlab/training-courses/