On May 15, Lauren Atlas provided a critical introduction and overview of pain neuroimaging. After her talk, there was a question-and-answer period moderated by Petra Schweinhardt.
- Lauren Atlas, PhD, National Institutes of Health (NIH), Bethesda, US
- Petra Schweinhardt, MD, PhD, Balgrist University Hospital and University of Zurich, Switzerland
Listen to the Webinar
Here is an abstract of Atlas’ talk:
Solving pain requires coordinated investigations that cross disciplinary boundaries. This presents a challenge for researchers and clinicians who must critically evaluate and digest research outside of their areas of expertise, and for new trainees selecting an approach or level of analysis to pursue in their research career. My goal in this webinar is to provide a critical introduction and overview of pain neuroimaging, modeled after our recent primer on this topic (Moayedi et al., 2018). I will focus on functional magnetic resonance imaging (fMRI) of pain, including study design, analysis, and interpretation. This talk will be geared toward new trainees, clinicians, and non-imagers. By reviewing the key elements of fMRI studies as well as strengths and limitations of fMRI, I hope to provide a foundation from which non-imagers can confidently and critically assess and evaluate human pain neuroimaging and contribute to this important research area.
Resources/References
Pain Neuroimaging in Humans: A Primer for Beginners and Non-Imagers.
Moayedi, Salomons, Atlas.
The Journal of Pain, Volume 19, Issue 9, September 2018, Pages 961.e1-961.e21.
- The webinar is a pared-down version of our complete primer.
Best Practices in Data Analysis and Sharing in Neuroimaging using MRI.
Nichols TE, Das S, Eickhoff SB, Evans AC, Glatard T, Hanke M, Kriegeskorte N, Milham MP, Poldrack RA, Poline J.-B, Proal E, Thirion B, Van Essen DC, White T, Yeo BTT
Nature Neuroscience, Volume 20, Issue 3, March 2017. Pages 299-303.
- This is a report from the Organization for Human Brain Mapping (OHBM) Committee on Best Practice in Data Analysis and Sharing (COBIDAS) outlining community standards for appropriate and reproducible fMRI studies. The complete version of the paper (via the link) includes “Appendix D. Itemized lists of best practices and reporting items” which includes an extensive checklist for what should be addressed in any fMRI study: experimental design reporting, Acquisition Reporting, Preprocessing Reporting, Statistical Modeling and Inference, Results Reporting, Data Sharing, and Reproducibility.
OHBM OnDemand: The OHBM’s on-demand library which has an archive or presentations going back to 2013.
- Highly recommend checking out the pre-conference workshops, including topics like Advanced FMRI analysis, Pattern Recognition for Neuroimaging, Brain Graphs, Neuroimaging Meta-analysis.
- Jeanette Mumford, an fMRI statistician, has created a youtube channel with tons of short video tutorials and lessons about neuroimaging data analysis. Videos range from basics to advanced topics and new trends. There are general overview videos as well as some that link to R code or show how to use FSL for analysis. There is also a very active Facebook group related to this series.
- Peter Bandettini at NIMH has led a summer fMRI course every summer since 2014. There are three talks per week, with topics ranging from fMRI acquisition and MR physics to pharmacology to real time fMRI. All talks are archived here. You can also sign up to be notified for the upcoming course.
- My 2018 talk on fMRI of pain complements today’s webinar, as there I give an overview of the history of brain imaging of pain, rather than the technical decisions.
- Unfortunately the website is currently down, but check back later.
- Martin Hebart created a matlab-based MVPA toolbox, “The Decoding Toolbox." A workshop he ran at NIH is archived here.
- Unfortunately the website is currently down, but check back later.
Principles of fMRI 1 and Principles of fMRI 2
- This is a two-part online course taught by Martin Lindquist and Tor Wager that covers fMRI design and statistics.
- There is an accompanying textbook here.
FMRIPrep and Brain Imaging Data Structure
- BIDS is a streamlined structure for fMRI data storage and organization.
- BIDS integrates with OpenNeuro, a platform for sharing fMRI data (see also other pain-specific repositories listed in our primer).
- BIDS data can be processed with FMRIPrep, a standardized preprocessing pipeline that uses steps from multiple software programs and helps reduce researcher degrees of freedom.
John Dylan Haynes' MVPA primer in Neuron
- Automated term-based meta-analyses of brain imaging data, which are useful for generating a priori ROIs.
Want some background reading? See the recent papers under Related Content in the right column of this page. And join the conversation about the webinar on Twitter @PainResForum #PRFWebinar.
See previous PRF webinars here.
Want some background reading? See the recent papers under Related Content in the right column of this page. And join the conversation about the webinar on Twitter @PainResForum #PRFWebinar.
See previous PRF webinars here.