Uploaded byMicah Allen
Resting-state fMRI: Beautiful Noise?
The document discusses resting state networks (RSNs), highlighting their robustness and implications for cognitive functions like memory and emotion, as well as their ease of analysis. It outlines a methodological approach for conducting resting state fMRI studies, including pre-processing techniques and considerations for analyzing resting connectivity. Future directions emphasize the importance of understanding the default mode network's role in various psychological conditions and the need for a nuanced interpretation of data from these studies.
Resting-state fMRI: Beautiful Noise?
- 1. RESTING STATE NETWORKS Beautiful Noise?
- 2. Overview of Talk Conclusion Methodological Recipe and Caveats Background Future directions
- 5. Conclusion Resting state networksare: Highly robust across cultures, laboratories, methods Localized to gray matter and predicted by tractography Found in fMRI, EEG, MEG, and intracranial recordings Implicated in information processing, multi- tasking, memory, learning, development and emotion Easy to obtain, easy to analyze, and damn interesting Human connectomics - don’t get left behind!
- 6. A Methodological Disclaimer WARNING: shamelessanalysis of low-frequency fluctuations Source: Smith chapter in Functional MRI: An Introduction to Methods
- 8. simple recipe forrsfMRI 5-7 minutes of rest Fixation, or no-fixation. Place at beginning of scan Duplicate for maximum effect Extra ROI timeseries/foci ICA vs a priori seed-r Regression with whole brain and/or task
- 9. Life at <.1 HZ
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- 11. 99 problems butacquisition ain’t one
- 12. Pre-processing Band-pass filter: remove constantoffsets and linear trends, retain <0.08 Hz Regression of nuisance variables; motion, global signal, average lateral ventricle, deep cerebral white matter.
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- 14. Analysis: ICA vsseed-based Data-driven vs a priori
- 15. Other Analysis Task-induced de-activation Rest-Stimulusinteraction Post-scan rest Correlation of resting connectivity with cognition, personality, or psychiatric inventories.
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- 20. Why Rest? Theory andBackground
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- 22. A little history The “default mode” of brain function originally proposed by Raichle and Fox (2001) Attracted initial controversy; “why we should resist the baseline” Has since exploded, evolved into the functional and human connectome projects. “Confusion springs from a failure to distinguish between psychological, physiological and anatomical accounts.” The Rt. Hon. Lord Brain (Brain 1969) From “a brief history of the DMN” (Raichle, 2007)
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- 24. Towards a DiscoveryScience Of Human Brain Function N = 1,093 24 Centers
- 25. Resting States arePredicted by Structure Predicting human resting-state functional connectivity from structural connectivity 1. C. J. Honeya, O. Spornsa,1, L. Cammounb, X. Gigandetb, J. P. Margulies et al. (2009) Thiranb, R. Meulicand P. Hagmannb,c
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- 31. To be safe Ifyou want to look at anti-r networks: Record respiration Avoid global signal regression Include a task likely to engage CEN and SAL networks.
- 32. A Default Mode? Mariana’sTrench Argument: Don’t conflate structure with content! Rumination, introspection, social cognition Free-energy Consciousness?
- 33. Picking apart DMN Althoughexact function remains unclear, DMN connectivity at rest and during task-processing now implicated in: Schizophrenia OCD Autism ADHD Levels of consciousness Task-irrelevant thoughts
- 34. Measuring the Default TheResting State Questionnaire (RSQ) Experience Sampling (Schooler et al) Differential engagement by task Correlation with individual differences
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- 38. Real Conclusion There issimply too much multi-modal, multi-cultural evidence to dismiss slow-wave processing as a feature of mammalian brains Simple stories; DMN as ‘consciousness’, ‘pure’ anti-correlation, 1:1 mapping between structure and function = FAIL If you are spending the time and energy doing fMRI, you might as well spend 5-7 minutes at rest.
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