Investigating Global Brain Connectivity: Methods, Software, and Findings

1. InvestigatingGlobal Brain Connectivity:Methods, Software, and Findings Michael W. Cole, Ph.D. Postdoctoral fellow Washington University in St. Louis

2. Overview • Measures of global brain connectivity (GBC) • Functional relevance of GBC • New software for advanced fcMRI analysis

3. Overview • Measures of global brain connectivity (GBC) • Functional relevance of GBC • New software for advanced fcMRI analysis

4. Resting state fcMRI • Based on intrinsic coordinated fluctuations between functionally connected regions • Poly-synaptic anatomical connectivity, likely weighted by Hebbian association strengths • Reliable across sessions and individuals, and robust to eyes open/closed, physiological artifacts, etc.(Van Dijk, et al., 2010)

5. Focus: Global brain connectivity (GBC)(degree centrality) Buckner et al., 2009

6. Anatomy suggests high subcortical GBC Cole, Pathak, & Schneider (2010). "Identifying the brain’s most globally connected regions", NeuroImage 49(4): 3132-3148.

7. Subcortical GBC • Top 5% (yellow), top 10% (orange) • Unweighted GBC (uGBC) • Threshold: r>.25

8. Thresholding removes information Unweighted network Threshold & binarize Weighted network Rubinov & Sporns, 2009

9. Compare weighted and unweightedGBC • More information in wGBC measure? • Important modulatory connectivity • What happens when modulatory connections are kept in the GBC calculation (wGBC)?

10. Subcortical uGBC Subcortical wGBC

11. Highest GBC in neocortex? • High GBC mainly in the DMN? Resting state fMRI Degree connectivity DMN CCN Fox et al. 2005 Buckner et al. 2009

12. The Cognitive Control Network (Wager et al. 2004) Consistent across 30+ cognitive control studies (Cole & Schneider, 2007) Greater within-network rs-fcMRI connectivity than outside-network connectivity

13. Large number of tasks rapidly learnable by the CCN • Rapid instructed task learning (RITL) • Rapid learning of 64 tasks • Cole, Bagic, et al., 2010 (Journal of Neuroscience) • CCN must coordinate distributed sensory, semantic, & motor representations essential for tasks • Implementing so many different tasks likely requires high GBC • Prediction: The CCN has especially high GBC

14. The CCN is in the top 5% • Along with the DMN • Conjunction of uGBC and wGBC: Cole, Pathak, & Schneider (2010). "Identifying the brain’s most globally connected regions", NeuroImage 49(4): 3132-3148.

15. Overview • Measures of global brain connectivity (GBC) • Functional relevance of GBC • New software for advanced fcMRI analysis

16. Functional relevance • Account for individual differences in behavior? • Provide insight into clinical disorders, such as schizophrenia? • Complex mental disorder • Several symptom domains • Substantial individual differences

17. GBC is robust tointer-individual variability

18. Global dysconnectivity in schizophrenia • Extensive evidence of PFC disruption • Search for variable global dysconnectivity within PFC • A disease process might affect a hub region’s connections globally and variably (across individuals) • Consistentlocus of disruption that can account for variability in symptom expression

19. Schizophrenia:Within-PFC global dysconnectivity Publication: Cole M.W., Anticevic A., Repovs G., Barch D. (in press). "Variable global dysconnectivity and individual differences in schizophrenia". Biological Psychiatry.

20. ‘Under/over’ DLPFC dysconnectivity • SCZ patients vs. controls (P<0.05, FWE corrected) • Combination of over- and under-connectivity

21. The consistent results are just the tip of the iceberg…

22. GBC individual differences correlate with cognitive impairments

23. Individual differences in DLPFC connectivity correlate with symptoms

24. Poverty (negative) • Flat affect: medial PFC under-connectivity? • Motor rigidness, lack of spontaneous movement: motor system over-connectivity?

25. Reality Distortion (positive) • Hallucinations: SMA under-connectivity • Less self-monitoring  imagined percepts seem to originate externally (see Frith, et al.) • Delusions (and hallucinations): Sensory over-connectivity • Excessive top-down signals (see Corlett, et al.)

26. Disorganization • Alogia (lack of coherent/logical thought): Within lateral PFC under-connectivity • Positive formal thought disorder (language disorder): Over-connectivity with Wernicke’s area

27. DLPFC dysconnectivity correlates with all cardinal symptoms • Connectivity with the DLPFC region showed: • High correlation with 3 cognitive deficits • High correlation with all 3 cardinal symptom domains • Locus of variable dysconnectivity • Consistent location, with connections that vary with symptoms • Helps account for individual differences in SCZ

28. Why DLPFC? • Has among the highest GBC in the brain(Cole et al., 2010; Mohda & Singh, 2010) • Has access to CCN, motor, and sensory networks, and dynamically couples with them (Fuster et al., 1985) • Disruption of DLPFC could have downstream effects on a variety of brain regions (and vice versa)

29. Why so many individual differences correlations? • GBC may make individual differences correlations more likely • Identifies ROIs with many disrupted connection • Large effects only (must survive averaging across thousands of connections) • GBC robust to individual differences • Will identify ROIs despite massive individual variability • ROI definition not biased toward locations that do not vary across individuals (unlike meta-analysis ROIs)

30. General approach: Understanding GBC-behavior correlations • Use GBC to identify an ROI with a group difference • Identify consistently contributing voxels • Identify if also inconsistently contributing voxels (by removing consistent voxels) • Assess functional relevance via GBC-behavior correlations • Correlate seed map with behavior voxel-wise

31. Flexible hub hypothesis (CNS 2011) • Regions that utilize extensive connectivity to flexibly implement task goals (like switching station) • GBC related to cognitive flexibility? • DLPFC’s GBC predicts fluid intelligence

32. Overview • Measures of global brain connectivity (GBC) • Functional relevance of GBC • New software for advanced fcMRI analysis

33. Introducing: gConnect • Integrated, automated preprocessing and advanced fcMRI analysis toolbox • Primary developer: GregaRepovs • Will be available at http://gconnect.fcmri.net • Sign up for email notification of release

34. gConnect features • fcMRI preprocessing • Freesurfer-integrated, automated • 4DFP or NIfTI image formats • Seed- and ROI-based fcMRI • Resting or task-based fcMRI • Slow- or rapid-event related • GBC • Highly efficient (2-5 mins per subject) • Highly flexible (weighted, unweighted, variety of thresholds)

35. Automated preprocessing • Automatically fit to each subject’s anatomy (using Freesurfer) • Identifies white matter, ventricles, whole brain mask for each subject • Applies nuisance regression of: above masks, motion, whole brain signal • Within-grey matter smoothing & dilation (reduces inclusion of non-grey matter data)

36. Example: GBC with N=198 • Freesurfer on supercomputer: ~1 day • Fast quality assurance (not many errors) • Generic preprocessing with AFNI: ~1 day • Default: Avi’s preprocessing script • gConnectfcMRI preprocessing: 4 hours • gConnect GBC processing: 3.6 hours

37. GBC with N=198:Preliminary results

38. Conclusions • Measures of global brain connectivity (GBC) • Weighted GBC provides more information • Highest GBC: CCN, DMN, and some subcortical regions • Functional relevance of GBC • Identifies regions with substantial disruption by disease& individual differences in behavior • New software for advanced fcMRI analysis • User friendly, automated

39. Acknowledgments • Todd Braver • Deanna Barch • GregaRepovs • Alan Anticevic • Walter Schneider • SudhirPathak