1. Am I my connectome? Statistical issues in functional connectomics Brian Caffo, PhD Department of Statistics at National Cheng-Kung University, Taiwan 2015 SMART group, Department of Biostatistics Bloomberg School of Public Health, Johns Hopkins University

2. Acknowledgements

3. 12:15 tomorrow

4. Am I my connectome? Is connectomics the key to understanding brain function? Are networkopathies the key to understanding many neurological disorders?

6. Struct./func. measurement (Huettel et al. 2009)

7. 39 …………. 12 T

8. Voxels Time Data

9. Voxels Time = Mixing matrix Components Data Spatial independent Components Time Courses

10. Voxels Time = Components Spatial independent Components Time Courses Subject

11. = Yang et al. ArXiv1302.4373

12. Time Data

13. Time

14. Homunculus: http://www.movementislife.be/wp-content/uploads/2013/07/I10-13-homunculus.jpghttp://www.movementislife.be/wp-content/uploads/2013/07/I10-13-homunculus.jpg Clustering: Nebel et al. 2012

19. Investment in connectomics

20. Example studies in altered connectivity http://fcon_1000.projects.nitrc.org/indi/adhd200/results.html

21. Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds

22. Progress Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds Measure reproducibility in high dimensional settings Figure out how to make headway with so much noise Move away from group to individual measurements

23. Progress Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds Measure reproducibility in high dimensional settings Figure out how to make headway with so much noise Move away from group to individual measurements

24. I2C2 (Shou et al. 2013)

26. Graphical I2C2 (Yue et al.)

27. Progress Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds Measure reproducibility in high dimensional settings Figure out how to make headway with so much noise Move away from group to individual measurements

28. Shrinkage is a key to reproducibility

29. Progress Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds Measure reproducibility in high dimensional settings Figure out how to make headway with so much noise Move away from group to individual measurements

30. Shrinkage improvement in clustering (Mejia et al.)

31. Progress Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds Model based ICA Scalability Structure More general factor analytic models

32. Progress Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds Model based ICA Scalability Structure More general factor analytic models

33. Voxels Time = Mixing matrix Components Data Spatial independent Components Time Courses Mixture of normals Ying Guo (Biometrics 2011) Ani Eloyan (Biostatistics 2013) Histogram smoothing Shanshan Li (Submitted)

34. Progress Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds Model based ICA Scalability Structure More general factor analytic models

35. Voxels Time = Components Spatial independent Components Time Courses Subject

37. Progress Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds Model based ICA Scalability Structure More general factor analytic models

38. Voxels Time = Components Spatial independent Components Time Courses Subject

39. L = Spatial hemispheric independent Components RR RL RR L

44. Progress Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds Model based ICA Scalability Structure More general factor analytic models

45. Chen, Lindquist, Caffo, Vogelstein (in progress)

49. Graphs, some considerations Node definitions Population graphs Measures of graph reproducibility Promote conditional independence Graphs (as an outcome) regression Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds

50. Graphs, some considerations Node definitions Population graphs Measures of graph reproducibility Promote conditional independence Graphs (as an outcome) regression Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds

51. How do we define a population graph? (Han et al.)

52. Graphs, some considerations Scalability Node definitions Population graphs Measures of graph reproducibility Promote conditional independence Graphs (as an outcome) regression Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds

53. Graph regression (Qiu et al.)

54. Graphs, some considerations Node definitions Population graphs Measures of graph reproducibility Promote conditional independence Graphs (as an outcome) regression Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds

55. Node definition and regional averaging

56. Summary Better definitions Integrated imaging Testable hypotheses Longitudinal studies Statistical connectomics Reproducible measurements Intervention/causal thinking Handle on nuisances confounds

57. Thanks!