1. Luiz Pessoa Department of Psychology Maryland Neuroimaging Center University of Maryland, College Park

2.  Michael Anderson: Franklin & Marshall  Lucina Uddin: Stanford/University of Miami  Josh Kinnison: University of Maryland

3.  One-to-one mapping A1A2A3A4 F1F2F3F4 amygdala “fear”

4.  Many-to-many mapping A1A2A3A4 F1F2F3F4 amygdala “fear”“value” ventral striatum

5. Emotion Cognition Motivation Perception Action … ?

6.  Understanding brain regions via functional repertoires: multidimensional Regions Passingham et al. (2002)

7.  Understanding brain regions via functional repertoires: imaging data BrainMap NeuroSynth Task domains (ontology)

8.  Understanding brain regions via functional repertoires: imaging data

9.  Regions will be more or less “diverse”  Use Shannon Entropy Anderson, Kinnison, and Pessoa (2013), Neuroimage

12. Network fingerprint

13. Fronto-parietal “attention” network (co-activation of BrainMap data) Toro et al. (2008)

15. Cingulo-parietal “resting-state” network (co-activation of BrainMap data) Toro et al. (2008)

17. Deen et al. (2010)

18. Uddin et al. (submitted) Determine co-activation partners (using NeuroSynth)

19. Uddin et al. (submitted) Determine co-activation partners (using NeuroSynth)

20. Uddin et al. (submitted) Determine co-activation partners (using NeuroSynth)

21. Common fingerprint All insula sub-sectors are highly diverse (cf. tripartite cognitive-affective-interoceptive scheme)

22. “Specific” fingerprint components Left dorsal anterior insula mean Phonology Working memory Reasoning … Sadness Happiness Fear …

23. “Specific” fingerprint components Dorsal Posterior Ventral “Cognitive” “Affective”

24.  Fronto-parietal: “attention”  Cingulo-opercular: “resting-state”  Dorsal attention: “endogenous attention”  Ventral attention: “exogenous attention”  Fronto-parietal: “rapid adaptive control”  Cingulo-opercular: “stable set control”  List goes on and on… Toro et al. (2008)

25. Task positiveTask negative

26.  Evaluate whether two sets (i.e., networks) of fingerprints are drawn from the same parent distribution “Statistical energy” (Aslan and Zech, 2005)

27.  Statistical energy X Y

28.  Permutation testing of ϕ XY Task-positive vs. Task-negative (co-activation data) Task-positive (co-activation; Toro et al. 2008) vs. Dorsal attention (resting-state; Yeo et al. 2011)

29.  Assortativity: “like connects with like”

30.  Statistical energy  “Functional distance” Pairs of regions within a network Pairs of regions between networks X Y Z

31. Networks

32. “Dorsal attention”

33. “Ventral attention”

34. “Default network” Dis-assortative

35. “Default network”: should fragment into several subnetworks Dis-assortative

36.  Characterize contributions of individual brain regions and networks without using singular task-bound functional attributions  Described quantitative property of networks – functional assortativity – that can be useful in understanding the functional and compositional similarities and differences between networks

37. A1A2A3 NC2NC4NC3NC1 Brain areas Neural computations Behaviors A4 Network 1Network 2Network 3 Cognitive Structure-function mapping Pessoa (2008), Nature Reviews Neuroscience

38. Michael Anderson Josh Kinnison Lucina Uddin National Institute of Mental Health emotioncognition.org