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Intrinsic Neural Connectiity of ACT-R ROIs

Intrinsic Neural Connectiity of ACT-R ROIs. Yulin Qin 1, 2 , Haiyan Zhou 1 , Zhijiang Wang 1 , Jain Yang 1 , Ning Zhong 1 , and John R. Anderson 2 1. International WIC Institute, Beijing University of Technology, Beijing, China

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Intrinsic Neural Connectiity of ACT-R ROIs

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  1. Intrinsic Neural Connectiity of ACT-R ROIs Yulin Qin1, 2, Haiyan Zhou1, Zhijiang Wang1, Jain Yang1, Ning Zhong1, and John R. Anderson2 1. International WIC Institute, Beijing University of Technology, Beijing, China 2. Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213

  2. Outline • Introduction • Methods • Results • Discussion

  3. Introduction • Why resting brain • A basic question • Functional connection of cognitive and metacognitive regions • Methods • Results • Discussion

  4. Why resting brain Goal of cognitive psychology: Cognitive psychology is the science of how the mind is organized to produce intelligent thought and how it is realized in the brain (John R. Anderson (2010) . Cognitive Psychology and its implications (7th edition). New York, NY: Worth Publishers)

  5. Organization example 1: Semantic Network Collins and Quillian (1969) Retrieval time from semantic memory. Journal of Verbal Learning and Verbal Behavior, 8, 240-247

  6. Organization example 2: ACT-R John R. Anderson, Michael D. Byrne, Scott Douglass, Christian Lebiere, and Yulin Qin. (2004). An integrated theory of the mind . Psychological Review. 111(4): 1036-1060

  7. Fundamental Hypothesis: Organization + Stimulus => Task evoked activation infer Stimulus + Task evoked activation ===> Organization(Task)

  8. Why resting brain? Synchronized spontaneous fluctuation in resting brain ===> Organization(Resting) infer

  9. A basic Question ● Stimulus + Task evoked activation ===> Organization(Task) Synchronized spontaneous fluctuation in resting brain ===> Organization(Resting) Is Organization(Task) consistent with Organization(Resting) ?

  10. Functional connection of cognitive and metacognitive regions Pyramid problems Regular Problems: 4$3=x (4$3=4+3+2=9 => x=9) Exception Problems x$4=x (2$4=2+1+0+(-1)=2 => x=2) Cognitive pattern: (1) Equal activity for exception and regular problems; (2) Much stronger activation when solving the problem than when reflecting on the problem’s solution after solving the problem Metacognitive pattern: (1) Stronger activity for exception than regular problems; (2) Equal activity when solving the problem and when reflecting on the problem’s solution after solving the problem Samuel Wintermute, Shawn Betts, Jennifer L. Ferris, Jon M. Fincham, John R. Anderson (submitted). Networks supporting execution of mathematical skill versus acquisition of new competence. Cognitive, Affective, and Behavior Neuroscience.

  11. (a) Metacognitive (b) Cognitive Metacognitive (d) (c) 1 Mixed Anti- Cognitive Metcognitive Correlation 0 Cognitive Anti- Metacognitive -1 Negative -1 0 1 Cognitive Correlation 1. Involving two basic brain activation patterns 2. More than 20% of brain significantly(p<0.01) correlated with one or both of them

  12. Outline • Introduction • Methods (resting brain) • Participants • Procedure • Data acquisition • Data preprocessing • Functional connectivity analysis • Results • Discussion

  13. Participants • 21 healthy students from BJUT • 10 female, 24.1±1.9 years old • Signed an informed consent • Data from all subjects were used for further data processing since their head shifted less than 1.5 mm or the head rotated less than 1.5°

  14. Procedure • Eye closed resting state scanning • 307 images • Totally 10’20’’ in one session

  15. Data Acquisition • 3.0 Tesla Siemens MRI scanner with a standard whole-head 12 channel coil • TR = 2 s • TE = 31 ms • Flip angle = 90 • FOV = 200 mm × 200 mm • Matrix =64 × 64 • Thickness = 3.2 mm • Gap = 0 mm • Axial slices = 32 (with AC-PC through the 23rd slice from the top of the brain • Voxel size = 3.125 mm × 3.125 mm × 3.2 mm

  16. Data Preprocessing • NIS (NeuroImaging Software, http://kraepelin.wpic.pitt.edu/nis/). • First 7 images deleted for magnetization equilibrium • Motion correction • Spatially normalized to a standard brain

  17. Functional Connectivity Analysis • REST (Resting-State fMRI Data Analysis Toolkit, http://www.restfmri.net/forum/index.php ) • Ideal band pass filter • Time serials in each voxel filtered into the frequency range of 0.01–0.08 Hz (period: 100s – 12.5s) • Regression analysis • Several sources of spurious variances from 6 head motion parameters, global mean signal and white matter signal removed • Seeds definition • Predefined (see below) • Voxel wised connectivity in whole brain • r map • r to Z map • Group t-test: p<0.01(uncorrected), cluster size>4

  18. Predefined 12 Seeds

  19. ACC LIPFC Motor HIPS PSPL PPC BA 10 ANG Middle Insula Anterior Insula PSPL: Posterior superior parietal lobule; ACC: Anterior cingulate cortex; HIPS: Horizontal intraparietal sulcus; PPC: Posterior parietal cortex; LIPFC: Lateral inferior prefrontal cortex; ANG: Angular gyrus Caudate Fusiform is 5 slices below to the last slice, not shown here.

  20. Outline Introduction Methods Results Metacognitive network Cognitive network Mixted network Control network Discussion

  21. 1. Metacognitive network

  22. Functional Connectivity in Resting State L Seed: BA 10 R R L

  23. Functional Connectivity in Resting State R L L Seed: ANG R

  24. Functional Connectivity in Resting State R L L Seed: Fusiform R

  25. 2. Cognitive network

  26. Functional Connectivity in Resting State 2.1 L Seed: PPC R R L

  27. Functional Connectivity in Resting State 2.2 Seed: HIPS L R R L

  28. Functional Connectivity in Resting State 2.3 R L Seed: PSPL L R

  29. Functional Connectivity in Resting State 2.4 R L Seed: Motor L R

  30. 3. Mixed network

  31. L Seed: LIPFC R Functional Connectivity in Resting State R L

  32. ANG LIPFC HIPS PPC Metacognitive Mixed Cognitive

  33. 4. Control network

  34. Functional Connectivity in Resting State R L L R Seed: ACC 1,3 2 2 3 1 – metacognitive (most, with 3) 2 – cognitive 3 - mixed

  35. Functional Connectivity in Resting State R L Seed: Caudate L R 1 2 3 1 – metacognitive (most) 2 – cognitive 3 - mixed

  36. Functional Connectivity in Resting State R L L R Seed: Insula-anterior 1,3 2 1 – metacognitive (most) 2 – cognitive 3 - mixed

  37. Functional Connectivity in Resting State R L L R Seed: Insula-middle 1,3 2 1 – metacognitive (most) 2 – cognitive 3 - mixed

  38. Outline Introduction Methods Results Discussion

  39. 1. High consistency between the brain activation patterns in task-on brain and the spontaneous fluctuation patterns in resting brain 2. Convergent evidence for four kinds of brain networks: (1) Metacognitive (2) Cognitive (3) Mixed (4) Control 3. Functional connectivity in the resting brain can help us to elaborate the picture of brain organization

  40. 3.1 Two kinds of cognitive connectivity in resting brain L R L Seed: PPC R Seed: HIPS L

  41. 3.2. Separated patterns between PPC and LIPFC in functional connectivity in resting state L Seed: LIPFC R L Seed: PPC R L In many places, they are very close, but do not overlap

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