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.

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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 2. Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213

Outline Introduction Methods Results Discussion

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

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 (7 th edition). New York, NY: Worth Publishers)

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

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

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

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

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

Functional connection of cognitive and metacognitive regions Pyramid problems Regular Problems: 4$3=x (4$3=4+3+2=9 => x=9) Exception Problemsx$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.

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

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

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°

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

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 = mm × mm × 3.2 mm

Data Preprocessing NIS (NeuroImaging Software, First 7 images deleted for magnetization equilibrium Motion correction Spatially normalized to a standard brain

Functional Connectivity Analysis REST (Resting-State fMRI Data Analysis Toolkit, ) 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 4

Predefined 12 Seeds

Motor PSPL ACC HIPS PPC ANG BA 10 Anterior Insula Caudate Middle 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 LIPFC Fusiform is 5 slices below to the last slice, not shown here.

Outline Introduction Methods Results – Metacognitive network – Cognitive network – Mixted network – Control network Discussion

1. Metacognitive network

Seed: BA 10 RL LR Functional Connectivity in Resting State

Seed: ANGRLLR Functional Connectivity in Resting State

Seed: FusiformLR RL

2. Cognitive network

R L RL Functional Connectivity in Resting State Seed: PPC 2.1

Functional Connectivity in Resting State Seed: HIPS RL LR 2.2

RL Functional Connectivity in Resting State Seed: PSPL LR 2.3

RL Functional Connectivity in Resting State Seed: Motor LR 2.4

3. Mixed network

Functional Connectivity in Resting State Seed: LIPFCRLLR

PPCHIPSANGLIPFC CognitiveMixedMetacognitive

4. Control network

RL Functional Connectivity in Resting State Seed: ACC LR 1,3 2 1 – metacognitive (most, with 3) 2 – cognitive 3 - mixed 2 3

RL Functional Connectivity in Resting State Seed: Caudate LR – metacognitive (most) 2 – cognitive 3 - mixed 3

RL Functional Connectivity in Resting State Seed: Insula-anterior LR 1,3 2 1 – metacognitive (most) 2 – cognitive 3 - mixed

RL 1 – metacognitive (most) 2 – cognitive 3 - mixed Functional Connectivity in Resting State Seed: Insula-middle LR 1,3 2

Outline Introduction Methods Results Discussion

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

3.1 Two kinds of cognitive connectivity in resting brain Seed: HIPS RLSeed: PPC L LR

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