Implications of a Dynamic Causal Modeling Analysis of fmri Data. Andrea Stocco University of Washington, Seattle

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1 Implications of a Dynamic Causal Modeling Analysis of fmri Data Andrea Stocco University of Washington, Seattle

2 Production Rules and Basal Ganglia Buffer Buffer Buffer Thalamus Striatum Matching Striatum Selection Pallidum Substantia Nigra Pallidum Execution Thalamus Procedural Module

3 Production Rules Transfer Variables Respond-if-asked IF.. Request About. Status Movie Status THEN Raise Hand Imitation Stranger Game Things Seen Imitation Stranger Game Things Seen Do. Raise Hand

4 Exchanging information across buffers Question 1: Can we experimentally test it? Question 2: Are we missing something crucial from basal ganglia anatomy

5 Exchanging information across buffers Question 1: Can we experimentally test it? Question 2: Are we missing something crucial from basal ganglia anatomy

6 How Do We Measure Information Transfer? Functional connectivity

7 Increased Correlation Functional connectivity

8 Bidirectional Measures Functional connectivity

9 How do we test it? Effective connectivity

10 Dynamic Causal Modeling b 1 b 2 A 1,2 B 2,3 C 2,1 D 1,2 y 2 y 1 y 3 y 2 y 1 y 3 x 1 x 2 y = S i b i *x i x 1 x 2 dy/dt = Ay + S i x i B(i)y + S j y j D(j)y + Cx

11 Do the Basal Ganglia Modulate Connectivity? Direct Model Modulatory Model Prat, Stocco et al., submitted

12 They Do! Prat, Stocco et al., submitted

13 L Caudate L PFC Motor ACC Visual R Caudate R Prefrontal Empirical Connectivity Matrix Modulatory Model Connectivity Matrix R PFC R Caudate Visual ACC LBG Motor LCaudate

14 ACT-R s Connectivity Matrix PROCEDURAL CONFLICT-RESOLUTION PROCEDURAL PRODUCTION-FIRED PREPARE-FOR-ENCODING PROCEDURAL CLEAR-BUFFER RETRIEVAL PROCEDURAL CONFLICT-RESOLUTION PROCEDURAL PRODUCTION-FIRED NEXT-POSITION PROCEDURAL CLEAR-BUFFER GOAL GOAL SET-BUFFER-CHUNK GOAL OPERATION PROCEDURAL CONFLICT-RESOLUTION IMAGINAL MOD-BUFFER-CHUNK IMAGINAL PROCEDURAL CONFLICT-RESOLUTION PROCEDURAL PRODUCTION-FIRED RETRIEVE-OPERATION (p prepare-for-encoding =visual> =TASK ==> +imaginal> task =TASK +visual-location> PROCEDURAL CLEAR-BUFFER RETRIEVAL DECLARATIVE START-RETRIEVAL PROCEDURAL CONFLICT-RESOLUTION DECLARATIVE RETRIEVED-CHUNK OPERATION DECLARATIVE SET-BUFFER-CHUNK RETRIEVAL OPERATION PROCEDURAL CONFLICT-RESOLUTION +t

15 L Caudate Motor L PFC ACC Visual R Caudate R PFC L Caudate Motor L PFC ACC Visual R Caudate R PFC The Connectivity Matrix Model Experimental Data R PFC R Caudate Visual ACC L PFC Motor L Caudate R PFC R Caudate Visual ACC L PFC Motor L Caudate

16 Negative Values Are Important Prat, Stocco et al., submitted

17 Summary, part 1 The effect of production rules can be measured through effective connectivity Effective connectivity patterns can be used to test ACT-R models However: Negative values pose a problem Suggest inhibitory production rules

18 Exchanging information across buffers Question 1: Is it compatible with basal ganglia anatomy? Question 2: Are we missing something crucial from basal ganglia anatomy

19 Basal Ganglia physiology and ACT-R Buffer Buffer Buffer Thalamus Striatum Matching Striatum Selection Pallidum Substantia Nigra Pallidum Execution Thalamus Procedural Module

20 Basal Ganglia physiology and ACT-R Thalamus Substantia Nigra Pallidum + + D2(-) Indirect Pathway (NO GO) Striatum D1(+) Direct Pathway (GO) + To Frontal Cortex

21 Probabilistic Stimulus Selection (PSS) Choose Accuracy Avoid Accuracy まみ Correct! Feedback Choice タ 70% ま 80% と 60% み 20% の 30% れ 40% まと No Feedback Choice タ 70% ま 80% と 60% み 20% の 30% れ 40% Training Phase Test Phase Frank, Seeberger, & O Reilly, 2004, Science

22 Influence of Dopamine on Choose and Avoid Accuracies Accuracy (%) Frank, Seeberger, O Reilly, Controls Controls 50 Choose Decision Strategy Avoid

Dopamine in Parkinson Disease HO OH NH 2 Dopamine +1 0 +1 Dopamine gap 0

23 Dopamine in Parkinson Disease HO OH NH 2 Dopamine Dopamine gap Healthy control -1 Parkinson Excess Dopamine -1 Parkinson, on meds

24 Accuracy (%) Influence of Dopamine on Go & No-Go 100 Frank, Seeberger, O Reilly, Controls PD, Off 50 Choose Decision Strategy Avoid

25 Accuracy (%) Influence of Dopamine on Go & No-Go 100 Frank, Seeberger, O Reilly, Controls PD, On PD, Off 50 Choose Decision Strategy Avoid

26 Straightforward model まみ PSS Task Visual Module Left: A Right: B Object Choose A ACT-R Choose B Choose C Choose D Visual Module Left Location Choose E Respond Choose F Motor Module Index Left Press Manual Procedural Module

27 Learning rate α? Expected noise s? Alpha = 0.20, Noise = 0.10 Alpha = 0.18, Noise = 0.10 Alpha = 0.15, Noise = 0.10 Alpha = 0.13, Noise = 0.10 Alpha = 0.10, Noise = Alpha = 0.20, Noise = 0.10 Alpha = 0.20, Noise = 0.08 Alpha = 0.20, Noise = 0.06 Alpha = 0.20, Noise = 0.04 Alpha = 0.20, Noise = Choose A Avoid B 0.5 Choose A Avoid B

28 A Dual-Pathway Model まみ PSS Task まみ PSS Task Visual Module Left: A Right: B Object Standard ACT-R Choose A Choose B Visual Module Left: A Right: B Object ACT-R With Competitive Pathways Choose A Avoid A Choose B Avoid B Choose C Choose D Choose C Avoid C Choose D Avoid D Choose E Choose F Choose E Avoid E Choose F Avoid F Visual Module Left Location Visual Module Left Location Respond Respond Motor Module Index Left Press Manual Procedural Module Motor Module Index Left Press Manual Procedural Module

29 Results D1 = 1.00, D2 = 1.00 D1 = 1.00, D2 = 0.75 D1 = 1.00, D2 = 0.50 D1 = 1.00, D2 = 0.25 D1 = 1.00, D2 = D1 = 1.00, D2 = D1 = 0.75, D2 = 1.00 D1 = 0.50, D2 = 1.00 D1 = 0.25, D2 = 1.00 D1 = 0.10, D2 = Choose A Avoid B 0.5 Choose A Avoid B

30 Results (Default parameters) Comtrol PD, On PD, Off 0.5 Choose A Avoid B Stocco, submitted

31 Implications for Executive Functions Press left if you see a square or or Congruent Trials Incongruent Trials

32 Experimental Results

33 Simon Task Model Task Model Visual Buffer Circle Left Process Shape Don t Process Shape Process Position Don t Process Position Working Memory Module Circle --- Motor Module Spreading Activation Respond Long-Term Memory Module Task Rule 1 Square Left Task Rule 2 Circle Right

34 Model predictions Stocco et al., submitted

35 Fluid Intelligence: Raven s Advanced Progressive Matrices (RAPM)

36 Raven's Score Raven's Score Results: Experiment 1 (N = 95) Correlation between Avoid and Intelligence Correlation between Choose and Intelligence R = 0.34 R = Avoid Accuracy Choose Accuracy

37 Abbreviated Raven's Score Raven's Score Replication: Experiment 2 (N = 83) Correlation between Avoid and Intelligence Correlation between Choose and Intelligence R = 0.24 R = Avoid Accuracy Choose Accuracy

38 Model Strategy Start Retrieve solution Found? Select feature Find pattern Select rule Time from last rule > Criterion? Uses time from last successful rule identification to decide when no progress can be made Done? End

39 Crucial Steps Start Retrieve solution Pick Feature Found? Select feature Pick F1 Don t Pick F1 Pick F2 Don t Pick F2 Pick FN Don t Pick FN Find pattern Select rule Pick Rule Done? End Pick Rule 1 Don t Pick Rule 1 Pick Rule 2 Don t Pick Rule 2 Pick Rule N Don t Pick Rule N

40 Model Predictions 0.8 % RAPM Problems Solved D2 = 1.00 D2 = 0.75 D2 = 0.50 D2 = 0.25 D2 = 0.10

41 Mean brain activity during problems p < 0.05, FWE-corrected

42 Negative correlation with Accuracy Bilateral Basal Ganglia

43 Mean Problem Accuracy Negative correlations in the BG Striatum R = Mean Problem Related Activity

44 Dynamic Causal Modeling Imaginal Retrieval Visual Caudate

45 Accuracy Dynamic Causal Modeling Modulatory Effect of BG on Negative Connectivity Value (Visual to Prefrontal) R = 0.35, p = Parameter Value

46 Summary, part 2 The effect of production rules can be measured through effective connectivity Effective connectivity patterns can be used to test ACT-R models Anatomically, we are missing the functional distinction between two pathways It seems to play an important functional role across multiple domains.

47 Thank You! The Basal UW Chantel Prat Lauren Graham Brianna Yamasaki Jose Ceballos Patrick Rice Michael McDonald Nicole Murray

48 After the talk EXTRA SLIDES

Plausibility of BG as Production Rules D C B A Cortex, Layer 2/3 from D from C

from B from A from D from C from B from A to A to B to C to D GPi/SNr from D from

to C to D from D from C from B from A to A B C D A B C D from D from C from B from

Stewart, Berkolay, & SNc Eliasmith, 2012, Front Neurosci.

49 Plausibility of BG as Production Rules D C B A Cortex, Layer 2/3 from D from C from B from A A B C D Striatal Interneurons Cortex, Layer 4 from D Striatum from C from B from A from D from C from B from A to A to B to C to D GPi/SNr from D from C from B from A to A to B to C to D Thalamus from D from C from B from A to A to B to C to D from D from C from B from A to A B C D A B C D from D from C from B from A STN from D from C from B from A to A to B to C to D GPe SNc Interneurons Stewart, Berkolay, & SNc Eliasmith, 2012, Front Neurosci. Stocco, Lebiere, & Anderson, 2010, Psych Review. O Reilly & Frank, 2006, Neural Netw. Terrence Stewart Randy O Reilly

4 A Few Empirical Verifications Anderson, 2005: Basal ganglia activity varies with

50 % BOLD Change A Few Empirical Verifications Anderson, 2005: Basal ganglia activity varies with number of rules Left Caudate Nucleus Stocco & Anderson, 2008: Basal Scan ganglia activity varies with number of variables in a rule Stocco & Prat, 2014: Basal ganglia activity varies with bilingualism (larger set of rules!)

Anatomy of the basal ganglia. Dana Cohen Gonda Brain Research Center, room 410

Anatomy of the basal ganglia. Dana Cohen Gonda Brain Research Center, room 410 Anatomy of the basal ganglia Dana Cohen Gonda Brain Research Center, room 410 danacoh@gmail.com The basal ganglia The nuclei form a small minority of the brain s neuronal population. Little is known about