Ian Stewart Dermot Barnes-Holmes

1. RELATIONAL FRAME THEORY The Current State of the Evidence Ian Stewart Dermot Barnes-Holmes

2. RELATIONAL FRAMING Core Properties NYOKA ORM 1 - MUTUAL ENTAILMENT 2 - COMBINATORIAL ENTAILMENT 3 - TRANSFORMATION OF FUNCTION

3. C rel C func Contextual Control is ORM NYOKA SAME SAME What is the look of an orm? What is the sound of an orm? SOUND LOOK Hiss Rattle Fangs Scaly

4. Sr+ Sr+ cat & cat Sr+ Sr+ banana & banana Sr+ apple & apple Sr+ Sr+ Sr+ fish & fish Multiple Exemplar Training Explicitly trained CRel (e.g. “is”) CRel (e.g. “is”) Sr+ tree tree Sr+ PREDICTS

5. Sr+ Sr+ Sr+ Sr+ Sr+ Multiple Stimulus Relations Crel (e.g. “smaller than”) Crel (e.g. “bigger than”) Cfunc (e.g., preference) We learn to choose the bigger when given a choice of appetitive items

6. Sr+ Hg Au Pt Sr+ Pt Hg Sr+ Sr+ Hg Pt Arbitrary Applicability Crel (e.g. “smaller than”) predicts Crel (e.g. “bigger than”) Cfunc (e.g. “worth”)

7. A B; B C A B; B C A B; B C C A C A C A C (f) A (f) C (f) A (f) C (f) A (f) An Operant Account Explicitly Reinforced Relational Response Multiple Exemplars Explicitly Reinforced Relational Response Unreinforced Derived Relational Response

8. An Overview of RF Research Evidence that derived relations and language are closely linked Comparative Developmental Comparison with Alternative Paradigms Neuropsychological Language-Like Effects Evidence that RF is an operant as claimed by Relational Frame Theory RF models of higher cognition Future directions

9. Evidence that DRR and language are closely linked Comparative Developmental Comparison with Alternative Paradigms Neuropsychological Language Like Effects

10. Evidence that DRR and language are closely linked Comparative Humans show derived relations from an early age whereas non verbal organisms have not yet shown conclusive evidence even of simple symmetry / mutual entailment

11. Evidence that DRR and language are closely linked Developmental NAME OBJECT OBJECT NAME

12. Evidence that DRR and language are closely linked 23 MTHS Train OBJECT NAME Test NAME OBJECT 17 MTHS 100 Expose Novel Name-Picture Test Novel Picture-Name 100 90% (4 pairs) 100 50 % CORRECT 87.5% (4 pairs) 80 50 % CORRECT 60 Percent Correct 0 40 Object Name 0 20 Sound 0 16 24 26 27 Age in Months Developmental Symmetry / mutual entailment appeared at 17 months of age Transitivity / combinatorial entailment appeared at 23 months of age Relational forms developed over time Lipkens, Hayes & Hayes (1993)

13. Evidence that DRR and language are closely linked Developmental • …and with the development of specific verbal skills • DRR correlates with cognitive / verbal ability Normal Normal Hearing Impaired: Language =>2 yrs LD: Receptive Chance Chance LD: No receptive Hearing Impaired: Expressive Naming No Receptive Naming Devany, Hayes, & Nelson (1986) Barnes, McCullagh, & Keenan (1990)

14. Evidence that DRR and language are closely linked 100 80 60 80 Percent Correct 40 70 60 20 Errors 50 40 0 Low High 30 20 Verbal Scores 10 0 Adult Teen Late Mid Early Childhood Priming Among Equivalent and Non-Equivalent Stimuli Reaction Time 900 800 700 Mean Milliseconds 600 500 Directly Eq. Member - Eq. Member - Nonsense - Nonsense - Symmetry Transitivity Equivalence Trained Nonmember Nonsense Eq. Member Nonsense Comparison with alternative paradigms Derived relations correlate with WAIS verbal ability Deictic RF correlate with Theory of Mind data McHugh, Barnes-Holmes, & Barnes-Holmes (2004) Pelez-Nouregas, O’Hora, & Barnes-Holmes (2005) Derived relations produce priming effects Barnes-Holmes et al. (2005)

15. Evidence that DRR and language are closely linked NORMAL IAT IAT USING NONSENSE WORDS 2000 1200 1000 1500 800 Reaction Time (ms) 1000 600 Reaction Time (ms) 400 500 200 0 0 PASS Group FAIL Group PASS Group FAIL Group Consistent Consistent Inconsistent Inconsistent Comparison with alternative paradigms The IAT effect is only produced by participants who have formed the appropriate derived relations Implicit Association Test – Ss. have to categorize congruent and incongruent stimuli as quickly as possible revealing implicit attitudinal biases S S S ns O’Toole, Barnes-Holmes et al. (2005) Only when the nonsense words were in derived relations was the IAT effect shown

16. Evidence that DRR and language are closely linked Neuropsychological Right Hemisphere Directly Trained and Equivalent Stimuli Left Hemisphere Non-Equivalent Stimuli Directly Trained Equivalent Stimuli Non-Equivalent Stimuli Derived relations produce differential ERPs measures Barnes-Holmes et al. (2005)

17. Evidence that DRR and language are closely linked Neuropsychological Deictic relational frames produce ERPs patterns similar to those found in ToM research Derived relations also produce fMRI activation patterns that resemble those involved in semantic processing Other Self McHugh, Barnes-Holmes & Barnes-Holmes (2004) Dickins, Singh, Roberts, Burns, Downes, Jimmieson, & Bentall (2001)

18. Evidence that DRR and language are closely linked Dymond and Barnes (1995) Train 1 Response Function Test 0 Response Function B1 Less B2 Same Less Same A1 More Same More C1 C2 Test 1 Response Function Test 2 Response Function Language-Like Effects Meaning / Verbal Control = Transformation of Function OPERANT TOF

19. Evidence that DRR and language are closely linked Language-Like Effects Meaning / Verbal Control ------ Transformation of Function RESPONDENT TOF TEST GSR: • Established relational network as follows using arbitrary stimuli • A < B < C Given CS shock function Given 0.5 strength shock function Dougher, Hamilton, Fink & Harrington (under submission)

20. Evidence that DRR and language are closely linked Language-Like Effects Generativity ------ Contextual Control Green Background / Hi Tone Color – contextual control over equivalence relations Tone – contextual control over order A1 – B1 – C1 – D1 A2 – B2 – C2 – D2 Sort 1st Sort 2nd / Hi Tone Red Background 120 untrained sequences emerged from 8 trained performances A1 – B1 – C2 – D2 A2 – B2 – C1 – D1 Sort 1st Sort 2nd Green Background / Lo Tone A2 – B2 – C2 – D2 A1 – B1 – C1 – D1 Sort 1st Sort 2nd Red Background / Lo Tone A2 – B2 – C1 – D1 A1 – B1 – C2 – D2 Sort 1st Sort 2nd Wulfert & Hayes (1988)

21. Evidence that DRR and language are closely linked Language-Like Effects RELATIONAL EVALUATION PROCEDURE Generativity ------ Contextual Control Stewart, Barnes-Holmes & Roche (2004)

22. RF models of cognition Analogy / Metaphor Rule Governed Behaviour Motivation Perspective Taking Implicit Cognition

23. RF models of cognition Analogy / Metaphor Relating derived relations to derived relations provides a model of analogical reasoning For example APPLE DOG Similar-Similar Similar Similar PEACH SHEEP A decade of research has followed the basic model of analogy as ‘equivalence-equivalence’ responding. This program has demonstrated various aspects of analogy / metaphor including (1) Insight (ii) Generativity (iii) Age-related development.

24. RF models of cognition Analogy / Metaphor A1 B1 C1 A2 C2 B2 C3 A3 B3 C4 A4 B4 B1/C1 Equivalence Equivalence B2/C2 B3/C4 (i) Modeling ‘insight’ via analogy Stewart, Barnes-Holmes, Roche & Smeets (2002)

25. RF models of cognition Analogy / Metaphor (ii) Modeling analogical generativity Stewart, Barnes-Holmes, Roche & Smeets (2002)

26. RF models of cognition Analogy / Metaphor Experiment 1 Expts. 2 & 3 B1C2 B1C3 B1C1 100 C1 C2 C3 80 60 No. Participants (%) 40 20 B1 0 Equiv Equiv-Equiv Equiv Equiv-Equiv Equiv Equiv-Equiv Expt. 4 Adults 9-yr Olds 5-yr Olds A1B1 A3B1 Carpentier, Smeets, & Barnes-Holmes (2002) A3B3 A3B2 A3B3 A3B2 100 100 80 80 60 60 No. Participants (%) No. Participants (%) 40 40 20 20 0 0 Equiv Equiv-Equiv Equiv-Equiv Equiv-Equiv Equiv-Equiv Equiv-Equiv 5-yr Olds Before Equiv After Equiv Before Equiv After Equiv Adults 5-Year Olds (iii) Tracking development NOTE: TEST AFTER EQUIVALENCE Carpentier, Smeets, & Barnes-Holmes (2003)

27. RF models of cognition Rule Governed Behaviour Networks of before-after derived relations provide a model of rule-governance or instructional control --- O’Hora & Barnes-Holmes (2003) Before / After Same / Different

28. RF models of cognition Rule Governed Behaviour The functions of the buttons are transformed in accordance with the particular rule such that the participant presses in a particular sequence

29. RF models of cognition Verbal Motivation (Formative Augmenting) CS- B1 B2 Conditioned Aversive Consequential Function OPPOSITE SAME SAME OPPOSITE A1 SAME Whelan & Barnes-Holmes (2004) OPPOSITE Whelan & Barnes-Holmes Motivative Aug. C1 C2 CS+ Valdivia, Dougher & Luciano Clinical Model CS- TEST THESE FOR DERIVED CONSEQUENTIAL FUNCTIONS

30. RF models of cognition Perspective Taking 80 70 60 50 Errors 40 30 20 10 0 Mid C/hood Early C/hood Adults Adoles. Late C/hood Age Range • RFT conceptualizes perspective-taking in terms of the deictic RFs of I-You, Here-There & Now-Then • In a cross-sectional study probing the development of deictic RF across a number of age groups, Hughes et al. (2004) showed a correlation between development of deictic RF and ability to perform on Theory of Mind tasks McHugh, Barnes-Holmes, & Barnes-Holmes (2004) • Relation Type • I / YOU • HERE / THERE • NOW / THEN • Complexity • Single Relations • Reversed Relations • Double Reversed Relations

31. TRAINING PERSPECTIVE 4 yrs. 1 mth. / 63 sessions of training over 10 weeks

32. RF models of cognition Implicit Cognition Precursor to the Relational Evaluation Procedure (pREP) Relational Evaluation Procedure (REP) Implicit Relational Assessment Procedure (IRAP) Relational Completion Procedure (RCP)

33. RF models of cognition Implicit Cognition Consistent Tasks Autistic Bad Normal Bad Similar Opposite Similar Opposite D K D K Inconsistent Tasks Autistic Good Normal Good Opposite Similar Opposite Similar D K D K Implicit Relational Assessment Procedure

34. RF models of cognition Implicit Cognition Implicit Relational Assessment Procedure RESULTS All three groups showed a tendency to relate autism to negative terms more quickly than to positive terms. This lack of difference on the implicit test contrasts with the pattern seen on the explicit.

35. RF models of cognition Implicit Cognition Attitudes to Autism Scale (AAS) CHABA: Perceived Efficacy 30 35 30 25 25 20 20 15 Mean Scores 15 10 10 5 5 0 0 Years None Months Years None Months CHABA: Depression/Anger CHABA: Fear/Anxiety 12 6 10 5 8 4 6 3 4 2 2 1 0 0 Years None Months Years None Months Explicit Measures

36. Some Future Directions of RFT research The Development of Multiple Stimulus Relations Pragmatic Verbal Analysis Hierarchy & Categorization

37. Contextually controlled mutual entailment (ME) in equivalence (EQ) Contextually controlled combinatorial entailment (CE) in EQ Contextually controlled transfer of stimulus function through EQ relations Integration of above into a functional response class – the frame of co-ordination Simple examples of verbal understanding Contextually controlled ME in additional types of stimulus relations Contextually controlled CE in additional types of stimulus relations Contextually controlled transfer of stimulus functions in additional types of stimulus relations Integration of these into additional relational frames Simple examples of genuinely verbal governance of behavior by others Conditional contextual control (CC) over participation of given elements in relational frames Development of relational networks (RNs) More complex examples of verbal understanding Verbal governance of the behavior of others (e.g., verbal mands and tacts) Transformation of stimulus functions across relational networks Increasing number and complexity of relational frames Increasing acquisition specific participants in specific relational frames (e.g., vocabulary) Complex interactions between relations (training in one influences development of another) Integration of related types of relational frames into families of relational responses Elaborated and increasingly subtle contextual control over relational responding (e.g., syntax; number of relational terms) Elaborated and increasingly subtle contextual control over transformation of stimulus functions (e.g., number and specificity of functional terms) Non-arbitrary properties serve as a relational context for AARR Increasingly complex relational networks With acquisition of equivalence, time or causality, and evaluation, the development of relational sentences that function fully as rules Relating RNs Transformation of stimulus functions based on the relating of relational networks Relating relational networks under the control of non-arbitrary properties of the environment More complex examples of rule understanding and rule governance, particularly pliance and tracking Regulation of the behavior of the listener through the establishment of RNs in the listener’s repertoire With acquisition of hierarchical class membership, use of RNs to abstract non-arbitrary properties and have these participate in relational frames Abstracting properties of the non-arbitrary environment based on RNs and the relating of RNs With the acquisition of temporal, contingency and causal relational frames, increased insensitivity to temporal delays Development of deictic relational frames Development of perspective taking and sense of self Construction of the verbal other Construction of the conceptualized group Contextual control of relational responding by the non-arbitrary and arbitrary properties of the listener Further development of rule following particularly augmenting Regulation of the behavior of the listener by orienting the listener to abstracted features of the environment Acquisition of increasingly abstract verbal consequences Self-rule generation and self-rule following Pragmatic verbal analysis and increasingly complex forms of problem solving and reasoning Increased dominance of the verbal functions of the environment SUGGESTED SEQUENCE OF RELATIONAL FRAME LEARNING Hayes, Barnes-Holmes & Roche (2001) Suggested Development of Relational Responding

38. Future Directions Development of MSR What is the typical sequence of the development of relational frames? How do relational frames relate to each other? Presumably certain frames are important or necessary precursors to the development of other frames? S / D, M / L  HIERARCHY COMPARISON  CONTAINMENT OPPOSITION  PERSPECTIVE TAKING SPATIAL RELATIONS  TEMPORAL RELATIONS More work needed on the development of Transformation of Function and contextual control over Transformation of Function More work needed with respect to training relational frames in language delayed children

39. Future Directions Pragmatic Verbal Analysis PVA is ‘framing events relationally under the control of abstracted features of the non-arbitrary environment that are themselves framed relationally’ Phenomena involving PVA Abstraction, Thinking, Planning, Strategic and Valuative Problem Solving Despite it’s importance, as yet, we have nothing in the RFT literature that might be referred to as a model of PVA

40. Future Directions Pragmatic Verbal Analysis Dot size (e.g., large) Dot number (e.g., 1) No. of shapes (e.g., 3) Prototype model of PVA involving contextually controlled SAME / DIFFERENCE and MORE THAN / LESS THAN relations

41. Future Directions Hierarchical Relations Hierarchical relations are closely related to PVA in that the former are probably often implicated in the latter Little RFT research into hierarchical relations Hierarchical relations appear relatively complex -- Hierarchical relational responding may be asymmetrical as regards transfer of function (‘A is a type of B’ implies transfer from B to A but not usually from A to B) -- Hierarchy appears to require contextually flexible responding in accordance with SAME / DIFFERENT relations as well as appropriate comparison relational responding -- Formally there are different examples of hierarchy - analytic (‘part of’), classification (‘member of’), organizational (‘subordinate to’), familial (‘son / daughter of’) but whether such differences imply different functional delineations is an empirical issue

42. RELATIONAL FRAME THEORY The Current State of the Evidence Ian Stewart Dermot Barnes-Holmes