Kevin S. LaBar and Nicole C. Huff

1. Kevin S. LaBar and Nicole C. Huff

4. Classical conditioning and generalization: Historical accounts Concept of emotion families (can talk only about one aspect of fear here today) Evolutionary perspective: helps to build neuroanatomical models Flexibility of system & unique human complexities Concept of emotion families (can talk only about one aspect of fear here today) Evolutionary perspective: helps to build neuroanatomical models Flexibility of system & unique human complexities

5. Classical conditioning and specialization: Historical accounts

6. Classical conditioning and generalization: Historical accounts We now know that this �old� view of S-R reflexive learning offered by Lashley and others is wrong; complex computations are performed on mental representations of stimuli and reinforcers in a seemingly simple conditioning experiment, including representations of CS, US, other stimuli present in the environment, context, timing, other stimuli not present (2nd-order conditioning), etc.; this view counters Pavlov�s original argument that CS1-learning actively transfers to CS2; rather Lashley & Humphrey argue that the default state is a general rule and learning is reflected by specialization (discrimination)We now know that this �old� view of S-R reflexive learning offered by Lashley and others is wrong; complex computations are performed on mental representations of stimuli and reinforcers in a seemingly simple conditioning experiment, including representations of CS, US, other stimuli present in the environment, context, timing, other stimuli not present (2nd-order conditioning), etc.; this view counters Pavlov�s original argument that CS1-learning actively transfers to CS2; rather Lashley & Humphrey argue that the default state is a general rule and learning is reflected by specialization (discrimination)

7. Defining generalization Two forms of generalization for rule-based learning 1. Instance-based: new rule is produced to predict properties found in observed instances of a known category 2. Condition-simplifying: drop a condition to make rule more general - specialization: forming a new rule by adding constraints to an existing rule

8. Applying generalization to fear conditioning 1. Instance-based: a. acquisition of novel fears to cues and environments that predict reinforcers b. presence of conditioned fear response to the same cue in varying contexts or situations (Humphrey, p. 267, 1951) c. presence of a conditioned fear response to novel cues and environments that share features with the exemplar 2. Specialization: a. learning to discriminate which cues control fear behavior b. learning to determine when and where fear should be expressed Concept of emotion families (can talk only about one aspect of fear here today) Evolutionary perspective: helps to build neuroanatomical models Flexibility of system & unique human complexities Concept of emotion families (can talk only about one aspect of fear here today) Evolutionary perspective: helps to build neuroanatomical models Flexibility of system & unique human complexities

9. Experimental paradigm: Human fear conditioning Note rapid learning (one-trial); reversal learning; conditional discriminationNote rapid learning (one-trial); reversal learning; conditional discrimination

10. Behavioral evidence for instance-based generalization of fear Note foregrounding of cue (CR is higher); Tone fear test supports Humphreys (1951) definition of generalization; Context test shows that CR generalizes to background cues present at the time of learning even when explicit CS (or US) is not present � i.e., when salient features are removed; later we�ll show that cue and context learning are partially dissociableNote foregrounding of cue (CR is higher); Tone fear test supports Humphreys (1951) definition of generalization; Context test shows that CR generalizes to background cues present at the time of learning even when explicit CS (or US) is not present � i.e., when salient features are removed; later we�ll show that cue and context learning are partially dissociable

11. Demonstrates that stimuli that share features to learned exemplar (based on perceptual similarity) will elicit similar responsesDemonstrates that stimuli that share features to learned exemplar (based on perceptual similarity) will elicit similar responses

12. Note: general response pattern is default state; this is behaviorally adaptive for survivalNote: general response pattern is default state; this is behaviorally adaptive for survival

13. Note: pattern of initial generalization to both CSs, then discrimination between CS+ and CS- late in trainingNote: pattern of initial generalization to both CSs, then discrimination between CS+ and CS- late in training

14. Theoretical perspectives on generalization and conditioning Two classes of theories Elemental: individual environmental cues or stimulus features are separately associated with reinforcers in memory (Rescorla-Wagner, 1972). Item similarity guides generalization. Configural: stimulus combinations are stored as whole unique context representations that enter into associations with reinforcers (Pearce, 1994; Rudy & O�Reilly, 1999). Pattern completion (from partial input) supports generalization and pattern separation (from competing inputs) supports specialization. There are two partially independent neural systems that support these forms of stimulus representation Tested by adding vs. subtracting an element to the context. Elemental view: subtracting is more costly than adding. Configural: shouldn�t matter; representations are unique. Data in rats (Gonzalez et al., 2003) & humans (Wheeler et al., 2006) show that subtracting produces sharper generalization gradients (less generalization) than adding. Supports elemental view. But Rudy & O�Reilly (1999) show that only pre-exposure to entire context (and not just to similar contexts that share its features) will yield contextual conditioning, and generalization to other contexts is reduced by prior exposure to a specific context.Tested by adding vs. subtracting an element to the context. Elemental view: subtracting is more costly than adding. Configural: shouldn�t matter; representations are unique. Data in rats (Gonzalez et al., 2003) & humans (Wheeler et al., 2006) show that subtracting produces sharper generalization gradients (less generalization) than adding. Supports elemental view. But Rudy & O�Reilly (1999) show that only pre-exposure to entire context (and not just to similar contexts that share its features) will yield contextual conditioning, and generalization to other contexts is reduced by prior exposure to a specific context.

17. Fear pathways: Simplified model Reciprocal connections not shown; note parallel subcortical and cortical input pathways; mention will be important for instance-based generalization; then note hippo & PFC descending input to amygdala; will be important for specialization of fear to spatial (where) and temporal (when) contexts, respectivelyReciprocal connections not shown; note parallel subcortical and cortical input pathways; mention will be important for instance-based generalization; then note hippo & PFC descending input to amygdala; will be important for specialization of fear to spatial (where) and temporal (when) contexts, respectively

18. Note +rapid cue conditioning & greater associative strength in controls; cue is foregrounded & context is backgrounded; this is an example of generalization from cue to context; amygdala needs input from hippo to generate contextual fear responseNote +rapid cue conditioning & greater associative strength in controls; cue is foregrounded & context is backgrounded; this is an example of generalization from cue to context; amygdala needs input from hippo to generate contextual fear response

19. Protein synthesis blockade following training reduces expression of cued fear in novel context not only do you need intact amygdala during learning but active processing within amygdala following learning faciltiates long-term memory of fear and generalization of cued fear to other contextsnot only do you need intact amygdala during learning but active processing within amygdala following learning faciltiates long-term memory of fear and generalization of cued fear to other contexts

20. Properties of amygdala function that facilitate induction-based generalization partial independence of CS-US associations from context representation equipotentiality of subcortical and cortical input pathways (Romanski et al., 1992) indelibility of emotional learning in absence of cortex (LeDoux et al., 1989) relatively broad & species-typical receptive field tuning (Bordi & LeDoux, 1992) partial independence: fear can generalize to cue outside context; subcortical input ? eliciting stimuli can be partial or similar, not exact; plasticity & indelibility enable rapid induction-based generalization and perseveration; convergence & connectivity allow multiple cues to become associated ? cross-modal generalization; broad tuning necessary in order for similar cues to elicit response; also mention rapid synaptic plasticity mechanisms, multimodal convergence & broad connectivitypartial independence: fear can generalize to cue outside context; subcortical input ? eliciting stimuli can be partial or similar, not exact; plasticity & indelibility enable rapid induction-based generalization and perseveration; convergence & connectivity allow multiple cues to become associated ? cross-modal generalization; broad tuning necessary in order for similar cues to elicit response; also mention rapid synaptic plasticity mechanisms, multimodal convergence & broad connectivity

22. Double dissociation of explicit knowledge and conditioned fear in humans

24. Specialization: Learning when not to fearFear extinction depends on vmPFC � amygdala interactions Note: consolidation is key but not indicated here� normally, we acquire fears in 1-2 trials (unlike last slide); without discrimination or over-training, we must prevent overgeneralized response; adds flexibility; fears are appropriate at some temporal contexts but not others; mention reversal training�form of retroactive interference; new learning is requiredNote: consolidation is key but not indicated here� normally, we acquire fears in 1-2 trials (unlike last slide); without discrimination or over-training, we must prevent overgeneralized response; adds flexibility; fears are appropriate at some temporal contexts but not others; mention reversal training�form of retroactive interference; new learning is required

25. vmPFC damage in rats yields fear perseveration requires PFC (developmental story � little albert)requires PFC (developmental story � little albert)

27. Extinction shows temporal control over expression of fear � when is it appropriate to express fear; but we also learn where it is appropriate to express fear -- contextual control over fear (zoo vs. woods); extinction training is context-specific (Bouton) and does not generalize like initial fear acquisition; changes in the context can renew fear and changes in the emotional meaning of the context can reinstate the expression of extinguished fears; problem with treatment of phobias; context disambiguates meaning of CS (dual representation with retroactive interference) and biases retrieval of prior fear representationExtinction shows temporal control over expression of fear � when is it appropriate to express fear; but we also learn where it is appropriate to express fear -- contextual control over fear (zoo vs. woods); extinction training is context-specific (Bouton) and does not generalize like initial fear acquisition; changes in the context can renew fear and changes in the emotional meaning of the context can reinstate the expression of extinguished fears; problem with treatment of phobias; context disambiguates meaning of CS (dual representation with retroactive interference) and biases retrieval of prior fear representation

29. Note that amygdala, in turn, drives specialization in other brain regions, including sensory neocortex; alternate model of Quirk: mPFC ? ITCNote that amygdala, in turn, drives specialization in other brain regions, including sensory neocortex; alternate model of Quirk: mPFC ? ITC

30. 4 issues: experimental model of contextual fear recovery in phobia; gain experimental control over environment; make context more realistic and dynamic; adapt to fMRI to use functional connectivity modeling to test alternate models of amygdala, hippocampus, and mPFC interactions; NSF funding4 issues: experimental model of contextual fear recovery in phobia; gain experimental control over environment; make context more realistic and dynamic; adapt to fMRI to use functional connectivity modeling to test alternate models of amygdala, hippocampus, and mPFC interactions; NSF funding

32. note: there are neurohormonal models as well that complement and extend this model (stress hormones, etc.); also Fredrikson social phobia resultnote: there are neurohormonal models as well that complement and extend this model (stress hormones, etc.); also Fredrikson social phobia result

33. note: there are neurohormonal models as well that complement and extend this model (stress hormones, etc.); also Fredrikson social phobia resultnote: there are neurohormonal models as well that complement and extend this model (stress hormones, etc.); also Fredrikson social phobia result

35. Summary: Fear conditioning and generalization Initial learning mediated by amygdala-dependent implicit memory system whose properties support generalization to novel contexts and to stimuli that share features Specialization of learning with continued training alters tuning of perceptual cortical representations and recruits prefrontal and hippocampal processing for temporal and contextual control over fear expression Overgeneralization related to hyperactive amygdala responses during learning and lack of cortical control contribute to emotional memory persistence and inappropriate expression in anxiety disorders

36. Generalization and Conditioned Fear: Epilogue

37. Acknowledgements

38. Opposite contextual control of behavior to same CS; shows generalization gradients according to orientation similarity of CS that are context-dependentOpposite contextual control of behavior to same CS; shows generalization gradients according to orientation similarity of CS that are context-dependent

39. note: within trial rapid learning implicates direct thalamo-amygdala pathway; learning in amygdala may subsequently entrain cortex via backprojectionsnote: within trial rapid learning implicates direct thalamo-amygdala pathway; learning in amygdala may subsequently entrain cortex via backprojections

40. Temporary inactivation of rabbit amygdala affects plasticity in other regions

41. Amygdala connectivity in the primate forebrain

42. Specialization: Receptive field tuning in sensory cortex Cortical pathway necessary for discrimination learning (Teich et al., 1989) Gradual training-induced, amygdala-dependent shift in receptive field properties of auditory cortex neurons & role of cholinergic systems note: I don�t have a graph of discrimination training, but same thing happens with overtraining. Mention recent Armony caveat to cortex story? Interesting point: amygdala is necessary for this but doesn�t just call upon neurons that represent the given tone frequency; other neurons alter their firing properties (transiently) in combination with cholinergic input (attention/cortical arousal is required!). A) and B) above are from different experiments! A is tone-shock (?) pairing with 2.5 kHz stimulus; (B) is tone paired with NBM stimulation note: I don�t have a graph of discrimination training, but same thing happens with overtraining. Mention recent Armony caveat to cortex story? Interesting point: amygdala is necessary for this but doesn�t just call upon neurons that represent the given tone frequency; other neurons alter their firing properties (transiently) in combination with cholinergic input (attention/cortical arousal is required!). A) and B) above are from different experiments! A is tone-shock (?) pairing with 2.5 kHz stimulus; (B) is tone paired with NBM stimulation