skip to main content


Title: Pavlovian occasion setting in human fear and appetitive conditioning: Effects of trait anxiety and trait depression
Contexts and discrete stimuli often hierarchically influence the association between a stimulus and outcome. This phenomenon, called occasion setting, is central to modulation-based Pavlovian learning. We conducted two experiments with humans in fear and appetitive conditioning paradigms, training stimuli in differential conditioning, feature-positive discriminations, and feature-negative discriminations. We also investigated the effects of trait anxiety and trait depression on these forms of learning. Results from both experiments showed that participants were able to successfully learn which stimuli predicted the electric shock and monetary reward outcomes. Additionally, as hypothesized, the stimuli trained as occasion setters had little-to-no effect on simple reinforced or non-reinforced stimuli, suggesting the former were indeed occasion setters. Lastly, in fear conditioning, trait anxiety was associated with increases in fear of occasion setter/conditional stimulus compounds; in appetitive conditioning, trait depression was associated with lower expectations of monetary reward for the trained negative occasion setting compound and transfer of the negative occasion setter to the simple reinforced stimulus. These results suggest that clinically anxious individuals may have enhanced fear of occasion setting compounds, and clinically depressed individuals may expect less reward with compounds involving the negative occasion setter.  more » « less
Award ID(s):
1911441
NSF-PAR ID:
10334959
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Behaviour research and therapy
Volume:
147
ISSN:
0005-7967
Page Range / eLocation ID:
103986
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Animals must learn to ignore stimuli that are irrelevant to survival and attend to ones that enhance survival. When a stimulus regularly fails to be associated with an important consequence, subsequent excitatory learning about that stimulus can be delayed, which is a form of nonassociative conditioning called ‘latent inhibition’. Honey bees show latent inhibition toward an odor they have experienced without association with food reinforcement. Moreover, individual honey bees from the same colony differ in the degree to which they show latent inhibition, and these individual differences have a genetic basis. To investigate the mechanisms that underly individual differences in latent inhibition, we selected two honey bee lines for high and low latent inhibition, respectively. We crossed those lines and mapped a Quantitative Trait Locus for latent inhibition to a region of the genome that contains the tyramine receptor geneAmtyr1[We use Amtyr1 to denote the gene and AmTYR1 the receptor throughout the text.]. We then show that disruption ofAmtyr1signaling either pharmacologically or through RNAi qualitatively changes the expression of latent inhibition but has little or slight effects on appetitive conditioning, and these results suggest that AmTYR1 modulates inhibitory processing in the CNS. Electrophysiological recordings from the brain during pharmacological blockade are consistent with a model that AmTYR1 indirectly regulates at inhibitory synapses in the CNS. Our results therefore identify a distinctAmtyr1-based modulatory pathway for this type of nonassociative learning, and we propose a model for howAmtyr1acts as a gain control to modulate hebbian plasticity at defined synapses in the CNS. We have shown elsewhere how this modulation also underlies potentially adaptive intracolonial learning differences among individuals that benefit colony survival. Finally, our neural model suggests a mechanism for the broad pleiotropy this gene has on several different behaviors.

     
    more » « less
  2. We aimed to examine mechanistically the observed foraging differences across two honey bee, Apis mellifera , subspecies using the proboscis extension response assay. Specifically, we compared differences in appetitive reversal learning ability between honey bee subspecies: Apis mellifera caucasica (Pollman), and Apis mellifera syriaca (Skorikov) in a “common garden” apiary. It was hypothesized that specific learning differences could explain previously observed foraging behavior differences of these subspecies: A.m. caucasica switches between different flower color morphs in response to reward variability, and A.m. syriaca does not switch. We suggest that flower constancy allows reduced exposure by minimizing search and handling time, whereas plasticity is important when maximizing harvest in preparation for long winter is at a premium. In the initial or Acquisition phase of the test we examined specifically discrimination learning, where bees were trained to respond to a paired conditioned stimulus with an unconditioned stimulus and not to respond to a second conditioned stimulus that is not followed by an unconditioned stimulus. We found no significant differences among the subspecies in the Acquisition phase in appetitive learning. During the second, Reversal phase of the experiment, where flexibility in association was tested, the paired and unpaired conditioned stimuli were reversed. During the Reversal phase A.m. syriaca showed a reduced ability to learn the reverse association in the appetitive learning task. This observation is consistent with the hypothesis that A.m. syriaca foragers cannot change the foraging choice because of lack of flexibility in appetitive associations under changing contingencies. Interestingly, both subspecies continued responding to the previously rewarded conditioned stimulus in the reversal phase. We discuss potential ecological correlates and molecular underpinnings of these differences in learning across the two subspecies. In addition, in a supplemental experiment we demonstrated that these differences in appetitive reversal learning do not occur in other learning contexts. 
    more » « less
  3. The reward-hypersensitivity model posits that trait reward hypersensitivity should elicit hyper/hypo-approach motivation following exposure to recent life events that activate (goal striving and goal attainment) or deactivate (goal failure) the reward system, respectively. To test these hypotheses, we had 87 young adults with high trait reward (HRew) sensitivity or moderate trait reward (MRew) sensitivity report frequency of life events via the Life Event Interview. Brain activation was assessed during the functional MRI monetary-incentive-delay task. Greater exposure to goal-striving events was associated with higher nucleus accumbens (NAc) reward anticipation among HRew participants and lower orbitofrontal cortex (OFC) reward anticipation among MRew participants. Greater exposure to goal-failure events was associated with higher NAc and OFC reward anticipation only among HRew participants. This study demonstrated different neural reward anticipation (but not outcome) following reward-relevant events for HRew individuals compared with MRew individuals. Trait reward sensitivity and reward-relevant life events may jointly modulate reward-related brain function, which has implications for understanding psychopathology.

     
    more » « less
  4. Heightened fear and inefficient safety learning are key features of fear and anxiety disorders. Evidence-based interventions for anxiety disorders, such as cognitive behavioral therapy, primarily rely on mechanisms of fear extinction. However, up to 50% of clinically anxious individuals do not respond to current evidence-based treatment, suggesting a critical need for new interventions based on alternative neurobiological pathways. Using parallel human and rodent conditioned inhibition paradigms alongside brain imaging methodologies, we investigated neural activity patterns in the ventral hippocampus in response to stimuli predictive of threat or safety and compound cues to test inhibition via safety in the presence of threat. Distinct hippocampal responses to threat, safety, and compound cues suggest that the ventral hippocampus is involved in conditioned inhibition in both mice and humans. Moreover, unique response patterns within target-differentiated subpopulations of ventral hippocampal neurons identify a circuit by which fear may be inhibited via safety. Specifically, ventral hippocampal neurons projecting to the prelimbic cortex, but not to the infralimbic cortex or basolateral amygdala, were more active to safety and compound cues than threat cues, and activity correlated with freezing behavior in rodents. A corresponding distinction was observed in humans: hippocampal–dorsal anterior cingulate cortex functional connectivity—but not hippocampal–anterior ventromedial prefrontal cortex or hippocampal–basolateral amygdala connectivity—differentiated between threat, safety, and compound conditions. These findings highlight the potential to enhance treatment for anxiety disorders by targeting an alternative neural mechanism through safety signal learning.

     
    more » « less
  5. Abstract Sensory stimuli evoke spiking neural responses that innately or after learning drive suitable behavioral outputs. How are these spiking activities intrinsically patterned to encode for innate preferences, and could the neural response organization impose constraints on learning? We examined this issue in the locust olfactory system. Using a diverse odor panel, we found that ensemble activities both during (‘ON response’) and after stimulus presentations (‘OFF response’) could be linearly mapped onto overall appetitive preference indices. Although diverse, ON and OFF response patterns generated by innately appetitive odorants (higher palp-opening responses) were still limited to a low-dimensional subspace (a ‘neural manifold’). Similarly, innately non-appetitive odorants evoked responses that were separable yet confined to another neural manifold. Notably, only odorants that evoked neural response excursions in the appetitive manifold could be associated with gustatory reward. In sum, these results provide insights into how encoding for innate preferences can also impact associative learning. 
    more » « less