Disentangling the Roles of Approach, Activation and Valence in Instrumental and Pavlovian Responding

Hard-wired, Pavlovian, responses elicited by predictions of rewards and punishments exert significant benevolent and malevolent influences over instrumentally-appropriate actions. These influences come in two main groups, defined along anatomical, pharmacological, behavioural and functional lines. Investigations of the influences have so far concentrated on the groups as a whole; here we take the critical step of looking inside each group, using a detailed reinforcement learning model to distinguish effects to do with value, specific actions, and general activation or inhibition. We show a high degree of sophistication in Pavlovian influences, with appetitive Pavlovian stimuli specifically promoting approach and inhibiting withdrawal, and aversive Pavlovian stimuli promoting withdrawal and inhibiting approach. These influences account for differences in the instrumental performance of approach and withdrawal behaviours. Finally, although losses are as informative as gains, we find that subjects neglect losses in their instrumental learning. Our findings argue for a view of the Pavlovian system as a constraint or prior, facilitating learning by alleviating computational costs that come with increased flexibility

Brain-behaviour correlates of habitual motivation in chronic back pain

Nees F, Ruttorf M, Fuchs X, Rance M, Beyer N. Brain-behaviour correlates of habitual motivation in chronic back pain. Scientific Reports. 2020;10(1): 11090

The Role of the Striatum in Learning to Orthogonalize CD Action and Valence: A Combined PET and 7 T MRI Aging Study

Pavlovian biases influence instrumental learning by coupling reward seeking with action invigoration and punishment avoidance with action suppression. Using a probabilistic go/no-go task designed to orthogonalize action (go/no-go) and valence (reward/punishment), recent studies have shown that the interaction between the two is dependent on the striatum and its key neuromodulator dopamine. Using this task, we sought to identify how structural and neuromodulatory age-related differences in the striatum may influence Pavlovian biases and instrumental learning in 25 young and 31 older adults. Computational modeling revealed a significant age-related reduction in reward and punishment sensitivity and marked (albeit not significant) reduction in learning rate and lapse rate (irreducible noise). Voxel-based morphometry analysis using 7 Tesla MRI images showed that individual differences in learning rate in older adults were related to the volume of the caudate nucleus. In contrast, dopamine synthesis capacity in the dorsal striatum, assessed using [18F]-DOPA positron emission tomography in 22 of these older adults, was not associated with learning performance and did not moderate the relationship between caudate volume and learning rate. This multiparametric approach suggests that age-related differences in striatal volume may influence learning proficiency in old age

Acute stress selectively impairs learning to act

Stress interferes with instrumental learning. However, choice is also influenced by non-instrumental factors, most strikingly by biases arising from Pavlovian associations that facilitate action in pursuit of rewards and inaction in the face of punishment. Whether stress impacts on instrumental learning via these Pavlovian associations is unknown. Here, in a task where valence (reward or punishment) and action (go or no-go) were orthogonalised, we asked whether the impact of stress on learning was action or valence specific. We exposed 60 human participants either to stress (socially-evaluated cold pressor test) or a control condition (room temperature water). We contrasted two hypotheses: that stress would lead to a non-selective increase in the expression of Pavlovian biases; or that stress, as an aversive state, might specifically impact action production due to the Pavlovian linkage between inaction and aversive states. We found support for the second of these hypotheses. Stress specifically impaired learning to produce an action, irrespective of the valence of the outcome, an effect consistent with a Pavlovian linkage between punishment and inaction. This deficit in action-learning was also reflected in pupillary responses; stressed individuals showed attenuated pupillary responses to action, hinting at a noradrenergic contribution to impaired action-learning under stress

Learning in anticipation of reward and punishment: perspectives across the human lifespan

Learning to act to receive reward and to withhold to avoid punishment has been found to be easier than learning the opposite contingencies in young adults. To what extent this type of behavioral adaptation might develop during childhood and adolescence and differ during aging remains unclear. We therefore tested 247 healthy individuals across the human life span (7-80 years) with an orthogonalized valenced go/no-go learning task. Computational modeling revealed that peak performance in young adults was attributable to greater sensitivity to both reward and punishment. However, in children and adolescents, we observed an increased bias toward action but not reward sensitivity. By contrast, reduced learning in midlife and older adults was accompanied by decreased reward sensitivity and especially punishment sensitivity along with an age-related increase in the Pavlovian bias. These findings reveal distinct motivation-dependent learning capabilities across the human life span, which cannot be probed using conventional go/reward no-go/punishment style paradigms that have important implications in lifelong education

Modeling Avoidance in Mood and Anxiety Disorders Using Reinforcement Learning.

BACKGROUND: Serious and debilitating symptoms of anxiety are the most common mental health problem worldwide, accounting for around 5% of all adult years lived with disability in the developed world. Avoidance behavior-avoiding social situations for fear of embarrassment, for instance-is a core feature of such anxiety. However, as for many other psychiatric symptoms the biological mechanisms underlying avoidance remain unclear. METHODS: Reinforcement learning models provide formal and testable characterizations of the mechanisms of decision making; here, we examine avoidance in these terms. A total of 101 healthy participants and individuals with mood and anxiety disorders completed an approach-avoidance go/no-go task under stress induced by threat of unpredictable shock. RESULTS: We show an increased reliance in the mood and anxiety group on a parameter of our reinforcement learning model that characterizes a prepotent (Pavlovian) bias to withhold responding in the face of negative outcomes. This was particularly the case when the mood and anxiety group was under stress. CONCLUSIONS: This formal description of avoidance within the reinforcement learning framework provides a new means of linking clinical symptoms with biophysically plausible models of neural circuitry and, as such, takes us closer to a mechanistic understanding of mood and anxiety disorders

Pavlovian control of escape and avoidance

Contains fulltext : 195168.pdf (publisher's version ) (Open Access)To survive in complex environments, animals need to have mechanisms to select effective actions quickly, with minimal computational costs. As perhaps the computationally most parsimonious of these systems, Pavlovian control accomplishes this by hardwiring specific stereotyped responses to certain classes of stimuli. It is well documented that appetitive cues initiate a Pavlovian bias toward vigorous approach; however, Pavlovian responses to aversive stimuli are less well understood. Gaining a deeper understanding of aversive Pavlovian responses, such as active avoidance, is important given the critical role these behaviors play in several psychiatric conditions. The goal of the current study was to establish a behavioral and computational framework to examine aversive Pavlovian responses (activation vs. inhibition) depending on the proximity of an aversive state (escape vs. avoidance). We introduce a novel task in which participants are exposed to primary aversive (noise) stimuli and characterized behavior using a novel generative computational model. This model combines reinforcement learning and drift-diffusion models so as to capture effects of invigoration/inhibition in both explicit choice behavior as well as changes in RT. Choice and RT results both suggest that escape is associated with a bias for vigorous action, whereas avoidance is associated with behavioral inhibition. These results lay a foundation for future work that promise to provide insights into typical and atypical aversive Pavlovian responses involved in psychiatric disorders, allowing us to quantify both implicit and explicit indices of vigorous choice behavior in the context of aversion.12 p