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Human Pavlovian fear conditioning conforms to probabilistic learning.

ABSTRACT: Learning to predict threat from environmental cues is a fundamental skill in changing environments. This aversive learning process is exemplified by Pavlovian threat conditioning. Despite a plethora of studies on the neural mechanisms supporting the formation of associations between neutral and aversive events, our computational understanding of this process is fragmented. Importantly, different computational models give rise to different and partly opposing predictions for the trial-by-trial dynamics of learning, for example expressed in the activity of the autonomic nervous system (ANS). Here, we investigate human ANS responses to conditioned stimuli during Pavlovian fear conditioning. To obtain precise, trial-by-trial, single-subject estimates of ANS responses, we build on a statistical framework for psychophysiological modelling. We then consider previously proposed non-probabilistic models, a simple probabilistic model, and non-learning models, as well as different observation functions to link learning models with ANS activity. Across three experiments, and both for skin conductance (SCR) and pupil size responses (PSR), a probabilistic learning model best explains ANS responses. Notably, SCR and PSR reflect different quantities of the same model: SCR track a mixture of expected outcome and uncertainty, while PSR track expected outcome alone. In summary, by combining psychophysiological modelling with computational learning theory, we provide systematic evidence that the formation and maintenance of Pavlovian threat predictions in humans may rely on probabilistic inference and includes estimation of uncertainty. This could inform theories of neural implementation of aversive learning.

SUBMITTER: Tzovara A

PROVIDER: S-EPMC6118355 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Human Pavlovian fear conditioning conforms to probabilistic learning.

Tzovara Athina A Korn Christoph W CW Bach Dominik R DR

PLoS computational biology 20180831 8

Learning to predict threat from environmental cues is a fundamental skill in changing environments. This aversive learning process is exemplified by Pavlovian threat conditioning. Despite a plethora of studies on the neural mechanisms supporting the formation of associations between neutral and aversive events, our computational understanding of this process is fragmented. Importantly, different computational models give rise to different and partly opposing predictions for the trial-by-trial dy ...[more]

PMID: 30169519

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Project description:BackgroundAssociative conditioning is a ubiquitous form of learning throughout the animal kingdom and fear conditioning is one of the most widely researched models for studying its neurobiological basis. Fear conditioning is also considered a model system for understanding phobias and anxiety disorders. A fundamental issue in fear conditioning regards the existence and location of neurons in the brain that receive convergent information about the conditioned stimulus (CS) and unconditioned stimulus (US) during the acquisition of conditioned fear memory. Convergent activation of neurons is generally viewed as a key event for fear learning, yet there has been almost no direct evidence of this critical event in the mammalian brain.Methodology/principal findingsHere, we used Arc cellular compartmental analysis of temporal gene transcription by fluorescence in situ hybridization (catFISH) to identify neurons activated during single trial contextual fear conditioning in rats. To conform to temporal requirements of catFISH analysis we used a novel delayed contextual fear conditioning protocol which yields significant single- trial fear conditioning with temporal parameters amenable to catFISH analysis. Analysis yielded clear evidence that a population of BLA neurons receives convergent CS and US information at the time of the learning, that this only occurs when the CS-US arrangement is supportive of the learning, and that this process requires N-methyl-D-aspartate receptor activation. In contrast, CS-US convergence was not observed in dorsal hippocampus.Conclusions/significanceBased on the pattern of Arc activation seen in conditioning and control groups, we propose that a key requirement for CS-US convergence onto BLA neurons is the potentiation of US responding by prior exposure to a novel CS. Our results also support the view that contextual fear memories are encoded in the amygdala and that the role of dorsal hippocampus is to process and transmit contextual CS information.

Project description:Threat conditioning is a common associative learning model with translational relevance. How threat-conditioned cues impact on formally unrelated instrumental behavior in humans is not well known. Such an effect is known as Pavlovian-to-instrumental transfer (PIT). While PIT with aversive primary Pavlovian reinforcers is established in nonhuman animals, this is less clear in humans, where secondary reinforcers or instructed instrumental responses are most often investigated. We modified an existing human PIT procedure to include primary reinforcers. Participants first learned to obtain (or avoid losing) appetitive instrumental reinforcement (chocolate) by appropriate approach or avoidance actions. They either had to act (Go) or to withhold an action (NoGo), and in the Go condition either to approach a reward target to collect it or to withdraw from the reward target to avoid losing it. Then they learned to associate screen color (CS) with aversive Pavlovian reinforcement (electric shock US). In the transfer phase, we conducted the instrumental task during the presence of Pavlovian CS. In a first experiment, we show that the aversive Pavlovian CS+, compared to CS-, increased response rate in Go-Withdraw trials, i.e., induce conditioned facilitation of avoidance responses. This finding was confirmed in a second and independent experiment with an increased number of Go-Withdraw trials. Notably, we observed no appreciable conditioned suppression of approach responses. Effect size to distinguish CS+/CS- in Go-Withdraw trials was d = 0.42 in the confirmation sample. This would require n = 37 participants to demonstrate threat learning with 80% power. Thus, the effect size is on a practically useful scale although smaller than for model-based analysis of autonomic measures. In summary, our results indicate conditioned facilitation of formally unrelated instrumental avoidance behavior in humans and provide a novel behavioral threat learning measure that requires only key presses.

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Human Pavlovian fear conditioning conforms to probabilistic learning.

Publications

Human Pavlovian fear conditioning conforms to probabilistic learning.

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