Erotic cue exposure increases physiological arousal, biases choices toward immediate rewards, and attenuates model‐based reinforcement learning.
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| Title: | Erotic cue exposure increases physiological arousal, biases choices toward immediate rewards, and attenuates model‐based reinforcement learning. |
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| Authors: | Mathar, David (AUTHOR), Wiebe, Annika (AUTHOR), Tuzsus, Deniz (AUTHOR), Knauth, Kilian (AUTHOR), Peters, Jan (AUTHOR) |
| Source: | Psychophysiology. Dec2023, Vol. 60 Issue 12, p1-27. 27p. |
| Abstract: | Computational psychiatry focuses on identifying core cognitive processes that appear altered across distinct psychiatric disorders. Temporal discounting of future rewards and model‐based control during reinforcement learning have proven as two promising candidates. Despite its trait‐like stability, temporal discounting may be at least partly under contextual control. Highly arousing cues were shown to increase discounting, although evidence to date remains somewhat mixed. Whether model‐based reinforcement learning is similarly affected by arousing cues remains unclear. Here, we tested cue‐reactivity effects (erotic pictures) on subsequent temporal discounting and model‐based reinforcement learning in a within‐subjects design in n = 39 healthy heterosexual male participants. Self‐reported and physiological arousal (cardiac activity and pupil dilation) were assessed before and during cue exposure. Arousal was increased during exposure of erotic versus neutral cues both on the subjective and autonomic level. Erotic cue exposure increased discounting as reflected by more impatient choices. Hierarchical drift diffusion modeling (DDM) linked increased discounting to a shift in the starting point bias of evidence accumulation toward immediate options. Model‐based control during reinforcement learning was reduced following erotic cues according to model‐agnostic analysis. Notably, DDM linked this effect to attenuated forgetting rates of unchosen options, leaving the model‐based control parameter unchanged. Our findings replicate previous work on cue‐reactivity effects in temporal discounting and for the first time show similar effects in model‐based reinforcement learning in a heterosexual male sample. This highlights how environmental cues can impact core human decision processes and reveal that comprehensive modeling approaches can yield novel insights in reward‐based decision processes. Our findings highlight how environmental cues can impact core human decision processes with high relevance for a broad spectrum of (sub‐) clinical conditions. With this, we replicate previous work of erotic cue exposure on temporal discounting and for the first time show similar effects in model‐based reinforcement learning. By utilizing hierarchical Bayesian drift diffusion modeling, we demonstrate that comprehensive modeling of behavioral data can yield deeper insights in psychophysiological research. [ABSTRACT FROM AUTHOR] |
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| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | Computational psychiatry focuses on identifying core cognitive processes that appear altered across distinct psychiatric disorders. Temporal discounting of future rewards and model‐based control during reinforcement learning have proven as two promising candidates. Despite its trait‐like stability, temporal discounting may be at least partly under contextual control. Highly arousing cues were shown to increase discounting, although evidence to date remains somewhat mixed. Whether model‐based reinforcement learning is similarly affected by arousing cues remains unclear. Here, we tested cue‐reactivity effects (erotic pictures) on subsequent temporal discounting and model‐based reinforcement learning in a within‐subjects design in n = 39 healthy heterosexual male participants. Self‐reported and physiological arousal (cardiac activity and pupil dilation) were assessed before and during cue exposure. Arousal was increased during exposure of erotic versus neutral cues both on the subjective and autonomic level. Erotic cue exposure increased discounting as reflected by more impatient choices. Hierarchical drift diffusion modeling (DDM) linked increased discounting to a shift in the starting point bias of evidence accumulation toward immediate options. Model‐based control during reinforcement learning was reduced following erotic cues according to model‐agnostic analysis. Notably, DDM linked this effect to attenuated forgetting rates of unchosen options, leaving the model‐based control parameter unchanged. Our findings replicate previous work on cue‐reactivity effects in temporal discounting and for the first time show similar effects in model‐based reinforcement learning in a heterosexual male sample. This highlights how environmental cues can impact core human decision processes and reveal that comprehensive modeling approaches can yield novel insights in reward‐based decision processes. Our findings highlight how environmental cues can impact core human decision processes with high relevance for a broad spectrum of (sub‐) clinical conditions. With this, we replicate previous work of erotic cue exposure on temporal discounting and for the first time show similar effects in model‐based reinforcement learning. By utilizing hierarchical Bayesian drift diffusion modeling, we demonstrate that comprehensive modeling of behavioral data can yield deeper insights in psychophysiological research. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 00485772 |
| DOI: | 10.1111/psyp.14381 |
