Sensitivity to intrinsic rewards is domain general and related to mental health

Blain, Bastien; Pinhorn, India; Sharot, Tali

doi:10.1038/s44220-023-00116-x

Cited by 5 publications

(3 citation statements)

References 102 publications

(65 reference statements)

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“…This fits well with the clinical features of anhedonia (or depression), i.e. an inability to enjoy, a lack of motivation to participate in typically rewarding activities [40], [86], [87], and difficulty using reward-related information to guide decisions [42], [88], [89]. Turning to apathy, we observed our most surprising, yet robust, transdiagnostic finding.…”

Section: Discussionsupporting

confidence: 80%

Emotions and individual differences shape foraging under threat

Scholl¹,

Trier²,

O’Reilly³

et al. 2023

Preprint

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Animals and humans in natural environments balance their time between vigilance for threats and foraging for rewards. We designed a decision-making task to investigate how mood states and psychiatrically-relevant transdiagnostic dimensions affected this in a large online sample (discovery: N=374, replication: N=702). Mood was related to task environmental factors and stress showed homeostatic relationships with task behaviours such as foraging. Anxiety was associated with decreased vigilance due to threat-related worry, while compulsive checking was linked with increased but sub-optimal vigilance. Apathy was related to reduced vigilance and more frequent foraging, potentially reflecting reluctance to switch behaviours. Anhedonia was linked with a reduction in self-reported task engagement. Women reported higher stress and favoured vigilance over foraging. In sum, behavioural traits associated with psychological illness corresponded not simply to responsivity to threat but to specific, replicable patterns of balancing behaviour between foraging and vigilance for predatory threat.

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Section: Discussionsupporting

confidence: 80%

Emotions and individual differences shape foraging under threat

Scholl¹,

Trier²,

O’Reilly³

et al. 2023

Preprint

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“…A complementary genetic perspective on music reward sensitivity could be a particularly fruitful strategy to better understand human musicality and affect because we found genetic influences to be primarily separate from other relevant perceptual-affective processes, such as music perceptual abilities and general reward sensitivity. The dissociation between the genetics of music reward sensitivity and general perceptual and reward processing mirrors the finding that specific musical anhedonia, i.e., blunted or absent hedonic responses from music stimuli, exists in the absence of any perceptual or generalised reward deficit 12,16 , yet contrasts other findings suggesting sensitivity to intrinsic rewards to be domain general 50 . This implies that genetic variance associated with music reward sensitivity, beyond perceptual and general reward processing, can be used to better disentangle and understand the mechanisms involved in sensory-specific experiences of enjoyment.…”

Section: Discussionsupporting

confidence: 53%

Distinct genetic pathways to music enjoyment

Bignardi,

Wesseldijk,

Mas-Herrero

et al. 2024

Preprint

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Humans engage with music for various reasons that range from emotional regulation and relaxation to social bonding. While there are large inter-individual differences in how much humans enjoy music, little is known about the origins of those differences. Here, we disentangled the genetic factors underlying such variation. We collected behavioural data on several facets of music reward sensitivity, music perceptual ability, and general reward sensitivity from a large sample of Swedish twins (N = 9,169). We found that genetic factors substantially explain variance in music reward sensitivity above and beyond genetic influences shared with music perception and general reward sensitivity. Furthermore, multivariate analyses showed that genetic influences on the different facets of music reward sensitivity are partly distinct, uncovering distinct pathways to music enjoyment and different patterns of genetic associations with objectively assessed music perceptual abilities. These results paint a complex picture in which partially distinct sources of genetic variation contribute to different aspects of musical enjoyment and open up new possibilities for using inter-individual differences to gain insights into the biology of a key aspect of human behaviour.

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“…It should be noted that recent evidence has suggested that intrinsic motivation may lead to an analogous set of findings to those predicted by adaptive coding models (Molinaro and Collins, 2023). The capacity for intrinsic motivation also might vary across individuals (Blain et al, 2023), leading to an alternative set of predictions generated by intrinsic motivation models, which could be pursued in future work. Another scenario I did not consider was whether alpha influences the magnitude of the neural RPE signal directly (as opposed to indirectly by affecting prior expectations).…”

Section: Limitationsmentioning

confidence: 95%

A novel technique for delineating the effect of variation in the learning rate on the neural correlates of reward prediction errors in model-based fMRI

Chase

2023

Front. Psychol.

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IntroductionComputational models play an increasingly important role in describing variation in neural activation in human neuroimaging experiments, including evaluating individual differences in the context of psychiatric neuroimaging. In particular, reinforcement learning (RL) techniques have been widely adopted to examine neural responses to reward prediction errors and stimulus or action values, and how these might vary as a function of clinical status. However, there is a lack of consensus around the importance of the precision of free parameter estimation for these methods, particularly with regard to the learning rate. In the present study, I introduce a novel technique which may be used within a general linear model (GLM) to model the effect of mis-estimation of the learning rate on reward prediction error (RPE)-related neural responses.MethodsSimulations employed a simple RL algorithm, which was used to generate hypothetical neural activations that would be expected to be observed in functional magnetic resonance imaging (fMRI) studies of RL. Similar RL models were incorporated within a GLM-based analysis method including derivatives, with individual differences in the resulting GLM-derived beta parameters being evaluated with respect to the free parameters of the RL model or being submitted to other validation analyses.ResultsInitial simulations demonstrated that the conventional approach to fitting RL models to RPE responses is more likely to reflect individual differences in a reinforcement efficacy construct (lambda) rather than learning rate (alpha). The proposed method, adding a derivative regressor to the GLM, provides a second regressor which reflects the learning rate. Validation analyses were performed including examining another comparable method which yielded highly similar results, and a demonstration of sensitivity of the method in presence of fMRI-like noise.ConclusionOverall, the findings underscore the importance of the lambda parameter for interpreting individual differences in RPE-coupled neural activity, and validate a novel neural metric of the modulation of such activity by individual differences in the learning rate. The method is expected to find application in understanding aberrant reinforcement learning across different psychiatric patient groups including major depression and substance use disorder.

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Sensitivity to intrinsic rewards is domain general and related to mental health

Cited by 5 publications

References 102 publications

Emotions and individual differences shape foraging under threat

Emotions and individual differences shape foraging under threat

Distinct genetic pathways to music enjoyment

A novel technique for delineating the effect of variation in the learning rate on the neural correlates of reward prediction errors in model-based fMRI

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