Biology subjects

Mas-Herrero, E.

Publications and source records attributed to Mas-Herrero, E..

5 recordsLinked to original sources

bioRxiv2024

Distinct genetic pathways to music enjoyment

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.

genetics↗

bioRxiv2021

Statistical learning as reinforcement learning phenomena

Statistical learning (SL) is the ability to extract regularities from the environment. In the domain of language, this ability is fundamental in the learning of words and structural rules. In lack of reliable online measures, statistical word and rule learning have been primarily investigated using offline (post-familiarization) tests, which gives limited insights into the dynamics of SL and its neural basis. Here, we capitalize on a novel task that tracks the online statistical learning of language rules combined with computational modelling to show that online SL responds to reinforcement learning principles rooted in striatal function. Specifically, we demonstrate - on two different cohorts - that a Temporal Difference model, which relies on prediction errors, accounts for participants online learning behavior. We then show that the trial-by-trial development of predictions through learning strongly correlates with activity in both ventral and dorsal striatum. Our results thus provide a detailed mechanistic account of language-related SL and an explanation for the oft-cited implication of the striatum in SL tasks. This work, therefore, bridges the longstanding gap between language learning and reinforcement learning phenomena.

neuroscience↗

bioRxiv2020

Dopaminergic signalling modulates reward-driven music memory consolidation

Previously, we provided causal evidence for a dopamine-dependent effect of intrinsic reward on memory during self-regulated learning (Ripolles et al., 2016; Ripolles et al., 2018). Here, we further investigated the dopamine-dependent link between reward and memory by focusing on one of the most iconic abstract rewards in humans: music. Twenty-nine healthy participants listened to unfamiliar excerpts--which had to be remembered following a consolidation period--after the intake of a dopaminergic antagonist, a dopaminergic precursor, and a placebo across three separated sessions. The intervention modulated the pleasantness experienced during music-listening and memory recognition of the presented songs (i.e., lower with the antagonist, higher with the precursor) in individuals with higher sensitivity to musical reward. Our work highlights the flexibility of the human dopaminergic system, which is able to enhance memory formation not only through explicit and/or primary reinforcers but also via intrinsic, abstract, or aesthetic rewards of different natures.

neuroscience↗

bioRxiv2018

Intrinsically regulated learning is modulated by synaptic dopamine availability

We recently provided evidence that an intrinsic reward-related signal--triggered by successful learning in absence of any external feedback--modulated the entrance of new information into long-term memory via the activation of the dopaminergic midbrain, hippocampus, and ventral striatum (the SN/VTA-Hippocampal loop; Ripolles et al., 2016). Here, we used a double-blind, within-subject randomized pharmacological intervention to test whether this learning process is indeed dopamine-dependent. A group of healthy individuals completed three behavioural sessions of our learning task after the intake of different pharmacological treatments: a dopaminergic precursor, a dopamine receptor antagonist or a placebo. Results show that the pharmacological intervention bidirectionally modulated behavioral measures of both learning and pleasantness, inducing memory benefits after 24 hours only for those participants with a high sensitivity to reward. These results provide causal evidence for a dopamine-dependent mechanism instrumental in intrinsically regulated learning, and further suggest that subject-specific dopamine sensitivity drastically alters learning success.

neuroscience↗

bioRxiv2017

The contribution of striatal pseudo-reward prediction errors to value-based decision-making

Most studies that have investigated the brain mechanisms underlying learning have focused on the ability to learn simple stimulus-response associations. However, in everyday life, outcomes are often obtained through complex behavioral patterns involving a series of actions. In such scenarios, parallel learning systems are important to reduce the complexity of the learning problem, as proposed in the framework of hierarchical reinforcement learning (HRL). One of the key features of HRL is the computation of pseudo-reward prediction errors (PRPEs) which allow the reinforcement of actions that led to a sub-goal before the final goal itself is achieved. Here we wanted to test the hypothesis that, despite not carrying any rewarding value per se, pseudo-rewards might generate a bias in choice behavior when reward contingencies are not well-known or uncertain. Second, we also hypothesized that this bias might be related to the strength of PRPE striatal representations. In order to test these ideas, we developed a novel decision-making paradigm to assess reward prediction errors (RPEs) and PRPEs in two studies (fMRI study: n = 20; behavioural study: n = 19). Our results show that overall participants developed a preference for the most pseudo-rewarding option throughout the task, even though it did not lead to more monetary rewards. fMRI analyses revealed that this preference was predicted by individual differences in the relative striatal sensitivity to PRPEs vs RPEs. Together, our results indicate that pseudo-rewards generate learning signals in the striatum and subsequently bias choice behavior despite their lack of association with actual reward.

neuroscience↗