Biology subjects

Marco-Pallares, J.

Publications and source records attributed to Marco-Pallares, J..

5 recordsLinked to original sources

bioRxiv2024

Odor-induced persistent neural activity in associativeencoding in humans

This study explored the impact of brief exposure to odor cues on sustained neural activity during a 6-second delay period before memory encoding of a picture image. Combining univariate and multivariate ERP analytical approaches, our results align with nonhuman data, indicating that odor cues induced sustained neural activity in humans, persisting beyond the odor exposure throughout the nearly 6-second delay period. We observed higher amplitude of sustained ERPs for unpleasant compared to pleasant odor cues. Additionally, participants exhibited more confident memory recall for pictures preceded by unpleasant rather than pleasant odor cues during encoding, underscoring the influence of brief odor cues on memory formation for temporally distant events. In conclusion, this study revealed that brief exposure to odor cues induced sustained neural activity in humans, with distinct effects on memory formation along the pleasantness dimension, emphasizing the lasting impact of olfactory stimuli on cognitive processes.

neuroscience↗

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

Visuomotor temporal adaptation is tuned to gamma brain oscillatory coherence

Every time we use our smartphone, tablet, or other electronic devices we are exposed to temporal delays between our actions and the sensory feedback. We can compensate for such delays by adjusting our motor commands and doing so likely requires establishing new temporal mappings between motor areas and sensory predictions. However, little is known about the neural underpinnings that would support building new temporal correspondences between different brain areas. We here address the possibility that communication through coherence, which is thought to support neural interareal communication, lies behind the neural processes accounting for how humans cope with additional delays between motor and sensory areas. We recorded EEG activity while participants intercepted moving targets while seeing a cursor that followed their hand with a delay rather than their own hand. Participants adjusted their movements to the delayed visual feedback and intercepted the target with the cursor. The EEG data shows a significant increase in coherence of beta and gamma bands between visual and motor areas during the hand on-going movement towards interception. However, when looking at differences between participants depending on the level of adaptation, only the increase in gamma band correlated with the level of temporal adaptation. We are able to describe the time course of the coherence using coupled oscillators showing that the times at which high coherence is achieved are within useful ranges to solve the task. Altogether, these results evidence the functional relevance of brain coherence in a complex task where adapting to new delays is crucial. AUTHOR SUMMARYHumans are often exposed to delays between their actions and the incoming sensory feedback caused by actions. While there have been advances in the understanding of the conditions at which temporal adaptation can occur, little is known about the neural mechanisms enabling temporal adaptation. In the present study we measure brain activity (EEG) to investigate whether communication through coherence between motor and sensory areas might be responsible for ones ability to cope with externally imposed delays in an interception task. We show evidence that neural coherence at gamma band between visual and motor areas is related to the degree of adaptation to temporal delays.

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↗