Biology subjects

de Diego-Balaguer, R.

Publications and source records attributed to de Diego-Balaguer, R..

6 recordsLinked to original sources

bioRxiv2024

Investigating altered limbic reward system in Huntington's Disease: Implications for apathy

Huntingtons disease (HD) is an inherited neurodegenerative condition characterized by motor, cognitive, and behavioral impairments. Apathy, marked by reduced motivation and goal-directed behavior, is the most prevalent psychiatric symptom in HD, impacting both patients and caregivers. Traditionally linked to executive dysfunction within the dorsolateral prefrontal cortex (dlPFC)-dorsal striatum loop in HD, the role of limbic regions in the basal ganglia and their impact on reward processing deficits remains poorly understood. This study sought to dissociate the functional correlates that are altered in reward valuation and may underlie apathy in HD. We aimed to tease apart whether apathy is associated with insensitivity to processing rewards, hypersensitivity to losses, or both, leading to the observed lack of motivation in apathetic individuals. Thirty-nine HD gene-expansion carriers (HDGEC) and 26 non-apathetic control participants underwent functional magnetic resonance imaging during a gambling task. The goal was to identify disrupted reward-related regions in HDGEC and their association with apathetic symptoms. Whole-brain analysis of gains and losses separately showed a significant reduction in activity, when HD group was compered to controls, within the left ventral striatum (VS), including the nucleus accumbens. The effect observed in the VS remained when clinically apathetic HDGEC were compared with controls. Conversely, non-apathetic HDGEC did not show any significant differences from controls. Interestingly, these group differences appeared exclusively during the processing of the reward. Additionally, higher levels of apathy were associated with especially decreased activity related with the processing of gains in this region. Our findings highlight the vulnerability of the left VS in HD and its association with the altered processing of gains, particularly in apathetic individuals, while preserving the valuation of losses. This suggests that reward insensitivity associated with VS dysfunction may be an important component of apathy in HD. Understanding the underlying mechanisms of reward processing and apathy in HD may help elucidate the implications of limbic regions as opposed to frontal executive dysfunction in apathy.

neuroscience↗

bioRxiv2023

Crossmodal statistical learning is facilitated by modality predictability

Statistical learning involves extracting statistical regularities from the environment. Despite the ubiquitous crossmodal relations in our environment, previous research has failed in showing crossmodal learning suggesting that statistical learning is modality-specific, occurring within but not between sensory modalities. The present study investigates under which circumstances statistical learning can occur between modalities. In the first experiment, participants viewed a stream of meaningless visual fractals and synthetic auditory stimuli. Importantly, the sequence of stimuli could be grouped into unimodal or crossmodal pairs based on their internal transitional probabilities. Using implicit and explicit measures of learning, we found that participants only learned the unimodal pairs. In the second experiment, pairs were presented in separate unimodal and crossmodal blocks. The crossmodal blocks alternated visual and auditory modalities allowing participants to anticipate the upcoming modality. This manipulation allowed significant statistical learning for the crossmodal pairs, reflected only by implicit measures. This suggests that modality transitions predictability aids correct attention deployment across sensory modalities, crucial for learning crossmodal statistical contingencies. In the third experiment, where audiovisual stimuli with semantic content were used leaving access to an amodal shared representation, participants could explicitly recognize statistical regularities between crossmodal pairs even when the upcoming modality was unpredictable. This finding suggests statistical learning between crossmodal pairs can occur when sensory-level limitations are bypassed, and when learning unfolds at an amodal level of representation. These findings challenge the view that statistical learning is strictly modality-specific, instead indicating that crossmodal statistical learning depends on attentional mechanisms and representational level. Public significance statementPrevious research has established that low-level statistical learning occurs within individual sensory modalities. However, evidence for statistical learning across modalities remains limited. This has led to the hypothesis that statistical learning operates as a modality-specific system, constrained by the perceptual properties and content of each sensory system. In this study, we demonstrate that modality transitions predictability enables crossmodal statistical learning, even in the absence of semantic information. Notably, this constraint does not apply to meaningful stimuli, which can be processed at an amodal level. Our findings broaden the classical neurobiological model of statistical learning by highlighting the roles of attentional mechanisms and representational levels in supporting crossmodal statistical learning.

animal behavior and cognition↗

bioRxiv2023

Disentangling the neurobiological bases of temporal impulsivity in Huntington's disease

BackgroundDespite its impact on daily life, impulsivity in Huntingtons disease (HD) is understudied as a neuropsychiatric symptom. Our aim is to characterize temporal impulsivity in HD, evaluated through a Delay Discounting (DD) task, and to disentangle the underlying white matter correlates in HD. MethodsForty-seven HD individuals and thirty-six healthy controls conducted a DD task and complementary Sensitivity to Punishment and Sensitivity to Reward (SR) Questionnaire. Diffusion-tensor imaging was employed to characterize the structural connectivity of two limbic tracts: the uncinate fasciculus (UF) and the accumbofrontal tract (NAcc-OFC). Multiple linear regression analyses were applied to analyze the relationship between impulsive behavior and white-matter microstructural integrity. ResultsAltered structural connectivity in both the NAcc-OFC and UF in HD individuals was observed. Moreover, the variability in structural connectivity of these tracts was associated with the individual differences in temporal impulsivity. Specifically, increased structural connectivity in the right NAcc-OFC predicted increased temporal impulsivity, while reduced connectivity in the left UF was associated with higher temporal impulsivity scores. LimitationsOther cognitive mechanisms and white matter tracts may play a role in temporal impulsivity. ConclusionsThis study provides evidence that individual differences observed in impulsivity may be explained by variability in limbic fronto-striatal tracts. We emphasize the importance of investigating the spectrum of impulsivity in HD, less prevalent than other psychiatric features, but impacting the quality of life of patients and their caregivers.

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↗

bioRxiv2019

Integrating When and What Information in the Left Parietal Lobe Allows Language Rule Generalization

A crucial aspect when learning a language is discovering the rules that govern how words are combined in order to convey meanings. Since rules are characterized by sequential co-occurrences between elements (e.g. These cupcakes are unbelievable), tracking the statistical relationships between these elements is fundamental. However, statistical learning alone cannot fully account for the ability to create abstract rule representations that can be generalized, a paramount requirement of linguistic rules. Here, we provide evidence that, after the statistical relations between words have been extracted, the engagement of goal-directed attention is key to enable rule generalization. Incidental learning performance during a rule-learning task on an artificial language revealed a progressive shift from statistical learning to goal-directed attention. In addition, and consistent with the recruitment of attention, fMRI analyses of late learning stages showed left parietal activity within a broad bilateral dorsal fronto-parietal network. Critically, rTMS on participants peak of activation within the left parietal cortex impaired their ability to generalize learned rules to a structurally analogous new language. No stimulation or rTMS on a non-relevant brain region did not have the same interfering effect on generalization. Performance on an additional attentional task showed that rTMS on the same parietal site hindered participants ability to integrate what (stimulus identity) and when (stimulus timing) information about an expected target. The present findings suggest that learning rules from speech is a two-stage process: following statistical learning, goal-directed attention -involving left parietal regions- integrates what and when stimulus information to facilitate rapid rule generalization.

neuroscience↗

bioRxiv2018

Implicit but not explicit exposure to threat conditioned stimulus prevents spontaneous recovery of threat potentiated startle responses in humans

It has long been posited that threat learning operates and forms under an affective and a cognitive learning system that are supported by different brain circuits. A primary drawback in exposure-based therapies is the high rate of relapse when higher order inhibitory structures failed to inhibit the emotional responses driven by the defensive circuit. It has been shown that implicit exposure of fearful stimuli leads to a long-lasting reduction of avoidance behavior in patients with phobia through the facilitation of fear processing areas in the absence of subjective fear. Despite the potential benefits of this approach in the treatment of phobias and PTSD, implicit exposure to fearful stimuli is still under-investigated. Here, we used unconscious presentation of threat-conditioned stimuli in healthy humans, using a continuous flash suppression technique. We found that implicit exposure of a conditioned stimulus reduced, on the following day, defensive responses to the conditioned stimulus measured by threat-potentiated startle responses but not by the electrodermal activity. Our results suggest that implicit exposure using CFS might facilitate the modulation of the affective component of fearful memories, representing an important therapeutic target to further advance exposure-based psychotherapies.

animal behavior and cognition↗