Biology subjects

Verdejo-Roman, J.

Publications and source records attributed to Verdejo-Roman, J..

3 recordsLinked to original sources

bioRxiv2025

The elusive neural signature of emotion regulation capabilities: evidence from a large-scale consortium

Cognitive reappraisal is a fundamental emotion regulation strategy for mental and physical well-being, but how its neural mechanisms relate to individual differences remains poorly understood. In a consortium effort analyzing 40 fMRI datasets (N=2,175), we examined the relationship between neural activation during reappraisal tasks and three core individual difference indices of reappraisal capabilities: (1) trait questionnaires, (2) task-based affective ratings, and (3) amygdala down-regulation. Strikingly, there was no shared overlap across these three common indices. Only a very weak correlation emerged between amygdala down-regulation and task-based affective ratings. Whole-brain analyses revealed no reliable neural associations with trait questionnaires, and associations with task-based affective ratings fell outside canonical emotion regulation networks (e.g., prefrontal circuitry). Moreover, amygdala down-regulation, often interpreted as a stable individual marker, was confounded by person-specific whole-brain responses -- a limitation extending to fMRI research beyond the emotion regulation domain. These findings challenge the assumption that an individuals prefrontal activity is a valid indicator of their reappraisal capabilities and suggest that common trait, behavioral, and neural measures might capture distinct facets of emotion regulation. More broadly, our results highlight concrete methodological challenges for fMRI research on individual differences, with implications extending beyond emotion regulation to the neuroscience of personality, psychopathology, and general well-being.

neuroscience↗

bioRxiv2023

Computational modeling of reinforcement learning and functional neuroimaging of probabilistic reversal dissociates compulsive behaviors in Gambling and Cocaine Use Disorders

Cognitive flexibility refers to the ability to adjust to changes in the environment and is essential for adaptive behavior. It can be investigated using laboratory tests such as probabilistic reversal learning (PRL). In individuals with both Cocaine Use Disorder (CUD) and Gambling Disorder (GD), overall impairments in PRL flexibility are observed. However, it is poorly understood whether this impairment depends on the same brain mechanisms in cocaine and gambling addictions. Reinforcement learning (RL) is the process by which rewarding or punishing feedback from the environment is used to adjust behavior, to maximise reward and minimise punishment. Using RL models, a deeper mechanistic explanation of the latent processes underlying cognitive flexibility can be gained. Here, we report results from a re-analysis of PRL data from control participants (n=18) and individuals with either GD (n=18) or CUD (n=20) using a hierarchical Bayesian RL approach. We observed significantly reduced stimulus stickiness (i.e., stimulus-bound perseveration) in GD, which may reflect increased exploratory behavior that is insensitive to outcomes. RL parameters were unaffected in CUD. We relate the behavioral findings to their underlying neural substrates through an analysis of task-based fMRI data. We report differences in tracking reward and punishment expected values (EV) in individuals with GD compared to controls, with greater activity during reward EV tracking in the cingulate gyrus and amygdala. In CUD, we observed reduced responses to positive punishment prediction errors (PPE) and increased activity following negative PPEs in the superior frontal gyrus compared to controls. Thus, an RL framework serves to differentiate behavior in a probabilistic learning paradigm in two compulsive disorders, GD and CUD.

neuroscience↗

bioRxiv2022

E/I unbalance and aberrant oscillation dynamics predict preclinical Alzheimer's disease

Alzheimers disease (AD) is a chronic, nonlinearly progressive neurodegenerative disease that affects multiple domains of behaviour and is the most common form of dementia. However, there is scarce understanding of its biological basis nor there are reliable markers for the earliest disease stages preceding AD. Here we investigated whether AD progression is predicted by increasingly aberrant critical brain dynamics driven by underlying E/I imbalance using magnetoencephalography (MEG) data from cross-sectional (N=343) and longitudinal (N=45) cohorts. As a hallmark of brain criticality, we quantified long-range temporal correlations (LRTCs) in neuronal oscillations and tracked changes in neuronal excitability. We demonstrate that attenuation and progressive changes of LRTCs characterize the earliest stages of disease progression and yield accurate classification to individuals with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). Our data indicate that pathological brain critical dynamics in AD progression provide a clinical marker for targeting specific treatments to individuals at increased risk.

neuroscience↗