Biology subjects

Uceta, M.

Publications and source records attributed to Uceta, M..

3 recordsLinked to original sources

bioRxiv2026

Neurodevelopment Trajectory of Electrophysiological Functional Connectivity Following Alcohol Use Initiation

BackgroundAdolescence is characterized by profound neurodevelopmental changes that shape large-scale brain network organization and may confer vulnerability to risk-taking behaviors, including alcohol use. While cross-sectional and prospective studies have examined functional connectivity (FC) alterations before and after consumption, there is little evidence of how networks evolve during adolescence. MethodsThe present longitudinal study investigated electrophysiological FC trajectories during alcohol initiation using resting-state magnetoencephalography (MEG). 61 alcohol-naive adolescents (mean age at baseline = 14.4) were assessed and re-evaluated two years later (mean age = 16.4). ResultsAt baseline, stronger FC in theta (4-8 Hz), alpha (8-12 Hz), and high-beta (20-30 Hz) bands predicted greater alcohol consumption at follow-up, replicating previous findings. Longitudinal analyses with linear mixed-effects models revealed significant stage x SAUs interactions across all three frequency bands. Adolescents with low-to-moderate alcohol use showed normative increases in FC over time, consistent with typical neurodevelopmental maturation. In contrast, heavier drinkers exhibited stabilization or reduction of FC, suggesting a divergence from normative trajectories. Notably, theta-band hyperconnectivity persisted after alcohol initiation and remained positively associated with current alcohol consumption, particularly across anteroposterior connections. ConclusionThese findings indicate heterogeneous neurodevelopmental trajectories associated with alcohol use severity. Elevated pre-consumption connectivity, especially in the theta band, may reflect a vulnerability marker rather than solely a consequence of alcohol exposure. Overall, results highlight the importance of considering individual variability in brain maturation when examining adolescent substance use and suggest that early hyperconnectivity may signal increased risk for heavier alcohol involvement.

neuroscience↗

bioRxiv2024

From electrophysiology to drink: Adolescent alcohol consumption predicted by differences in functional connectivity and neuroanatomy

Alcohol consumption during adolescence has been associated with neuroanatomical abnormalities and the appearance of future disorders. However, the latest advances in this field point to the existence of risk profiles which may lead to some individuals into an early consumption. To date, some studies have established predictive models of consumption based on sociodemographic, behavioural, and anatomical-functional variables using MRI. However, the neuroimaging variables employed are usually restricted to local and hemodynamic phenomena. Given the potential of connectome approaches, and the high temporal dynamics of electrophysiology, we decided to explore the relationship between future alcohol consumption and electrophysiological connectivity measured by MEG in a cohort of 83 individuals aged 14 to 16. We calculated predictive models throughout multiple linear regressions based on behavioural, anatomical, and functional connectivity variables. As a result, we found a positive correlation between alcohol consumption and the functional connectivity in frontal, parietal, and frontoparietal connections. Also, we identified negative relationships of alcohol consumption with neuroanatomical variables. Finally, the linear regression analysis determined the importance of anatomical and functional variables in the prediction of alcohol consumption but failed to find associations with impulsivity, sensation-seeking, and executive function scales. As conclusion, the predictive traits obtained in these models were closely associated with changes occurring during neurodevelopment, suggesting the existence of different paths in neurodevelopment that have the potential to influence adolescents relationship with alcohol consumption. Significance statementTo understand the onset of heavy drinking habits and develop prevention strategies, we need to characterize predisposition profiles at early ages. This longitudinal work provides important evidence by showing how adolescents at risk for engaging in alcohol behaviors showed resting-state functional connectivity and grey matter differences years before. The combination of these metrics allows us to establish predictive models of future alcohol episodes. In addition, differences in functional connectivity showed a positive relationship with behavioral variables such as lower executive functions and higher on the sensation-seeking. These predisposition phenotypes may rely on divergent neurodevelopmental pathways and deeper neurobiological abnormalities, such as dysfunctions of inhibitory neurotransmission and/or a genetic background of vulnerability.

neuroscience↗

bioRxiv2024

Clustering Electrophysiological Predisposition to Binge Drinking: An Unsupervised Machine Learning analysis

BackgroundThe demand for fresh strategies to analyze intricate multidimensional data in neuroscience is increasingly evident. One of the most complex events during our neurodevelopment is adolescence, where our nervous system suffers constant changes, not only in neuroanatomical traits, but also in neurophysiological components. One of the most impactful factors we deal with during this time is our environment, especially when encountering external factors such as social behaviors or substance consumption. Binge Drinking (BD) has emerged as an extended pattern of alcohol consumption in teenagers, not only affecting their future lifestyle, but changing their neurodevelopment. Recent studies have changed their scope into finding predisposition factors that may lead adolescents into this kind of patterns of consumption. MethodsIn this article, using unsupervised machine learning (UML) algorithms, we analyze the relationship between electrophysiological activity of healthy teenagers and the levels of consumption they had two years later. We used hierarchical agglomerative UML techniques based on Wards minimum variance criterion to clusterize relations between power spectrum and functional connectivity and alcohol consumption, based on similarity in their correlations, in frequency bands from theta to gamma. ResultsWe found that all frequency bands studied had a pattern of clusterization based on anatomical regions of interest related to neurodevelopment and cognitive and behavioral aspects of addiction, highlighting the dorsolateral and medial prefrontal, the sensorimotor, the medial posterior and the occipital cortices. All this patterns, of great cohesion and coherence, showed an abnormal electrophysiological activity, representing a dysregulation in the development of core resting-state networks. The clusters found maintained not only plausibility in nature, but robustness, making this a great example of the usage of UML in the analysis of electrophysiological activity, a new perspective into analysis that, while contributing to classical statistics, can clarify new characteristics of the variables of interest.

neuroscience↗