Biology subjects

Cuesta, P.

Publications and source records attributed to Cuesta, P..

3 recordsLinked to original sources

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↗

bioRxiv2023

When Maturation is Not Linear: Brain Oscillatory Activity in the Process of Aging as Measured by Electrophysiology

Changes in brain oscillatory activity are commonly used as biomarkers both in cognitive neuroscience and in neuropsychiatric conditions. However, little is known about how its profile changes across maturation. Here we use regression models to characterize magnetoencephalography power changes within classical frequency bands in a sample of 792 healthy participants, covering the range 13 to 80 years old. Our results reveal complex, non-linear trajectories of power changes that challenge the linear model traditionally reported. Moreover, these trajectories also exhibit variations across cortical regions. Remarkably, we observed that increases in slow wave activity are associated with a better cognitive performance across the lifespan, as well as with larger gray matter volume for elderlies, while fast wave activity decreases with adulthood. These results suggest that elevated power in low-frequency resting-state activity during aging may reflect a proxy for deterioration, rather than serving as a compensatory mechanism, as usually interpreted. In addition, it enhances our comprehension of both neurodevelopment and the aging process by highlighting the complexity and regional specificity of changes in brain rhythms. Furthermore, our findings have potential implications for understanding cognitive performance and structural integrity.

neuroscience↗

bioRxiv2023

The more, the merrier: multivariate phase synchronization methods excel pairwise ones in estimating brain connectivity from reconstructed neural sources

The estimation of functional connectivity (FC) from electro-(EEG) or magnetoencephalographic (MEG) recordings suffers from low spatial resolution, being one of the reasons for the reduced number of sensors compared to the number of reconstructed sources of activity. This problem can be avoided by estimating FC between larger regions instead of individual sources. However, combining all the sources in each area to produce a single time series per region is far from trivial. We have used simultaneous EEG/MEG data from 11 participants and compared the FC estimates from both techniques by using different multivariate approaches. Since the underlying generators are identical for EEG and MEG, the more similar the FC estimation from both techniques is, the more accurate it is likely to be. The results show that using either the average or the root-mean-square of the bivariate source-to-source FC estimates consistently outperforms the use of a representative time series from each area. We concluded that the reconstructed activity in each brain region is too complex to be reduced to a single representative time series and that full multivariate approaches must be used to describe between-area FC from electrophysiological recordings accurately. Moreover, the high correlation between the FC values estimated from EEG and MEG suggests that the results found in the high-sensitivity, low-noise MEG can be transferable to the more affordable EEG, at least when high-quality source reconstruction is used.

bioengineering↗