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del Agua, E.

Publications and source records attributed to del Agua, E..

3 recordsLinked to original sources

Global nonequilibrium cortical dynamics tie mid-level pupil-linked arousal to optimal task performance in humans

Ongoing fluctuations in brain state, largely driven by neuromodulators of arousal, shape how sensory inputs are processed and decisions are made. Here, we combined pharmacological manipulations and pupillary proxies of arousal to examine how global cortical state dynamics relate to perceptual sensitivity. We applied the thermodynamics-inspired INSIDEOUT framework to electroencephalography (EEG) recordings from two visual discrimination tasks performed under placebo, atomoxetine (noradrenergic enhancer), and donepezil (cholinergic enhancer) challenges. INSIDEOUT quantifies the strength of functional hierarchies within the brain via the computation of temporal irreversibility in neural activity. Trial-wise global irreversibility increased linearly with pupil-indexed arousal and exhibited a nonlinear inverted-U relationship with perceptual sensitivity, while showing no differences across drug conditions. A nonlinear mediation analysis revealed that temporal irreversibility can account for a significant portion of the association between pupil-linked arousal and perceptual sensitivity. At lower arousal, increases in prestimulus irreversibility improved perceptual accuracy, whereas at higher arousal, pre- and poststimulus irreversibility had different effects. These results bridge intrinsic whole-brain dynamics with perceptual decision-making, demonstrating that neuromodulator-linked arousal tunes cortical states and, in turn, perceptual performance. More broadly, the results shed new light on how arousal may reconfigure neural global dynamics.

neuroscience↗

Modeling Hierarchical Brain Dynamics Outperforms Hormonal Biomarkers in Predicting Menstrual Cycle Phases

Hormonal fluctuations across the menstrual cycle influence large-scale brain dynamics, yet the underlying neurobiological mechanisms remain poorly understood. In this study, 60 nat-urally cycling women were scanned using resting-state fMRI during the early follicular, pre-ovulatory, and mid-luteal phases. We then applied a thermodynamics-inspired framework to explore the functional hierarchical organization of whole-brain dynamics across these phases. First, we found that brain dynamics are significantly modulated by estradiol, progesterone, and age across multiple resting-state networks. Second, to elucidate underlying mechanisms, we es-timated generative effective connectivity (GEC) matrices using whole-brain models and trained support vector machine classifiers to predict menstrual phases. These model-based biomarkers outperformed traditional functional connectivity and hormone measures in classifying men-strual cycle phases. These findings reveal that menstrual cycle-related changes modulate the hierarchical reorganization of brain dynamics, highlighting the potential of model-based ap-proaches to advance womens brain health research.

neuroscience↗

Whole-brain dynamics and hormonal fluctuations across the menstrual cycle: The role of progesterone and age in healthy women

Recent neuroimaging research suggests that female sex hormone fluctuations modulate brain activity. Nevertheless, how brain network dynamics change across the female menstrual cycle remains largely unknown. Here, we investigated the dynamical complexity u nderlying three menstrual cycle phases (i.e., early follicular, pre-ovulatory, and mid-luteal) in 60 healthy naturally-cycling women scanned using resting-state fMRI. Our results revealed that the preovulatory phase exhibited the highest variability over time (node-metastability) across the whole-brain functional network compared to the early follicular and mid-luteal phases, while the early follicular showed the lowest. Additionally, we found that large-scale resting-state networks reconfigure along the menstrual cycle phases. Finally, we used multilevel mixed-effects models to examine the impact of hormonal fluctuations and age on whole-brain and resting-state networks. We found significant age-related changes across the whole brain, control, and dorsolateral attention networks. Additionally, we observed progesterone-related changes, specifically within limbic and somatomotor networks. Overall, these findings evidence that both age and progesterone modulate brain network dynamics along the menstrual cycle.

neuroscience↗