Biology subjects

Mento, G.

Publications and source records attributed to Mento, G..

2 recordsLinked to original sources

bioRxiv2026

Where is ADHD in the brain? Evidence for a neurodevelopmental continuum of brain dynamics

BackgroundAttention-deficit/hyperactivity disorder (ADHD) has traditionally been conceptualized categorically, with efforts to identify disorder-specific neurobiological endophenotypes. However, dimensional models suggest that brain-behavior organization may follow developmental axes that cut across diagnostic boundaries. We tested whether neural dynamics and cortical excitability differentiate those with ADHD diagnoses from typically developing (TD) peers, and whether brain-behavior covariance aligns with diagnostic or developmental dimensions. MethodsWe studied 84 participants aged 8-17 years (51 ADHD, 33 TD). High-density electrophysiological (hdEEG) measures included task-free source-resolved data used to derive mean global brain fluidity (variance of dynamic functional connectivity) and region-specific cortical excitability. Behavioural measures included self- and parent-report questionnaires, cognitive control (CC) tasks, and neuropsychological tests. Partial least squares (PLS) assessed multivariate brain-behavior associations including age, followed by clustering based on latent component scores. ResultsGroup differences emerged in parent-report questionnaires and CC tasks, but not in neuropsychological measures. ADHD individuals showed higher mean global brain fluidity and increased cortical excitability. The excitability-fluidity relationship was network-dependent: higher excitability predicted higher fluidity in task-positive networks and lower fluidity in default-mode and salience networks, with no group effects. PLS identified a latent dimension linking neural metrics with age, verbal fluency, inhibitory control, and positive affect, but it did not distinguish ADHD from TD. Clustering revealed two neurodevelopmental profiles spanning both groups. ConclusionsWhile ADHD is associated with mean-level differences in neural dynamics, brain-behaviour organization follows a developmental neurocognitive-affective axis that transcends the diagnostic boundary. These findings support a dimensional framework for understanding neurobiological variation in neurodevelopmental conditions.

neuroscience↗

bioRxiv2024

Dynamic transient brain states in preschoolers mirror parental report of behavior and emotion regulation

The temporal dynamics of resting-state networks (RSNs) may represent an intrinsic functional repertoire supporting cognitive control performance across the lifespan (Kupis et al., 2021). However, little is known about brain dynamics during the preschool period, which is a sensitive time window for cognitive control development. The fast timescale of synchronization and switching characterizing cortical network functional organization gives rise to quasi-stable patterns (i.e., brain states) that recur over time. These can be inferred at the whole-brain level using Hidden Markov Models (HMMs), an unsupervised machine learning technique that allows the identification of rapid oscillatory patterns at the macro-scale of cortical networks (Vidaurre et al., 2018). The present study used a HMM technique to investigate dynamic neural reconfigurations and their associations with behavioral (i.e., parental questionnaires) and cognitive (i.e., neuropsychological tests) measures in typically developing preschoolers (4-6 years old). We used high density EEG to better capture the fast reconfiguration patterns of the HMM-derived metrics (i.e., switching rates, entropy rates, transition probabilities and fractional occupancies). Our results revealed that the HMM-derived metrics were reliable indices of individual neural variability and differed between boys and girls. However, only brain state transition patterns toward prefrontal and default-mode brain states, predicted differences on parental-report questionnaire scores. Overall, these findings support the importance of resting-state brain dynamics as functional scaffolds for behavior and cognition. Brain state transitions may be crucial markers of individual differences in cognitive control development in preschoolers. KeypointsO_LIHMM-derived metrics are reliable hallmarks of individual neural variability and show gender-related differences. C_LIO_LIBrain state transition patterns toward prefrontal and default-mode brain states predict differences on parental-report questionnaires scores. C_LIO_LIBrain state transitions may be crucial markers of individual differences in cognitive control development in preschoolers. C_LI

neuroscience↗