Tandi, J. | Search bioRxiv

bioRxiv2019

Cognitive vulnerability to sleep deprivation is robustly associated with two dynamic connectivity states

Robustly linking dynamic functional connectivity (DFC) states to behaviour is an important goal of the fledgling research using these methods. Previously, using a sliding window approach, we identified two dynamic connectivity states (DCS) linked to arousal. Here, in an independent dataset, 32 healthy participants underwent two sets of resting-state functional magnetic resonance imaging (fMRI) scans, once in a well-rested state and once after a single night of total sleep deprivation. Using a temporal differencing method, DFC and clustering analysis on the resting state fMRI data revealed five centroids that were highly correlated with those found in previous work, including the two states associated with high and low arousal. Individual differences in cognitive vulnerability to sleep deprivation were measured using changes in Psychomotor Vigilance Test (PVT) performance (lapses and median reaction speed), Changes in the percentage of time spent in the arousal states from the well-rested to the sleep-deprived condition specifically were correlated with declines in PVT performance. Our results provide good evidence of the validity and reproducibility of DFC measures, particularly with regard to measuring arousal and attention, and are an encouraging base from which to build a chronnectome mapping DCS to cognition.

neuroscience↗

bioRxiv2018

Dynamic functional connectivity markers of objective trait mindfulness

While mindfulness is commonly viewed as a skill to be cultivated through practice, untrained individuals can also vary widely in dispositional mindfulness. Prior research has identified static neural connectivity correlates of this trait. Here, we use dynamic functional connectivity (DFC) analysis of resting-state fMRI to study time-varying connectivity patterns associated with naturally varying and objectively measured trait mindfulness. Participants were selected from the top and bottom tertiles of performers on a breath-counting task to form high trait mindfulness (HTM; N = 21) and low trait mindfulness (LTM; N = 18) groups. DFC analysis of resting state fMRI data revealed that the HTM group spent significantly more time in a brain state associated with task-readiness - a state characterized by high within-network connectivity and greater anti-correlations between task-positive networks and the default-mode network (DMN). The HTM group transitioned between brain states more frequently, but the dwell time in each episode of the task-ready state was equivalent between groups. These results persisted even after controlling for vigilance. Across individuals, certain connectivity metrics were weakly correlated with self-reported mindfulness as measured by the Five Facet Mindfulness Questionnaire, though these did not survive multiple comparisons correction. In the static connectivity maps, HTM individuals had greater within-network connectivity in the DMN and the salience network, and greater anti-correlations between the DMN and task-positive networks. In sum, DFC features robustly distinguish HTM and LTM individuals, and may be useful biological markers for the measurement of dispositional mindfulness.

neuroscience↗