+ Site Statistics
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

Spontaneous eyelid closures link vigilance fluctuation with fMRI dynamic connectivity states



Spontaneous eyelid closures link vigilance fluctuation with fMRI dynamic connectivity states



Proceedings of the National Academy of Sciences of the United States of America 113(34): 9653-9658



Fluctuations in resting-state functional connectivity occur but their behavioral significance remains unclear, largely because correlating behavioral state with dynamic functional connectivity states (DCS) engages probes that disrupt the very behavioral state we seek to observe. Observing spontaneous eyelid closures following sleep deprivation permits nonintrusive arousal monitoring. During periods of low arousal dominated by eyelid closures, sliding-window correlation analysis uncovered a DCS associated with reduced within-network functional connectivity of default mode and dorsal/ventral attention networks, as well as reduced anticorrelation between these networks. Conversely, during periods when participants' eyelids were wide open, a second DCS was associated with less decoupling between the visual network and higher-order cognitive networks that included dorsal/ventral attention and default mode networks. In subcortical structures, eyelid closures were associated with increased connectivity between the striatum and thalamus with the ventral attention network, and greater anticorrelation with the dorsal attention network. When applied to task-based fMRI data, these two DCS predicted interindividual differences in frequency of behavioral lapsing and intraindividual temporal fluctuations in response speed. These findings with participants who underwent a night of total sleep deprivation were replicated in an independent dataset involving partially sleep-deprived participants. Fluctuations in functional connectivity thus appear to be clearly associated with changes in arousal.

Please choose payment method:






(PDF emailed within 0-6 h: $19.90)

Accession: 058892274

Download citation: RISBibTeXText

PMID: 27512040

DOI: 10.1073/pnas.1523980113


Related references

Principal States of Dynamic Functional Connectivity Reveal the Link Between Resting-State and Task-State Brain: An fMRI Study. International Journal of Neural Systems 28(7): 1850002, 2018

Estimating Dynamic Connectivity States in fMRI Using Regime-Switching Factor Models. IEEE Transactions on Medical Imaging 37(4): 1011-1023, 2018

Dimensionality reduction impedes the extraction of dynamic functional connectivity states from fMRI recordings of resting wakefulness. Journal of Neuroscience Methods 293: 151-161, 2018

Dynamic connectivity states estimated from resting fMRI Identify differences among Schizophrenia, bipolar disorder, and healthy control subjects. Frontiers in Human Neuroscience 8: 897, 2014

Dynamic connectivity detection: an algorithm for determining functional connectivity change points in fMRI data. Frontiers in Neuroscience 9: 285, 2015

The frequency dimension of fMRI dynamic connectivity: Network connectivity, functional hubs and integration in the resting brain. Neuroimage 121: 227-242, 2015

Direct comparison of spontaneous functional connectivity and effective connectivity measured by intracortical microstimulation: an fMRI study in macaque monkeys. Cerebral Cortex 21(10): 2348-2356, 2011

Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia. Neuroimage 180(Pt B): 619-631, 2018

Dynamic functional connectivity and its behavioral correlates beyond vigilance. Neuroimage 177: 1-10, 2018

The dynamic programming high-order Dynamic Bayesian Networks learning for identifying effective connectivity in human brain from fMRI. Journal of Neuroscience Methods 285: 33-44, 2017

Contrasting brain patterns of writing-related DTI parameters, fMRI connectivity, and DTI-fMRI connectivity correlations in children with and without dysgraphia or dyslexia. Neuroimage. Clinical 8: 408-421, 2015

Identifying effective connectivity parameters in simulated fMRI: a direct comparison of switching linear dynamic system, stochastic dynamic causal, and multivariate autoregressive models. Frontiers in Neuroscience 7: 70, 2013

Frequency-Resolved Dynamic Functional Connectivity Reveals Scale-Stable Features of Connectivity-States. Frontiers in Human Neuroscience 12: 253, 2018

Dynamic effective connectivity in resting state fMRI. Neuroimage 180(Pt B): 594-608, 2018

Functional Brain Connectivity Develops Rapidly Around Term Age and Changes Between Vigilance States in the Human Newborn. Cerebral Cortex 26(12): 4540-4550, 2016