Infant functional networks are modulated by state of consciousness and circadian rhythm

Abstract

Functional connectivity networks are valuable tools for studying development, cognition, and disease in the infant brain. In adults, such networks are modulated by the state of consciousness and the circadian rhythm; however, it is unknown if infant brain networks exhibit similar variation, given the unique temporal properties of infant sleep and circadian patterning. To address this, we analyzed functional connectivity networks calculated from long-term EEG recordings (average duration 20.8 hours) from 19 healthy infants. Networks were subjectspecific, as inter-subject correlations between weighted adjacency matrices were low. However, within individual subjects, both sleep and wake networks were stable over time, with stronger functional connectivity during sleep than wakefulness. Principal component analysis revealed the presence of two dominant networks; visual sleep scoring confirmed that these corresponded to sleep and wakefulness. Lastly, we found that network strength, degree, clustering coefficient, and path length significantly varied with time of day, when measured in either wakefulness or sleep at the group level. Together, these results suggest that modulation of healthy functional networks occurs over ~24 hours and is robust and repeatable. Accounting for such temporal periodicities may improve the physiological interpretation and use of functional connectivity analysis to investigate brain function in health and disease.

EEG biomarkers for the diagnosis and treatment of infantile spasms

“…In multiple studies, children with IS exhibited stronger cross-correlation FCNs compared with healthy controls ( 41 , 45 , 46 ). This held true when the FCNs were measured in both wakefulness and sleep; however, FCNs measured during sleep had stronger connections than those measured during wakefulness, for both children with IS and healthy controls ( 41 , 63 ). These cross-correlation networks were found to be individualized, rather than stereotyped within a subject group, ( 64 ), and they had high test-retest reliability, with stable networks produced from as little as 150 s of EEG data ( 45 , 46 , 63 ).…”

Dopaminergic Modulation of Local Non-oscillatory Activity and Global-Network Properties in Parkinson’s Disease: An EEG Study

“…We estimated the brain network metrics based on the scalp sensor-based EEG connectivity matrix. Although often performed in source space, due to a small number of channels (Lantz et al, 2003) we did it rather in sensor space similar to previous studies (Stam et al, 2007;Zeng et al, 2015;Chai et al, 2019;Sun et al, 2019;Mitsis et al, 2020;Smith et al, 2021). In the discussion, we mention and discuss limitations associated with the estimation of graph metrics in sensor space.…”

Dopaminergic modulation of local non-oscillatory activity and global-network properties in Parkinson’s disease: an EEG study

“…We estimated the brain network metrics based on the scalp sensor-based EEG connectivity matrix. Although often performed in source space, due to a small number of channels (Lantz et al, 2003) we did it rather in sensor space similar to previous studies (Chai et al, 2019;Mitsis et al, 2020;Smith et al, 2021;Stam et al, 2007;Sun et al, 7 2019; Zeng et al, 2015). In the discussion, we mention and discuss limitations associated with the estimation of graph metrics in sensor space.…”