A brain-age model for preterm infants based on functional connectivity.
Physiol Meas
; 39(4): 044006, 2018 04 26.
Article
in En
| MEDLINE
| ID: mdl-29596059
ABSTRACT
OBJECTIVE:
In this study, the development of EEG functional connectivity during early development has been investigated in order to provide a predictive age model for premature infants.APPROACH:
The functional connectivity has been assessed via the coherency function (its imaginary part (ImCoh) and its mean squared magnitude (MSC)), the phase locking value ([Formula see text]) and the Hilbert-Schimdt dependence (HSD) in a dataset of 30 patients, partially described and employed in previous studies (Koolen et al 2016 Neuroscience 322 298-307; Lavanga et al 2017 Complexity 2017 1-13). Infants' post-menstrual age (PMA) ranges from 27 to 42 weeks. The topology of the EEG couplings has been investigated via graph-theory indices. MAINRESULTS:
Results show a sharp decrease in ImCoh indices in θ, (4-8) Hz and α, (8-16) Hz bands and MSC in ß, (16-32) Hz band with maturation, while a more modest positive correlation with PMA is found for HSD, [Formula see text] and MSC in [Formula see text], θ, α bands. The best performances for the PMA prediction were mean absolute error equal to 1.51 weeks and adjusted coefficient of determination [Formula see text] equal to 0.8.SIGNIFICANCE:
The reported findings suggest a segregation of the cortex connectivity, which favours a diffused tasks architecture on the brain scalp. In summary, the results indicate that the neonates' brain development can be described via lagged-interaction network features.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Brain
/
Aging
/
Infant, Premature
/
Models, Neurological
/
Nerve Net
Type of study:
Prognostic_studies
Limits:
Humans
/
Infant
Language:
En
Journal:
Physiol Meas
Journal subject:
BIOFISICA
/
ENGENHARIA BIOMEDICA
/
FISIOLOGIA
Year:
2018
Document type:
Article
Affiliation country: