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Early Maturation of Functional Connectivity within Dorsal Brain Networks
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Introduction:
Prior visual neuroscience research has contributed ample evidence on functional anatomy of two long-range systemic visual networks, dorsal (DVN) and ventral (VVN). Their developmental course of functional connectivity was rarely studied.
Methods:
We examined within- and between-network connectivity using cortical periodic alpha band 8–13 Hz, a well-elaborated developmental marker of cognitive inhibitory control. Resting state magnetoencephalography (rsMEG) investigated age differences in functional network connectivity between carefully screened male participants: younger group (YG, 6:10–12 years) and older group (OG, 18:7–29 years). The morphology of cortical network nodes was informed
a priori
by pilot resting state functional magnetic resonance imaging (rsfMRI) and MRI morphometry studies. Phase Lag Index was employed to compute within- and between-network connectivity. We summarized the age differences in connectivity using graph theory metrics.
Results:
The power spectral density across cortical areas was comparable between YG and OG, indicating similar signal-to-noise ratios across the age groups. The dorsal brain in YG showed higher within-network connectivity for the inferior parietal/occipital (DVN) and medial posterior nodes (cingulate/precuneus) of the default mode network (DMN), functionally/anatomically linked to DVN. A significantly reduced anterior brain connectivity for VVN in YG suggested its protracted maturation. The topography of alpha connectivity between age groups displayed no statistically significant differences in the
posterior dorsal nodes
of DVN/DMN but significantly lower connectivity in
the anterior
dorsal/medial cortex
in YG as compared with OG
.
Discussion:
The current rsMEG finding on intrinsic alpha-band oscillatory connectivity in
child participants
is consistent with prior neuroimaging evidence in humans and primates securing an early maturational course of posterior dorsal brain networks.
Title: Early Maturation of Functional Connectivity within Dorsal Brain Networks
Description:
Introduction:
Prior visual neuroscience research has contributed ample evidence on functional anatomy of two long-range systemic visual networks, dorsal (DVN) and ventral (VVN).
Their developmental course of functional connectivity was rarely studied.
Methods:
We examined within- and between-network connectivity using cortical periodic alpha band 8–13 Hz, a well-elaborated developmental marker of cognitive inhibitory control.
Resting state magnetoencephalography (rsMEG) investigated age differences in functional network connectivity between carefully screened male participants: younger group (YG, 6:10–12 years) and older group (OG, 18:7–29 years).
The morphology of cortical network nodes was informed
a priori
by pilot resting state functional magnetic resonance imaging (rsfMRI) and MRI morphometry studies.
Phase Lag Index was employed to compute within- and between-network connectivity.
We summarized the age differences in connectivity using graph theory metrics.
Results:
The power spectral density across cortical areas was comparable between YG and OG, indicating similar signal-to-noise ratios across the age groups.
The dorsal brain in YG showed higher within-network connectivity for the inferior parietal/occipital (DVN) and medial posterior nodes (cingulate/precuneus) of the default mode network (DMN), functionally/anatomically linked to DVN.
A significantly reduced anterior brain connectivity for VVN in YG suggested its protracted maturation.
The topography of alpha connectivity between age groups displayed no statistically significant differences in the
posterior dorsal nodes
of DVN/DMN but significantly lower connectivity in
the anterior
dorsal/medial cortex
in YG as compared with OG
.
Discussion:
The current rsMEG finding on intrinsic alpha-band oscillatory connectivity in
child participants
is consistent with prior neuroimaging evidence in humans and primates securing an early maturational course of posterior dorsal brain networks.
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