The Functional Architecture of the Infant Brain as Revealed by Resting-State fMRI

Fransson, Peter; Ådén, Ulrika; Blennow, Mats; Lagercrantz, Hugo

doi:10.1093/cercor/bhq071

Cited by 478 publications

(406 citation statements)

References 66 publications

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“…Functional hubs were found to be predominantly confined to brain regions supporting primary functions (e.g. sensorimotor and visual cortex) and only a few hubs have been observed in association cortices including the insula and posterior cingulate cortex (De Asis-Cruz et al, 2015;Fransson et al, 2011;Gao et al, 2011). Notably, the configuration of functional brain hubs as observed in the neonatal brain is highly consistent with the outline of resting state networks during this period.…”

Section: Functional Connectomementioning

confidence: 67%

“…A number of reports described functional network architecture in neonates on a whole-brain level (De Asis-Cruz et al, 2015;Fransson et al, 2011;Gao et al, 2011). In line with network attributes of the neonatal structural connectome and adult human brain organization, functional brain networks in newborn infants exhibit small-world topology, a modular organization and a heavy-tailed degree distribution with functional hubs (Box 1).…”

Section: Functional Connectomementioning

confidence: 99%

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The emergence of functional architecture during early brain development

2017

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Early human brain development constitutes a sequence of intricate processes resulting in the ontogeny of functionally operative neural circuits. Developmental trajectories of early brain network formation are genetically programmed and can be modified by epigenetic and environmental influences. Such alterations may exert profound effects on neurodevelopment, potentially persisting throughout the lifespan. This review focuses on the critical period of fetal and early postnatal brain development. Here we collate findings from neuroimaging studies, with a particular focus on functional MRI research that interrogated early brain network development in both health and high-risk or disease states. First, we will provide an overview of the developmental processes that take place from the embryonic period through early infancy in order to contextualize brain network formation. Second, functional brain network development in the typically developing brain will be discussed. Third, we will touch on prenatal and perinatal risk factors that may interfere with the trajectories of functional brain wiring, including prenatal substance exposure, maternal mental illness and preterm

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Section: Functional Connectomementioning

confidence: 67%

Section: Functional Connectomementioning

confidence: 99%

The emergence of functional architecture during early brain development

2017

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“…(e.g. Dudink et al, 2012;Fransson et al, 2011;Lodygensky et al, 2010). The next obvious advance will be to define the functional correlate of any altered structure, and this can only be accomplished with improved spatial EEG information.…”

Section: Discussionmentioning

confidence: 99%

“…Recent work in neuroimaging (Dudink et al, 2012;Fransson et al, 2011;Lodygensky et al, 2010) and in developmental neurobiology (Colonnese and Khazipov, 2012;Hanganu-Opatz, 2010;Vanhatalo and Kaila, 2010) has made it clear that brain functions are already highly specialized early in development. Functional assessment of neonatal brain activity is currently severely hampered by the poor spatial resolution provided by conventional neonatal EEG recording (Andre et al, 2010), which hardly suffices to distinguish brain lobes from each other.…”

Section: Introductionmentioning

confidence: 99%

Spatial patterning of the neonatal EEG suggests a need for a high number of electrodes

et al. 2013

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TitleSpatial patterning of the neonatal EEG suggests a need for a high number of electrodes There is an increasing demand for source analysis of neonatal EEG, but currently there is inadequate knowledge about i) the spatial patterning of neonatal scalp EEG and hence ii) the number of electrodes needed to capture neonatal EEG in full spatial detail. This study addresses these issues by using a very high density (2.5 mm interelectrode spacing) linear electrode array to assess the spatial power spectrum, by using a high density (64 electrodes) EEG cap to assess the spatial extent of the common oscillatory bouts in the neonatal EEG and by using a neonatal size spherical head model to assess the effects of source depth and skull conductivities on the spatial frequency spectrum. The linear array recordings show that the spatial power spectrum decays rapidly until about 0.5-0.8 cycles per centimeter. The dense array EEG recordings show that the amplitude of oscillatory events decays within 4-6 cm to the level of global background activity, and that the higher frequencies (12)(13)(14)(15)(16)(17)(18)(19)(20) show the most rapid spatial decline in amplitude. Simulation with spherical head model showed that realistic variation in skull conductivity and source depths can both introduce orders of magnitude difference in the spatial frequency of the scalp EEG. Calculation of spatial Nyquist frequencies from the spatial power spectra suggests that an interelectrode distance of about 6-10 mm would suffice to capture the full spatial texture of the raw EEG signal at the neonatal scalp without spatial aliasing or under-sampling. The spatial decay of oscillatory events suggests that a full representation of their spatial characteristics requires an interelectrode distance of 10-20 mm. The findings show that the conventional way of recording neonatal EEG with about 10 electrodes ignores most spatial EEG content, that increasing the electrode density is necessary to improve neonatal EEG source localization and information extraction, and that prospective source models will need to carefully consider the neonatally relevant ranges of tissue conductivities and source depths when source localizing cortical activity in neonates.

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“…Many other studies have looked at functional network development in young infants [19,20,22,56]. Fransson et al, in particular, examined the resting-state functional network architecture of very young preterm infants (25 weeks mean gestational age) and found that only half of the number of resting-state sub-networks found in healthy adults were present at the preterm stage [20].…”

Section: Introductionmentioning

confidence: 99%

Structural network analysis of brain development in young preterm neonates

et al. 2014

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Preterm infants develop differently than those born at term and are at higher risk of brain pathology. Thus, an understanding of their development is of particular importance. Diffusion tensor imaging (DTI) of preterm infants offers a window into brain development at a very early age, an age at which that development is not yet fully understood. Recent works have used DTI to analyze structural connectome of the brain scans using network analysis. These studies have shown that, even from infancy, the brain exhibits small-world properties. Here we examine a cohort of 47 normal preterm neonates (i.e., without brain injury and with normal neurodevelopment at 18 months of age) scanned between 27 and 45 weeks post-menstrual age to further the understanding of how the structural connectome develops. We use fullbrain tractography to find white matter tracts between the 90 cortical and sub-cortical regions defined in the University of North Carolina Chapel Hill neonatal atlas. We then analyze the resulting connectomes and explore the differences between weighting edges by tract count versus fractional anisotropy. We observe that the brain networks in preterm infants, much like infants born at term, show high efficiency and clustering measures across a range of network scales. Further, the development of many individual region-pair connections, particularly in the frontal and occipital lobes, is significantly correlated with age. Finally, we observe that the preterm infant connectome remains highly efficient yet becomes more clustered across this age range, leading to a significant increase in its small-world structure.

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The Functional Architecture of the Infant Brain as Revealed by Resting-State fMRI

Cited by 478 publications

References 66 publications

The emergence of functional architecture during early brain development

The emergence of functional architecture during early brain development

Spatial patterning of the neonatal EEG suggests a need for a high number of electrodes

Structural network analysis of brain development in young preterm neonates

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