Functional connectivity in the developing brain: A longitudinal study from 4 to 9months of age

Abstract

We characterize the development of intrinsic connectivity networks (ICNs) from 4 to 9 months of age with resting state magnetic resonance imaging performed on sleeping infants without sedative medication. Data is analyzed with independent component analysis (ICA). Using both low (30 components) and high (100 components) ICA model order decompositions, we find that the functional network connectivity (FNC) map is largely similar at both 4 and 9 months. However at 9 months the connectivity strength decreases within local networks and increases between more distant networks. The connectivity within the default-mode network, which contains both local and more distant nodes, also increases in strength with age. The low frequency power spectrum increases with age only in the posterior cingulate cortex and posterior default mode network. These findings are consistent with a general developmental pattern of increasing longer distance functional connectivity over the first year of life and raise questions regarding the developmental importance of the posterior cingulate at this age.

Classification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivity

“…Among these dynamic states, several similar states were found in the previous studies. For example, similar dynamic states as states 1, 3 and 5 were found in (Allen et al, 2013; Damaraju et al, 2014). …”

“…Several previous studies have shown that schizophrenia and bipolar patients can be discriminated at group-level by using the information on dysfunctional integration of the brain (Allen et al, 2012; Arbabshirani et al, 2013a; Damaraju et al, 2014; Friston, 2002b; Rashid et al, 2014). We hypothesized that disrupted functional integration in schizophrenia and bipolar patients as captured by FNC analysis reveal powerful information for automatic discriminative analysis at subject-level.…”

“…We hypothesized that disrupted functional integration in schizophrenia and bipolar patients as captured by FNC analysis reveal powerful information for automatic discriminative analysis at subject-level. We expected some connectivity measures to be better captured in a static model and others in a dynamic model (Damaraju et al, 2014). Static FNC provides information about the overall mean connectivity and may be more optimal for connectivity that is persistent across the entire experiment than a dynamic FNC approach.…”

Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature

“…In neonates and very young infants, these individual compartments demonstrate locally correlated activity, but fail to synchronize into a coherent network (Damaraju et al, 2014; Fransson et al, 2007; Gao et al, 2009; Smyser et al, 2010; Wylie et al, 2014). Over the course of the first two years of life, these regions undergo a precise evolution to gradually bring the network ‘online’ (Damaraju et al, 2014; Gao et al, 2013; Gao et al, 2009). By two years of age, the network bears adult-like qualities, although coupling between distant anterior and posterior nodes of the network remain relatively low.…”

Brain functional network connectivity development in very preterm infants: The first six months

“…Resting-state networks (RSNs) correspond to the brain's functional architecture during task-based fMRI studies [8][9][10][11]. Attributed to its intrinsic characteristic of minimum/no demands for subject participation, rsfMRI is recognized as an ideal tool for investigating the brain's functional maturation and neurodevelopment in infancy [12][13][14][15][16][17][18][19][20][21][22][23][24].…”