The researchers created growth charts that reflected the configuration of what are called intrinsic connectivity networks — important units of
functional brain organization.
«These technology - inspired neuroscientific investigations, using advanced signal processing methods, push the frontier on what we know about
functional brain organization and the mind.»
Not exact matches
The results of the study are also of interest to researchers working in the field, as Professor Brandt explains: «The results illustrate the very specific
functional organization of our
brains.
From these
functional brain networks, a number of key characteristics that describe the overall
organization of a network were computed, including the clustering coefficient C and characteristic path length L (Watts and Strogatz, 1998).
Neuroimaging studies have linked intelligence to the developmental course of specific high - order
brain regions (Shaw et al., 2006), total
brain volume and focal
brain structure (Thompson et al., 2001; Haier et al., 2004; Colom et al., 2006; Hulshoff Pol et al., 2006; Choi et al., 2008), microstructural
organization of white matter (Chiang et al., 2009), and the
functional dynamics of specific high cognitive
brain regions (Duncan et al., 2000; Gray et al., 2003; Choi et al., 2008; Song et al., 2008).
The
functional brain networks showed a clear small - world
organization, expressed by λ ≈ 1 (c) and γ ≫ 1 (d) for T ≥ 0.3 (1 - sample t test, df = 18, all p < α of 0.01, Bonferroni corrected for multiple comparisons of T).
The
organization of the
functional brain network was examined using graph theory (Achard et al., 2006; Stam and Reijneveld, 2007; Bullmore and Sporns, 2009), as validated earlier (van den Heuvel et al., 2008b)(supplemental material, available at www.jneurosci.org).
The
functional brain networks showed a clear small - world
organization for 0.3 ≤ T ≤ 0.5 (Fig. 1a — d), expressed by L ≈ Lrandom and λ ≈ 1 for T ≤ 0.5 and C ≫ Crandom and γ ≫ 1 for T ≥ 0.3 (one - sample t test, all p < α of 0.01, Bonferroni corrected for multiple comparisons of T, df = 18), indicating a small - world
organization (Sporns et al., 2004; Stam, 2004; Achard et al., 2006; van den Heuvel et al., 2008b).
Small - world and scale - free
organization of voxel based resting - state
functional connectivity in the human
brain
Therefore future studies are needed to examine whether common genes mediate the association between
functional and structural
brain network
organization and intelligence.
Such an efficient
organization of our
brain network raises the question of a possible relationship between how efficiently the
functional connections of our
brain are placed and individual differences in intelligence.
Our data reflects the level of efficient
organization of the
functional brain network during a resting state and not the efficiency of
functional connectivity between
brain regions during the performance of specific cognitive tasks that enter into the IQ score.
Recently,
functional network connectivity (FNC, defined as the temporal correlation among spatially distant
brain networks) has been used to examine the
functional organization of
brain networks in
It investigates the human
brain, from the
functional organization of large scale cerebral systems to microscopic neurochemical processes.
Altered
functional and structural
brain network
organization in autism.
Our study provides new evidence that there is disrupted
organization of
functional brain networks in AD.
Small - world metrics can characterize the
functional organization of the
brain in AD, and our findings further suggest that these network measures may be useful as an imaging - based biomarker to distinguish AD from healthy aging.
Here we assess
functional brain network
organization of 23 of the world's most successful memory athletes and matched controls with fMRI during both task - free resting state baseline and active memory encoding.
Therefore, when
functional brain networks are constructed at the voxel - level, a resolution similar to ICA, a network based approach offers distinct advantages over ICA in understanding the overall
organization of the
brain network.
Using a similar logic, we first tested our hypothetical topographic model of the
functional - anatomic
organization of
brain networks subserving social cognition (Fig. 1).
Such a progressive influence may suggest that the fluctuation of maternal depression has a long - term impact on the development of the
brain functional organization in later life.
Therefore, over the time of the
brain development, our observations supported growing evidence that the
organization of the
brain's
functional network might be parallel to the behavioral development, even in early postnatal life.