RT Journal Article
SR Electronic
T1 Genetic Influences on Cost-Efficient Organization of Human Cortical Functional Networks
JF The Journal of Neuroscience
JO J. Neurosci.
FD Society for Neuroscience
SP 3261
OP 3270
DO 10.1523/JNEUROSCI.4858-10.2011
VO 31
IS 9
A1 Alex Fornito
A1 Andrew Zalesky
A1 Danielle S. Bassett
A1 David Meunier
A1 Ian Ellison-Wright
A1 Murat Yücel
A1 Stephen J. Wood
A1 Karen Shaw
A1 Jennifer O'Connor
A1 Deborah Nertney
A1 Bryan J. Mowry
A1 Christos Pantelis
A1 Edward T. Bullmore
YR 2011
UL http://www.jneurosci.org/content/31/9/3261.abstract
AB The human cerebral cortex is a complex network of functionally specialized regions interconnected by axonal fibers, but the organizational principles underlying cortical connectivity remain unknown. Here, we report evidence that one such principle for functional cortical networks involves finding a balance between maximizing communication efficiency and minimizing connection cost, referred to as optimization of network cost-efficiency. We measured spontaneous fluctuations of the blood oxygenation level-dependent signal using functional magnetic resonance imaging in healthy monozygotic (16 pairs) and dizygotic (13 pairs) twins and characterized cost-efficient properties of brain network functional connectivity between 1041 distinct cortical regions. At the global network level, 60% of the interindividual variance in cost-efficiency of cortical functional networks was attributable to additive genetic effects. Regionally, significant genetic effects were observed throughout the cortex in a largely bilateral pattern, including bilateral posterior cingulate and medial prefrontal cortices, dorsolateral prefrontal and superior parietal cortices, and lateral temporal and inferomedial occipital regions. Genetic effects were stronger for cost-efficiency than for other metrics considered, and were more clearly significant in functional networks operating in the 0.09–0.18 Hz frequency interval than at higher or lower frequencies. These findings are consistent with the hypothesis that brain networks evolved to satisfy competitive selection criteria of maximizing efficiency and minimizing cost, and that optimization of network cost-efficiency represents an important principle for the brain's functional organization.