4.8 Article

Cognitive fitness of cost-efficient brain functional networks

Publisher

NATL ACAD SCIENCES
DOI: 10.1073/pnas.0903641106

Keywords

efficiency; graph theory; schizophrenia; working memory; magnetoencephalography

Funding

  1. National Institute of Biomedical Imaging and Bioengineering and the National Institute of Mental Health (NIMH)
  2. Intramural Research Program of the National Institutes of Health (NIH)
  3. Medical Research Council
  4. Medical Research Council [G0001354, G0001354B] Funding Source: researchfish

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The human brain's capacity for cognitive function is thought to depend on coordinated activity in sparsely connected, complex networks organized over many scales of space and time. Recent work has demonstrated that human brain networks constructed from neuroimaging data have economical small-world properties that confer high efficiency of information processing at relatively low connection cost. However, it has been unclear how the architecture of complex brain networks functioning at different frequencies can be related to behavioral performance on cognitive tasks. Here, we show that impaired accuracy of working memory could be related to suboptimal cost efficiency of brain functional networks operating in the classical beta frequency band, 15-30 Hz. We analyzed brain functional networks derived from magnetoencephalography data recorded during working-memory task performance in 29 healthy volunteers and 28 people with schizophrenia. Networks functioning at higher frequencies had greater global cost efficiency than low-frequency networks in both groups. Superior task performance was positively correlated with global cost efficiency of the beta-band network and specifically with cost efficiency of nodes in left lateral parietal and frontal areas. These results are consistent with biophysical models highlighting the importance of beta-band oscillations for long-distance functional connections in brain networks and with pathophysiological models of schizophrenia as a dysconnection syndrome. More generally, they echo the saying that less is more'': The information processing performance of a network can be enhanced by a sparse or low-cost configuration with disproportionately high efficiency.

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