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that interlink multiple clusters consistently have the most widespread effects,
while lesions effects of more local hubs or non-hub regions are spatially more
restricted.
Lesions are only one way in which brain networks may become damaged.
Another way involves disruptions of connection patterns that occur in the course
of a disease process or of degeneration. In the near future, we may expect to see
systematic comparisons between connection patterns obtained from clinical
populations to those of normal subjects. Diffusion imaging approaches may
prove especially useful. When appropriately applied in a clinical context
(Johansen-Berg and Behrens, 2006), these approaches can provide important
connectional information in vivo that may reveal novel associations between
network disturbances and brain pathologies. To date, numerous studies of both
structural and functional brain connectivity suggest that changes in brain
connectivity patterns are associated with mental disorders and brain trauma.
Functional imaging has revealed differences in the organization of functional
connectivity between normal subjects and patients with Alzheimer's disease
(Stam et al ., 2007) and schizophrenia (Bluhm et al ., 2007; Garrity et al ., 2007).
In the case of schizophrenia, there is some evidence that the disorder is
associated with disorganized cortical white matter (Shergill et al ., 2007),
supporting the hypothesis that schizophrenia involves cortical disconnection
(Friston and Frith, 1995). Future mapping studies of structural connections
across the entire cerebral cortex will allow a more detailed characterization of
pathological changes affecting brain networks, providing mechanistic links
between “network disease” and cognitive or behavioral disturbances. Recovery
from a disease state, or from traumatic brain injury, may then be guided by a
better understanding of how structural changes affect functional interactions
among brain regions.
9.5. Conclusion
Neuroscience stands to gain significant new insights from the systematic
application of network approaches across different time and spatial scales. As
this brief overview has illustrated, there is rapid progress in mapping structural
and functional connections across the brain and emerging new insights into how
structural couplings in the brain shape its ongoing dynamics.
An increased understanding and more refined mapping of brain connectivity
raises the interesting prospect of large-scale realistic computational models of the
human brain. If such models could be designed at a level of scale commensurate
with that used in functional neuroimaging they would form important predictive
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