Injured Brains and Adaptive Networks: The Benefits and Costs of Hyperconnectivity

Abstract

A common finding in human functional brain imaging studies is that damage to neural systems paradoxically results in enhanced functional connectivity between network regions, a phenomenon commonly referred to as hyperconnectivity. We describe the various ways that hyperconnectivity operates to benefit a neural network following injury while simultaneously negotiating the trade-off between metabolic cost and communication efficiency. Hyperconnectivity may be optimally expressed by increasing connections through the most central and metabolically efficient regions (i.e., hubs). While adaptive in the short-term, we propose that chronic hyperconnectivity may leave network hubs vulnerable to secondary pathological processes over the life span due to chronically elevated metabolic stress. We conclude by offering novel, testable hypotheses for advancing our understanding of the role of hyperconnectivity in systems-level brain plasticity in neurological disorders. Trends: Brain imaging methods coupled with network neuroscience now permit previously unavailable opportunities to examine large-scale network changes after injury. One common response to neurological disruption of neural networks is increased brain connectivity between residual network regions, referred to as hyperconnectivity. Network hubs are centralized nodes in brain networks and are disproportionately represented as sites of pathology and may also play an important role in reintegration of function during recovery. There is converging evidence that increased brain metabolism, through local activity and increased network burden, is associated with neurodegeneration.