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It could be argued that the brain is the prototypical complex system: in humans approximately 86 billion nerve cells are coordinated into tens of cortical regions to ensure that information from sensation and perception is utilized in a repertoire of adaptive behaviors. And just as the information processing principles that allow a large decentralized system to function presents many new scientific challenges, so does the unique way in which the brain fails, either through normal aging or through the vastly accelerated loss of function associated with neurodegenerative disease. This meeting sought to employ insights of complexity science as they pertain to system collapse and system robustness to new emerging data accumulated by neurocognitive researchers. Of particular interest to the group was the question of network failure, or cascading failure. These describe the accelerating loss of modules, units, and cells associated with the reduction or sparsification in network connectivity observed in a range of diseases from Alzheimer’s through to prion diseases. The group focused on new and potential data sets and questions related to their optimal spatio-temporal resolution as well as new insights from nonlinear dynamics to include the statistical physics of networks and the stability of analogous ecological networks applied to clinical and psychological observation. Throughout discussion much emphasis was placed on the discovery of the appropriate levels for causal explanation. Candidate levels included the genetic level, protein aggregations within a single nerve cells, local neural circuits, and large-scale cortical fields. At each level there exists data associated with neuro- degenerative phenotypes. <br><br>At this point it is not clear what is purely correlational versus what could be said to be truly causal. In the absence of novel experimental procedures or realistic computer simulations the field is dominated by correlational studies and descriptions. Evidence from the loss of key brain function under anesthetic provided correlational evidence for critical regions and possibly pathways that might recapitulate the loss of conscious states of awareness during senescence. The loss of coherent correlations in phase among distant cortical regions in the resting state are reported to be correlated with the loss of key cognitive capacities in a variety of stressful circumstances, including sustained poverty. Evidence from the comparative analysis of cortical fields in nonhuman vertebrates suggests significant variability in those pathways required to ensure continued cognitive function over a lifespan. In many cases where data can be obtained there is evidence for the statistics of neural avalanches or power-law like behavior in the distribution of brain activity, suggesting that deviations from baseline power-law distributions might be profitably used as a diagnostic tool in establishing the effective state of health of the nervous system. At this point the group feels the need for a systematic summary of the key insights of network science as they pertain to network collapse, combined with a deliberative effort to map the requirements of these models onto available data-sets at different levels of organization to include the genetic, neural, neural circuit, and cortical field. <br><br>It was widely agreed that there is value to the community of aging and brain disease researchers to becoming more familiar with techniques that are a good fit to the essential characteristics of the system that they are working with. The group intends to spawn a small number of distinct groups each of which will pursue particular neurodegenerative diseases using a variety of new techniques.
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This can be partially based on the WSWG proposal you originally submitted but should reflect how the meeting actually went; include any notable feedback you received from participants; please also note what worked well and what could have been improved.
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e.g., in particular, any piece written for the SFI Update—contact John German for text
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