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COMPLEX TIME: Adaptation, Aging, & Arrow of Time

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A list of all pages that have property "Pre-meeting notes" with value "In my talk, I went over two main empirical studies. In the first, we used a dataset that highly-sampled 10 inspanidual subjects, across different days and tasks. We asked how functional brain networks vary over different timescales, and found that these network measurements are primarily stable, with only moderate/minor state-based effects. In the second experiment, we looked at how Parkinson’s disease affect functional brain networks. We found that PD selectively impacts blocks of network-to-network connections, remote from primary pathophysiology. I also described initial findings from a recent initiative into how we might characterize inspanidual variation in brain networks, showing that inspanidual network “variants” are stable and systematic. From these findings, I concluded: # Functional network measures are well-suited to tracking slow, stable brain processes # These measures can provide detailed images of inspanidual differences # Functional network effects can be complex, occurring at locations remote from primary pathology". Since there have been only a few results, also nearby values are displayed.

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    • Cognitive Regime Shift I - When the Brain Breaks/States and Stability in Human Functional Brain Networks  + (In my talk, I went over two main empiricalIn my talk, I went over two main empirical studies. In the first, we used a dataset that highly-sampled 10 individual subjects, across different days and tasks. We asked how functional brain networks vary over different timescales, and found that these network measurements are primarily stable, with only moderate/minor state-based effects. In the second experiment, we looked at how Parkinson’s disease affect functional brain networks. We found that PD selectively impacts blocks of network-to-network connections, remote from primary pathophysiology. I also described initial findings from a recent initiative into how we might characterize individual variation in brain networks, showing that individual network “variants” are stable and systematic. From these findings, I concluded:</br># Functional network measures are well-suited to tracking slow, stable brain processes</br># These measures can provide detailed images of individual differences</br># Functional network effects can be complex, occurring at locations remote from primary pathologyat locations remote from primary pathology)