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Difference between revisions of "Cognitive Regime Shift I - When the Brain Breaks/States and Stability in Human Functional Brain Networks"

From Complex Time
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|Pre-meeting notes=In 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:1. Functional network measures are well-suited to tracking slow, stable brain processes
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2. These measures can provide detailed images of individual differences
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3. Functional network effects can be complex, occurring at locations remote from primary pathology
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|Post-meeting notes=One discussion that emerged after the talk was the question of what the right level of analysis was for understanding brain dysfunction in aging and PD, and what form of causal argument or mechanism can be derived from these network descriptions of brain organization and dysfunction.A very interesting direction to go would be to create more theoretically driven models of brain dysfunction in PD, that might explain the disconnect between the functional network effects and known pathology in the disease. These models could then be tested in future experiments.
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|Presentation file=Gratton SFIBrainBreakDown2018 v1.pdf
 
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Revision as of 21:49, July 30, 2018

July 24, 2018
1:20 pm - 2:10 pm

Presenter

Caterina Gratton (Northwestern Univ.)

Abstract

In 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:1. Functional network measures are well-suited to tracking slow, stable brain processes 2. These measures can provide detailed images of individual differences 3. Functional network effects can be complex, occurring at locations remote from primary pathology

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