articleNeuroImageMar 14, 2017HYBRID OA

Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity

University of Pennsylvania · Cornell University · +2 more institutions

PubMed
Indexed incrossrefdoajpubmed

Abstract

Since initial reports regarding the impact of motion artifact on measures of functional connectivity, there has been a proliferation of participant-level confound regression methods to limit its impact. However, many of the most commonly used techniques have not been systematically evaluated using a broad range of outcome measures. Here, we provide a systematic evaluation of 14 participant-level confound regression methods in 393 youths. Specifically, we compare methods according to four benchmarks, including the residual relationship between motion and connectivity, distance-dependent effects of motion on connectivity, network identifiability, and additional degrees of freedom lost in confound regression. Our…

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1,148
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FWCI
58.50
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100%
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Authors

14

Topics & keywords

Keywords
  • Artifact (error)
  • Regression
  • Context (archaeology)
  • Computer science
  • Artificial intelligence
  • Regression analysis
  • Residual
  • Censoring (clinical trials)
UN Sustainable Development Goals
  • Peace, Justice and strong institutions
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