  Since initial reports regarding the impact of motion artifact on measures of
functional connectivity, there has been a proliferation of confound regression
methods to limit its impact. However, recent techniques have not been
systematically evaluated using consistent outcome measures. Here, we provide a
systematic evaluation of 12 commonly used confound regression methods in 193
young adults. Specifically, we compare methods according to three benchmarks,
including the residual relationship between motion and connectivity,
distance-dependent effects of motion on connectivity, and additional degrees of
freedom lost in confound regression. Our results delineate two clear trade-offs
among methods. First, methods that include global signal regression minimize
the relationship between connectivity and motion, but unmask distance-dependent
artifact. In contrast, censoring methods mitigate both motion artifact and
distance-dependence, but use additional degrees of freedom. Taken together,
these results emphasize the heterogeneous efficacy of proposed methods, and
suggest that different confound regression strategies may be appropriate in the
context of specific scientific goals.
