Work

Evaluating Alternative Correction Methods for Multiple Comparison in Functional Neuroimaging Research

Year: 2019

Type: article

Abstract: A significant challenge for fMRI research is statistically controlling for false positives without omitting true effects. Although a number of traditional methods for multiple comparison correction exist, several alternative tools have been developed that do not rely on strict parametric assumptions, but instead implement alternative methods to correct for multiple comparisons. In this study, we evaluated three of these methods, Statistical non-Parametric Mapping (SnPM), 3DClustSim, and Threshold Free Cluster Enhancement (TFCE), by examining which method produced the most consistent outcomes even when spatially-autocorrelated noise was added to the original images. We assessed the false alarm rate and hit rate of each method after noise was applied to the original images.

Source: Brain Sciences

DOI: 10.3390/brainsci9080198

Authors: Hyemin Han, Andrea Glenn, Kelsie J Dawson

Institution: University of Alabama

Language: English

Topic: Functional Brain Connectivity Studies

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,418