Region of interest analysis for fMRI.

By Russell A. Poldrack. Social Cognitive and Affective Neuroscience, 2007

866 citations recorded by the source corpus.

A common approach to the analysis of fMRI data involves the extraction of signal from specified regions of interest (or ROI's). Three approaches to ROI analysis are described, and the strengths and assumptions of each method are outlined.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/9e583802eeec570453931b7a25c3f0acfe0849a5

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In Cognitive Neuroscience

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Guidelines for reporting an fMRI study (2008, neutral): “Regions of interest (ROIs) may be used either to extract estimates of evoked signals or to limit corrections for multiple tests to a subset of all voxels (Poldrack, 2007).”
Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging (2018, methodology): “Model-Driven Analysis for Assessing Connectivity Among Regions or Seeds Brain functional connectivity analysis among a priori regions of interest (ROIs) or voxels (Poldrack, 2007) is the most widely applied model-driven method.”
The relation between statistical power and inference in fMRI (2017, background): “A widely advocated strategy for increasing the power of fMRI analyses is to rely on hypothesis-driven analyses that focus on specific aregions-of-interesto [71]).”
Best Practices in Data Analysis and Sharing in Neuroimaging using MRI (2016, background): “ROIs can be defined based on anatomy or previous literature [Poldrack2007], or based on functional results with great care and attention to circularity (see Extracted Data below).”
Theory of Mind and Empathic Explanations of Machiavellianism (2013, methodology): “Because the predictions were limited to specific anatomical regions based on the literature, we adopted a region-of-interest (ROI) approach (Poldrack, 2007) in order to test the significance of the activation.”
MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection (2015, neutral): “Automated segmentation of anatomical structures, i.e. delineation of regions of interest (ROIs), on MR images is an extremely important task for quantitative analysis of structural and functional brain changes, particularly in studies with large datasets (Good et al., 2002; Poldrack, 2007).”
A common allele in the oxytocin receptor gene (OXTR) impacts prosocial temperament and human hypothalamic-limbic structure and function (2010, methodology): “Following standard practice in neuroimaging (93), we used a strongly hypothesis-driven ROI to investigate genotype-dependent alteration in the limbic circuitry, i.”