The efficiency of fMRI region of interest analysis methods for detecting group differences

•Transformation into standard space affected structural and functional analysis results and group difference determinations.•Surface-based analyses using functional ROIs yielded the most group differences.•Native-space volumetric analyses generated significant group differences and would be appropri...

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Published in:Journal of neuroscience methods Vol. 226; pp. 57 - 65
Main Authors: Hutchison, Joanna L., Hubbard, Nicholas A., Brigante, Ryan M., Turner, Monroe, Sandoval, Traci I., Hillis, G. Andrew J., Weaver, Travis, Rypma, Bart
Format: Journal Article
Language:English
Published: Netherlands Elsevier B.V 15-04-2014
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Abstract •Transformation into standard space affected structural and functional analysis results and group difference determinations.•Surface-based analyses using functional ROIs yielded the most group differences.•Native-space volumetric analyses generated significant group differences and would be appropriate when time is limited. Using a standard space brain template is an efficient way of determining region-of-interest (ROI) boundaries for functional magnetic resonance imaging (fMRI) data analyses. However, ROIs based on landmarks on subject-specific (i.e., native space) brain surfaces are anatomically accurate and probably best reflect the regional blood oxygen level dependent (BOLD) response for the individual. Unfortunately, accurate native space ROIs are often time-intensive to delineate even when using automated methods. We compared analyses of group differences when using standard versus native space ROIs using both volume and surface-based analyses. Collegiate and military-veteran participants completed a button press task and a digit-symbol verification task during fMRI acquisition. Data were analyzed within ROIs representing left and right motor and prefrontal cortices, in native and standard space. Volume and surface-based analysis results were also compared using both functional (i.e., percent signal change) and structural (i.e., voxel or node count) approaches. Results suggest that transformation into standard space can affect the outcome of structural and functional analyses (inflating/minimizing differences, based on cortical geography), and these transformations can affect conclusions regarding group differences with volumetric data. Caution is advised when applying standard space ROIs to volumetric fMRI data. However, volumetric analyses show group differences and are appropriate in circumstances when time is limited. Surface-based analyses using functional ROIs generated the greatest group differences and were less susceptible to differences between native and standard space. We conclude that surface-based analyses are preferable with adequate time and computing resources.
AbstractList Using a standard space brain template is an efficient way of determining region-of-interest (ROI) boundaries for functional magnetic resonance imaging (fMRI) data analyses. However, ROIs based on landmarks on subject-specific (i.e., native space) brain surfaces are anatomically accurate and probably best reflect the regional blood oxygen level dependent (BOLD) response for the individual. Unfortunately, accurate native space ROIs are often time-intensive to delineate even when using automated methods. We compared analyses of group differences when using standard versus native space ROIs using both volume and surface-based analyses. Collegiate and military-veteran participants completed a button press task and a digit-symbol verification task during fMRI acquisition. Data were analyzed within ROIs representing left and right motor and prefrontal cortices, in native and standard space. Volume and surface-based analysis results were also compared using both functional (i.e., percent signal change) and structural (i.e., voxel or node count) approaches. Results suggest that transformation into standard space can affect the outcome of structural and functional analyses (inflating/minimizing differences, based on cortical geography), and these transformations can affect conclusions regarding group differences with volumetric data. Caution is advised when applying standard space ROIs to volumetric fMRI data. However, volumetric analyses show group differences and are appropriate in circumstances when time is limited. Surface-based analyses using functional ROIs generated the greatest group differences and were less susceptible to differences between native and standard space. We conclude that surface-based analyses are preferable with adequate time and computing resources.
Background: Using a standard space brain template is an efficient way of determining region-of-interest (ROI) boundaries for functional magnetic resonance imaging (fMRI) data analyses. However, ROIs based on landmarks on subject-specific (i.e., native space) brain surfaces are anatomically accurate and probably best reflect the regional blood oxygen level dependent (BOLD) response for the individual. Unfortunately, accurate native space ROIs are often time-intensive to delineate even when using automated methods.
BACKGROUNDUsing a standard space brain template is an efficient way of determining region-of-interest (ROI) boundaries for functional magnetic resonance imaging (fMRI) data analyses. However, ROIs based on landmarks on subject-specific (i.e., native space) brain surfaces are anatomically accurate and probably best reflect the regional blood oxygen level dependent (BOLD) response for the individual. Unfortunately, accurate native space ROIs are often time-intensive to delineate even when using automated methods. NEW METHODWe compared analyses of group differences when using standard versus native space ROIs using both volume and surface-based analyses. Collegiate and military-veteran participants completed a button press task and a digit-symbol verification task during fMRI acquisition. Data were analyzed within ROIs representing left and right motor and prefrontal cortices, in native and standard space. Volume and surface-based analysis results were also compared using both functional (i.e., percent signal change) and structural (i.e., voxel or node count) approaches. RESULTS AND COMPARISON WITH EXISTING METHOD(S)Results suggest that transformation into standard space can affect the outcome of structural and functional analyses (inflating/minimizing differences, based on cortical geography), and these transformations can affect conclusions regarding group differences with volumetric data. CONCLUSIONSCaution is advised when applying standard space ROIs to volumetric fMRI data. However, volumetric analyses show group differences and are appropriate in circumstances when time is limited. Surface-based analyses using functional ROIs generated the greatest group differences and were less susceptible to differences between native and standard space. We conclude that surface-based analyses are preferable with adequate time and computing resources.
•Transformation into standard space affected structural and functional analysis results and group difference determinations.•Surface-based analyses using functional ROIs yielded the most group differences.•Native-space volumetric analyses generated significant group differences and would be appropriate when time is limited. Using a standard space brain template is an efficient way of determining region-of-interest (ROI) boundaries for functional magnetic resonance imaging (fMRI) data analyses. However, ROIs based on landmarks on subject-specific (i.e., native space) brain surfaces are anatomically accurate and probably best reflect the regional blood oxygen level dependent (BOLD) response for the individual. Unfortunately, accurate native space ROIs are often time-intensive to delineate even when using automated methods. We compared analyses of group differences when using standard versus native space ROIs using both volume and surface-based analyses. Collegiate and military-veteran participants completed a button press task and a digit-symbol verification task during fMRI acquisition. Data were analyzed within ROIs representing left and right motor and prefrontal cortices, in native and standard space. Volume and surface-based analysis results were also compared using both functional (i.e., percent signal change) and structural (i.e., voxel or node count) approaches. Results suggest that transformation into standard space can affect the outcome of structural and functional analyses (inflating/minimizing differences, based on cortical geography), and these transformations can affect conclusions regarding group differences with volumetric data. Caution is advised when applying standard space ROIs to volumetric fMRI data. However, volumetric analyses show group differences and are appropriate in circumstances when time is limited. Surface-based analyses using functional ROIs generated the greatest group differences and were less susceptible to differences between native and standard space. We conclude that surface-based analyses are preferable with adequate time and computing resources.
Author Sandoval, Traci I.
Turner, Monroe
Hillis, G. Andrew J.
Weaver, Travis
Brigante, Ryan M.
Hubbard, Nicholas A.
Hutchison, Joanna L.
Rypma, Bart
AuthorAffiliation 2 Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX
3 Department of Psychology, University of Texas Southwestern Medical Center, Dallas, TX
1 School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX
AuthorAffiliation_xml – name: 1 School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX
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Keywords Standard space
Native space
Functional magnetic resonance imaging (fMRI)
Group differences
Region-of-interest (ROI)
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Snippet •Transformation into standard space affected structural and functional analysis results and group difference determinations.•Surface-based analyses using...
Using a standard space brain template is an efficient way of determining region-of-interest (ROI) boundaries for functional magnetic resonance imaging (fMRI)...
BACKGROUNDUsing a standard space brain template is an efficient way of determining region-of-interest (ROI) boundaries for functional magnetic resonance...
Background: Using a standard space brain template is an efficient way of determining region-of-interest (ROI) boundaries for functional magnetic resonance...
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StartPage 57
SubjectTerms Adult
Aged
Brain - anatomy & histology
Brain - physiology
Brain Mapping - methods
Cerebrovascular Circulation - physiology
Decision Making - physiology
Female
Functional Laterality
Functional magnetic resonance imaging (fMRI)
Group differences
Humans
Image Processing, Computer-Assisted - methods
Magnetic Resonance Imaging - methods
Male
Middle Aged
Military Personnel
Motor Activity - physiology
Motor Cortex - anatomy & histology
Motor Cortex - physiology
Native space
Neuropsychological Tests
Prefrontal Cortex - anatomy & histology
Prefrontal Cortex - physiology
Region-of-interest (ROI)
Standard space
Students
Veterans
Young Adult
Title The efficiency of fMRI region of interest analysis methods for detecting group differences
URI https://dx.doi.org/10.1016/j.jneumeth.2014.01.012
https://www.ncbi.nlm.nih.gov/pubmed/24487017
https://search.proquest.com/docview/1508426070
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https://pubmed.ncbi.nlm.nih.gov/PMC4000065
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