Cited by 546Functional Brain Connectivity StudiesAdvanced Neuroimaging Techniques and ApplicationsAdvanced MRI Techniques and Applications

Divide and conquer: A defense of functional localizers

Saxe, Rebecca, Brett, Matthew, Kanwisher, Nancy·2006·NeuroImage

Abstract

Numerous functionally distinct regions of cortex (e.g., V1, MT, the fusiform face area) can be easily identified in any normal human subject in just a few minutes of fMRI scanning. However, the locations of these regions vary across subjects. Investigations of these regions have therefore often used a functional region of interest (fROI) approach in which the region is first identified functionally in each subject individually, before subsequent scans in the same subjects test specific hypotheses concerning that region. This fROI method, which resembled long-established practice in visual neurophysiology, has methodological, statistical, and theoretical advantages over standard alternatives (such as whole-brain analyses of group data): (i) because functional properties are more consistently and robustly associated with fROIs than with locations in stereotaxic space, functional hypotheses concerning fROIs are often the most straightforward to frame, motivate, and test, (ii) because hypotheses are tested in only a handful of fROIs (instead of in tens of thousands of voxels), advance specification of fROIs provides a massive increase in statistical power over whole-brain analyses, and (iii) some fROIs may serve as candidate distinct components of the mind/brain worth investigation as such. Of course fROIs can be productively used in conjunction with other complementary methods. Here, we explain the motivation for and advantages of the fROI approach, and we rebut the criticism of this method offered by Friston et al. (Friston, K., Rotshtein, P., Geng, J., Sterzer, P., Henson, R., in press. A critique of functional localizers. NeuroImage).

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Crossref · 10.1016/j.neuroimage.2005.12.062

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  • Because of a constrained search volume, fROI analyses typically have higher statistical power than whole-brain analyses.

    “In addition, because of a constrained search volume, fROI analyses typically have higher statistical power than whole-brain analyses (Fedorenko, Hsieh, Nieto-Castañón, Whitfield-Gabrieli, & Kanwisher, 2010;Saxe, Brett, & Kanwisher, 2006).”
  • Definitively addressing the question of neural overlap between linguistic and nonlinguistic functions requires examining overlap within individual subjects.

    “Definitively addressing the question of neural overlap between linguistic and nonlinguistic functions requires examining overlap within individual subjects (27, 28), a data analysis strategy that has almost never been applied in neuroimaging investigations of high-level linguistic processing.”

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Authors
Saxe, R., Brett, M., & Kanwisher, N.
Affiliations
  • Massachusetts Institute of Technology (US)
  • MRC Cognition and Brain Sciences Unit (GB)
  • McGovern Institute for Brain Research (US)
Corresponding author
Saxe, Rebecca
Venue
NeuroImage
Publisher
Elsevier BV
Published
2006-05
Volume
30
Issue
4
Pages
1088-1096
ISSN
1053-8119 (ISSN-L)
OpenAlex
W2084332617
Cited by
544
References
49
Citations by year
2026: 26 · 2025: 21 · 2024: 25 · 2023: 29 · 2022: 23 · 2021: 26 · 2020: 26 · 2019: 50 · 2018: 16 · 2017: 24 · 2016: 25 · 2015: 33 · 2014: 20 · 2013: 22 · 2012: 38
FWCI
13.11
Type
journal article
Language
en
Open access
closed
Locations
  • NeuroImage (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Keywords
functional localizer, statistical power, whole-brain analysis, stereotaxic space, visual cortex, fusiform face area, motion processing
MeSH terms
Brain Mapping, Cerebral Cortex, Dominance, Cerebral, Fourier Analysis, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Mathematical Computing, Sensitivity and Specificity, Radiosurgery, Mind-Body Relations, Metaphysical, Surgery, Computer-Assisted

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