Literature DB >> 26553580

The reliability of individual differences in face-selective responses in the fusiform gyrus and their relation to face recognition ability.

Rankin W McGugin1,2, Isabel Gauthier3.   

Abstract

Face recognition ability varies widely in the normal population and there is increasing interest in linking individual differences in perception to their neural correlates. Such brain-behavior correlations require that both the behavioral measures and the selective BOLD responses be reliable. The reliability of the location of the fusiform face area (FFA) has been demonstrated in several studies. Here, we address reliability of a different kind: reliability of the magnitude of responses to faces within this localized region. We calculated split-half reliability of face-selective responses within functionally defined posterior and anterior face-selective patches in the fusiform gyrus (FFA1/FFA2). We used data from two published studies that included both a functional localizer for face-selective regions and independent data suitable for quantifying face-selectivity. We found highly reliable face selectivity in both hemispheres that was highest in the centermost voxel(s) compared to larger regions of interest. Differences in face-selectivity between the two face patches within one hemisphere and across hemispheres were also reliable. Our results reveal considerable reliability of face-selective signals in and across FFA in adults. Given the good reliability of behavioral measures of face recognition, prior failures to find a relationship between the mean response to faces in FFA and behavioral face recognition in normal adult subjects are unlikely to be due to limitations of the measurements.

Keywords:  Face-selectivity; Fusiform gyrus; Reliability

Mesh:

Year:  2016        PMID: 26553580     DOI: 10.1007/s11682-015-9467-4

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


  6 in total

1.  Modular community structure of the face network supports face recognition.

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Journal:  Cereb Cortex       Date:  2022-09-04       Impact factor: 4.861

Review 2.  The Face of Image Reconstruction: Progress, Pitfalls, Prospects.

Authors:  Adrian Nestor; Andy C H Lee; David C Plaut; Marlene Behrmann
Journal:  Trends Cogn Sci       Date:  2020-07-13       Impact factor: 20.229

3.  Cortical Morphology in Autism: Findings from a Cortical Shape-Adaptive Approach to Local Gyrification Indexing.

Authors:  Alisa R Zoltowski; Ilwoo Lyu; Michelle Failla; Lisa E Mash; Kacie Dunham; Jacob I Feldman; Tiffany G Woynaroski; Mark T Wallace; Laura A Barquero; Tin Q Nguyen; Laurie E Cutting; Hakmook Kang; Bennett A Landman; Carissa J Cascio
Journal:  Cereb Cortex       Date:  2021-10-01       Impact factor: 4.861

4.  Visual imagery of faces and cars in face-selective visual areas.

Authors:  Mackenzie A Sunday; Rankin W McGugin; Benjamin J Tamber-Rosenau; Isabel Gauthier
Journal:  PLoS One       Date:  2018-09-28       Impact factor: 3.240

5.  Properties of face localizer activations and their application in functional magnetic resonance imaging (fMRI) fingerprinting.

Authors:  Lena Schwarz; Benjamin Kreifelts; Dirk Wildgruber; Michael Erb; Klaus Scheffler; Thomas Ethofer
Journal:  PLoS One       Date:  2019-04-23       Impact factor: 3.240

6.  Neural responses to children's faces: Test-retest reliability of structural and functional MRI.

Authors:  Esther Heckendorf; Marian J Bakermans-Kranenburg; Marinus H van Ijzendoorn; Rens Huffmeijer
Journal:  Brain Behav       Date:  2019-02-09       Impact factor: 2.708

  6 in total

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