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Voxel Size, Dependent Measures, Or Similarity to Faces? Review and Comparison of various Possibilities on Explaining the Mixed FFA-Expertise Correlation Results
One of the unsolved debates in imaging neuroscience is whether the fusiform face area, or FFA, is specific to faces or also to the objects of expertise category. The extant literature shows that more studies reporting failures of finding significant expertise-FFA correlations, seemingly supportive o...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5393754/ http://dx.doi.org/10.1068/ic243 |
Sumario: | One of the unsolved debates in imaging neuroscience is whether the fusiform face area, or FFA, is specific to faces or also to the objects of expertise category. The extant literature shows that more studies reporting failures of finding significant expertise-FFA correlations, seemingly supportive of the face specificity hypothesis of FFA. However, systematic comparisons of these literature suggest that at least part of the reasons might be due to the inter-study differences on voxel size differences (3×3×7 vs. 3×3×3 mm3, for example), various dependent measures (e.g, summed t-scores vs. beta coefficients, and different indices of measures, such as [Birds minus Objects] vs. [Birds vs. Cars]), or similarity of expertise stimuli (e.g., Greebles vs. birds/cars) to faces. All these differences have yet to be systematically compared, and in this study we re-analyzed two lab-owned dataset (one has been found a positive and significant FFA-expertise correlation, another not) by resampling into 3 different voxel sizes (3×3×3, 3×3×5, and 3×3×7 mm3), with 3 dependent measures (summed-t, beta, and percent signal changes). Our results suggest that one should always list, and hopefully examine, all the possible source of variations before final conclusion. |
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