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UNIVERSITY OF BUCHAREST
FACULTY OF PHYSICS Guest
2024-11-23 17:50 |
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Conference: Bucharest University Faculty of Physics 2017 Meeting
Section: Biophysics; Medical Physics
Title:
Statistical analysis of face recognition/repetition paradigm in fMRI
– a factorial approach
Authors:
Simona SPÎNU, Radu MUTIHAC
*
Affiliation:
Faculty of Physics, University of Bucharest, 405 Atomistilor Str., PO Box MG-11, 077125, Măgurele, Romania
E-mail
simonaspinu91@yahoo.com
Keywords:
fMRI, factorial statistical analysis, face recognition, face repetition
Abstract:
There is a growing interest in complete defining functional interactions of different brain areas based on explaining the increased sensitivity and specificity of fMRI depending on the experimental paradigm or the changes in magnetic field intensity used. In order to obtain information about healthy or diseased areas of brain, different analysis and medical procedures are used. The rationale of our proposed work is to compare two approaches of activation by means of fMRI investigations and to confirm or not statistically the tested hypotheses using various paradigms. Our knowledge on the ability to visualize and analyze specific areas of subjects in a common analysis space as confirmatory and exploratory statistical analysis methods has not been performed so far. Therefore, the purpose of our work is to develop and present the benefits of these two types of analysis for a factorial event-related experimental paradigm as face recognition/repetition. The approach is based on human memory capacity to recognize physical images like in the case of a healthy adult subject called to visually recognize popular (famous) faces in random repetitions among several unknown (non-famous) faces.Furthermore, in this work, we studied the transparency of statistical analysis methods creating a parallel between hypothesis-driven models and data-driven models. In the end, we found that inferential and exploratory analysis methods are efficient, associative, integrative, and complementary for statistical analysis of a paradigm in pattern recognition.
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