Al-Baddai, S. and Al-Subari, K. and Tome, A. M. and Volberg, G. and Hanslmayr, S. and Hammwoehner, R. and Lang, E. W. (2014) Bidimensional ensemble empirical mode decomposition of functional biomedical images taken during a contour integration task. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 13. pp. 218-236. ISSN 1746-8094, 1746-8108
Full text not available from this repository. (Request a copy)Abstract
In cognitive neuroscience, extracting characteristic textures and features from functional imaging modalities which could be useful in identifying particular cognitive states across different conditions is still an important field of study. This paper explores the potential of two-dimensional ensemble empirical mode decomposition (2DEEMD) to extract such textures, so-called bidimensional intrinsic mode functions (BIMFs), of functional biomedical images, especially functional magnetic resonance images (fMRI) taken while performing a contour integration task. To identify most informative textures, i.e. BIMFs, a support vector machine (SVM) as well as a random forest (RF) classifier is trained for two different stimulus/response conditions. Classification performance is used to estimate the discriminative power of extracted BIMFs. The latter are then analyzed according to their spatial distribution of brain activations related with contour integration. Results distinctly show the participation of frontal brain areas in contour integration. Employing features generated from textures represented by BIMFs exhibit superior classification performance when compared with a canonical general linear model (GLM) analysis employing statistical parametric mapping (SPM). (C) 2014 Elsevier Ltd. All rights reserved.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | LATERAL OCCIPITAL COMPLEX; HUMAN VISUAL-CORTEX; CLASSIFICATION; ELEMENTS; EMD; PATTERNS; MACHINE; DISEASE; STATES; AREA; |
| Subjects: | 000 Computer science, information & general works > 020 Library & information sciences 100 Philosophy & psychology > 150 Psychology 500 Science > 570 Life sciences |
| Divisions: | Psychology and Pedagogy > Institut für Psychologie > Lehrstuhl für Psychologie I (Allgemeine Psychologie I und Methodenlehre) - Prof. Dr. Mark W. Greenlee Languages and Literatures > Institut für Information und Medien, Sprache und Kultur (I:IMSK) > Lehrstuhl für Informationswissenschaft Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 29 Aug 2019 12:09 |
| Last Modified: | 29 Aug 2019 12:11 |
| URI: | https://pred.uni-regensburg.de/id/eprint/9705 |
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