Authors:
Raquel Santano-Martínez
1
;
Raquel Leiva-González
1
;
Milad Avazbeigi
2
;
Agustín González-Gutiérrez
3
and
Santiago Marco
4
Affiliations:
1
Universitat de Barcelona, Spain
;
2
Institut for Bioengineering of Catalonia, Universitat de Barcelona and European Center for Soft Computing, Spain
;
3
Institut for Bioengineering of Catalonia and Universitat de Barcelona, Spain
;
4
Institute for Bioengineering of Catalonia and Universitat de Barcelona, Spain
Keyword(s):
Olfaction, Odour Coding, Feature Selection, Olfactory Bulb, Chemotopy, 2-Deoxyglucose Uptake.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Medical Image Detection, Acquisition, Analysis and Processing
Abstract:
Neural coding of chemical information is still under strong debate. It is clear that, in vertebrates, neural representation in the olfactory bulb is a key for understanding a putative odour code. To explore this code, in this work we have studied a public dataset of radio images of 2-Deoxyglucose uptake (2-DG) in the olfactory bulb of rats in response to diverse odorants using univariate pixel selection algorithms: rank-products and Mann-Whitney U (MWU) test. Initial results indicate that some chemical properties of odorants preferentially activate certain areas of the rat olfactory bulb. While non-parametric test (MWU) has difficulties to detect these regions, rank-product provides a higher power of detection.