DocumentCode :
1416740
Title :
Odor Discrimination Using Neural Decoding of the Main Olfactory Bulb in Rats
Author :
You, Kyung-Jin ; Ham, Hyoung Geol ; Lee, Hyun Joo ; Lang, Yiran ; Im, Changkyun ; Koh, Chin Su ; Kim, Mi-Yeon ; Shin, Hyung-Cheul ; Shin, Hyun-Chool
Author_Institution :
Dept. of Electron. Eng., Soongsil Univ., Seoul, South Korea
Volume :
58
Issue :
5
fYear :
2011
fDate :
5/1/2011 12:00:00 AM
Firstpage :
1208
Lastpage :
1215
Abstract :
This paper presents a novel method for inferring the odor based on neural activities observed from rats´ main olfactory bulbs. Multichannel extracellular single unit recordings were done by microwire electrodes (tungsten, 50 μm, 32 channels) implanted in the mitral/tufted cell layers of the main olfactory bulb of anesthetized rats to obtain neural responses to various odors. Neural response as a key feature was measured by subtraction of neural firing rate before stimulus from after. For odor inference, we have developed a decoding method based on the maximum likelihood estimation. The results have shown that the average decoding accuracy is about 100.0%, 96.0%, 84.0%, and 100.0% with four rats, respectively.
Keywords :
biomedical electrodes; cellular biophysics; decoding; inference mechanisms; maximum likelihood estimation; mechanoception; medical signal detection; neurophysiology; main olfactory bulb; maximum likelihood estimation; microwire electrodes; mitral/tufted cell layers; multichannel extracellular single unit recordings; neural decoding; neural firing rate; odor discrimination; Maximum likelihood decoding; Minerals; Neurons; Olfactory; Petroleum; Rats; BMI; inference; main olfactory bulb (MOB); neural activity; neural decoding; odorants; olfactory; Algorithms; Animals; Electrodes, Implanted; Electroencephalography; Evoked Potentials; Male; Models, Statistical; Odors; Olfactory Bulb; Organic Chemicals; Rats; Rats, Sprague-Dawley; Signal Processing, Computer-Assisted; Smell;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2010.2103312
Filename :
5678633
Link To Document :
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