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