Open Science Research Excellence
@article{(International Science Index):,
  title    = {Odor Discrimination Using Neural Decoding of Olfactory Bulbs in Rats},
  author    = {K.-J. You and  H.J. Lee and  Y. Lang and  C. Im and  C.S. Koh and  H.-C. Shin},
  country   = {},
  abstract  = {This paper presents a novel method for inferring the
odor based on neural activities observed from rats- main olfactory
bulbs. Multi-channel extra-cellular single unit recordings were done
by micro-wire electrodes (tungsten, 50μm, 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 substraction of neural firing rate
before stimulus from after. For odor inference, we have developed a
decoding method based on the maximum likelihood (ML) 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. This
work has profound implications for a novel brain-machine interface
system for odor inference.},
    journal   = {International Journal of Biological, Biomolecular, Agricultural, Food and Biotechnological Engineering},  volume    = {5},
  number    = {11},
  year      = {2011},
  pages     = {690 - 693},
  ee        = {},
  url       = {},
  bibsource = {},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 59, 2011},