title: Stable odor recognition by a neuro-adaptive electronic nose.
abstract: Sensitivity, selectivity and stability are decisive properties of sensors. In chemical gas sensors odor recognition can be severely compromised by poor signal stability, particularly in real life applications where the sensors are exposed to unpredictable sequences of odors under changing external conditions. Although olfactory receptor neurons in the nose face similar stimulus sequences under likewise changing conditions, odor recognition is very stable and odorants can be reliably identified independently from past odor perception. We postulate that appropriate pre-processing of the output signals of chemical sensors substantially contributes to the stability of odor recognition, in spite of marked sensor instabilities. To investigate this hypothesis, we use an adaptive, unsupervised neural network inspired by the glomerular input circuitry of the olfactory bulb. Essentially the model reduces the effect of the sensors' instabilities by utilizing them via an adaptive multicompartment feed-forward inhibition. We collected and analyzed responses of a 4 × 4 gas sensor array to a number of volatile compounds applied over a period of 18 months, whereby every sensor was sampled episodically. The network conferred excellent stability to the compounds' identification and was clearly superior over standard classifiers, even when one of the sensors exhibited random fluctuations or stopped working at all.
authors.affiliation: Department of Electronic Engineering, University of Rome Tor Vergata, Via del Politecnico 1, Rome 00133, Italy.
authors.forename: Eugenio
authors.initials: E
authors.lastname: Martinelli
authors.affiliation: Department of Electronic Engineering, University of Rome Tor Vergata, Via del Politecnico 1, Rome 00133, Italy.
authors.forename: Gabriele
authors.initials: G
authors.lastname: Magna
authors.affiliation: Department of Electronic Engineering, University of Rome Tor Vergata, Via del Politecnico 1, Rome 00133, Italy.
authors.forename: Davide
authors.initials: D
authors.lastname: Polese
authors.affiliation: BioCircuits Institute, University of California San Diego, 9500 Gilman Dr., La Jolla, CA 92093-0402, USA.
authors.forename: Alexander
authors.initials: A
authors.lastname: Vergara
authors.affiliation: 1] Inst. of Neurophysiology and Cellular Biophysics, University of Göttingen, Humboldtallee 23, 37077 Göttingen, Germany [2] DFG Excellence Cluster 171 and Bernstein Forum of Neurotechnology, Univ. Göttingen.
authors.forename: Detlev
authors.initials: D
authors.lastname: Schild
authors.affiliation: Department of Electronic Engineering, University of Rome Tor Vergata, Via del Politecnico 1, Rome 00133, Italy.
authors.forename: Corrado
authors.initials: C
authors.lastname: Di Natale
mesh_terms: D015374:Biosensing Techniques; D062609:Electronic Nose; D009812:Odorants; D009833:Olfactory Pathways / Q000502:physiology; D018034:Olfactory Receptor Neurons / Q000502:physiology