Joel White

Current trends in `artificial-nose' technology

Basic principles derived from biological olfaction, such as combining semiselective sensor arrays with pattern recognition, have been used to develop instrumentation capable of broad-band chemical detection and quantification. Commercially available instruments are useful in areas including quality control in the food, beverage and fragrance industries, environmental monitoring, chemical-purity and -mixture analysis, and medical diagnostics. Ongoing research is aimed at the development of more-advanced instruments that are smaller, cheaper, faster and more stable and reliable. These second-generation instruments are likely to find an increasing number of applications, including the on-line monitoring of fermentation and other bioprocesses.

Generating Sensor Diversity through Combinatorial Polymer Synthesis

A new approach for rapid, simple generation of uniquely responding sensors for use in polymer-based sensor arrays has been developed. Polymerization reactions between different combinations of two starting materials have been found to lead to many new, unique sensors with responses not simply related to the proportion of the starting materials. This approach is demonstrated in two ways:  (a) the use of discrete polymer sensing cones each comprised of a specific monomer combination and (b) the fabrication of a gradient sensor, containing all combinations between the starting and ending monomer concentrations. Gradient sensors were fabricated using two different binary monomer systems, with both systems showing regions of broadly diverse fluorescence responses to organic vapor pulses.

Optical sensor arrays for odor recognition

Optical sensor arrays containing fluorescent solvatochromatic dyes immobilized in a plurality of polymers generate information-rich responses upon exposure to organic vapors. The response profiles are used to train a variety of computational networks such that subsequent exposure of the array to the vapors enables them to be classified and/or quantified. A number of strategies can be taken to enhance sensitivity and to increase sensor diversity.

An olfactory neuronal network for vapor recognition in an artificial nose

Abstract. Odorant sensitivity and discrimination in the olfactory system appear to involve extensive neural processing of the primary sensory inputs from the olfactory epithelium. To test formally the functional consequences of such processing, we implemented in an artificial chemosensing system a new analytical approach that is based directly on neural circuits of the vertebrate olfactory system. An array of fiber-optic chemosensors, constructed with response properties similar to those of olfactory sensory neurons, provide time-varying inputs to a computer simulation of the olfactory bulb (OB). The OB simulation produces spatiotemporal patterns of neuronal firing that vary with vapor type. These patterns are then recognized by a delay line neural network (DLNN). In the final output of these two processing steps, vapor identity is encoded by the spatial patterning of activity across units in the DLNN, and vapor intensity is encoded by response latency. The OB-DLNN combination thus separates identity and intensity information into two distinct codes carried by the same output units, enabling discrimination among organic vapors over a range of input signal intensities. In addition to providing a well-defined system for investigating olfactory information processing, this biologically based neuronal network performs better than standard feed-forward neural networks in discriminating vapors when small amounts of training data are used.

Solid-state, dye-labeled DNA detects volatile compounds in the vapor phase.

This paper demonstrates a previously unreported property of deoxyribonucleic acid—the ability of dye-labeled, solid-state DNA dried onto a surface to detect odors delivered in the vapor phase by changes in fluorescence. This property is useful for engineering systems to detect volatiles and provides a way for artificial sensors to emulate the way cross-reactive olfactory receptors respond to and encode single odorous compounds and mixtures. Recent studies show that the vertebrate olfactory receptor repertoire arises from an unusually large gene family and that the receptor types that have been tested so far show variable breadths of response. In designing biomimetic artificial noses, the challenge has been to generate a similarly large sensor repertoire that can be manufactured with exact chemical precision and reproducibility and that has the requisite combinatorial complexity to detect odors in the real world. Here we describe an approach for generating and screening large, diverse libraries of defined sensors using single-stranded, fluorescent dye–labeled DNA that has been dried onto a substrate and pulsed with brief exposures to different odors. These new solid-state DNA-based sensors are sensitive and show differential, sequence-dependent responses. Furthermore, we show that large DNA-based sensor libraries can be rapidly screened for odor response diversity using standard high-throughput microarray methods. These observations describe new properties of DNA and provide a generalized approach for producing explicitly tailored sensor arrays that can be rationally chosen for the detection of target volatiles with different chemical structures that include biologically derived odors, toxic chemicals, and explosives.

Robust stimulus encoding in olfactory processing: hyperacuity and efficient signal transmission

We investigate how efficient signal transmission and reconstruction can be achieved within the olfactory system. We consider a theoretical model of signal integration within the olfactory pathway that derives from its convergent architecture and results in increased sensitivity to chemical stimuli between the first and second stages of the system. This phenomenon of signal integration in the olfactory system is formalised as an instance of hyperacuity. By exploiting a large population of chemically sensitive microbeads, we demonstrate how such a signal integration technique can lead to real gains in sensitivity in machine olfaction. In a separate computational model of the early olfactory pathway that is driven by real-world chemosensor input, we investigate how spike-based signal and graded-potential signalling compares for supporting the accuracy of reconstruction of the chemical stimulus at later stages of neuronal processing.

Odor recognition in an artificial nose by spatio-temporal processing using an olfactory neuronal network ☆

Abstract We have developed an analytical approach for an artificial chemosensing system that is based directly on olfactory neural circuits. An array of chemosensors, with response properties similar to olfactory sensory neurons, provides time-varying inputs to a computer simulation of the olfactory bulb (OB). The OB simulation produces spatio-temporal patterns of spiking that vary with odor type. These patterns are then recognized by a delay line neural network (DLNN). After OB–DLNN processing, odor identity is encoded by activity across DLNN units, and odor intensity is encoded by response latency, enabling discrimination among organic vapors over a range of concentrations.

Stimulus encoding during the early stages of olfactory processing: A modeling study using an artificial olfactory system

Abstract This paper addresses the issue of how efficient stimulus encoding may be carried out within the early stages of the olfactory system—in particular how a rate-coding scheme compares to the direct transmission of graded potentials in terms of the accuracy of the estimate that an ideal observer may make about the stimulus. We make use of a spiking neuronal model of the early stages of the olfactory system that is driven by fluorescent microbead chemosensors in order to compare these two coding schemes. Our results indicate how the charging time-constants present at the first stages of neuronal information processing within the olfactory bulb directly affects its ability to accurately reconstruct the stimulus.

Representation of Odor Information in the Olfactory System: From Biology to an Artificial Nose

The olfactory systems of animals as diverse as insects and primates are well-known for having extraordinary sensitivity while, at the same time, exhibiting broad discriminative abilities. These properties, often mutually exclusive in other chemical recognition systems, appear to arise from the parallel, distributed nature of the processes that underlie how odors are encoded at each level in the olfactory pathway in the brain. In this paper we describe how we have tried to characterize the physiological aspects of these processes in biological experiments, capture these processes in a computational model, and then to use these observations to design and build a biologically inspired artificial device. The Tufts Medical School Nose has achieved a degree of sensitivity and discriminability that, for certain compounds under defined conditions, approaches that of its biological parent.

Improved vapor sensitivity by rationally designing fluorescent turn-on sensors.

We report a turn-on sensor framework with enhanced vapor sensitivity by increasing the sensors response dynamic range via rational design of the sensor formulation. Using a fluorescent dye as the reporter, our approach begins by reducing sensor background fluorescence through the use of selected quenchers. Analyte interaction induces the onset of emission by interrupting the quenching interaction, thereby turning on the sensor. We demonstrate over an order of magnitude increase in vapor sensitivity for dimethyl methylphosphonate (a Sarin simulant) detection using a sensor containing inorganic oxides as a quencher for Nile Red dye. This approach was also used to develop a new sensor with improved sensitivity for methyl benzoate (a hydrolysis byproduct of cocaine, used to train drug-sniffing dogs). By generalization, additional candidate quenchers for Nile Red were identified based on Lewis acid/base interactions. This framework can be applied in parallel with other amplification strategies including mass transport incentive, one-analyte-to-multiple-reporter schemes or signal lasing to further increase sensor response amplitude.