Explosives detection by military working dogs: Olfactory generalization from components to mixtures

Lazarowski, Lucia; Dorman, David C.

doi:10.1016/j.applanim.2013.11.010

Cited by 99 publications

(56 citation statements)

References 33 publications

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“…In addition, the dogs' 579 perception of the mixture stimulus in our study suggest that dogs perceive the mixture as a new 580 odor rather than as its individual elements. Consistent with previous behavioral studies, this 581 may explain why dogs trained on individual target odors have difficulty generalizing to mixtures 582(Lazarowski & Dorman, 2014;Lazarowski et al, 2015). Further, dogs' brain activations showed 583 more similarity between the mixture of odors and a no reward odor, suggesting either a584 learned association or a neural bias toward the no reward (distractor) odor.…”

supporting

confidence: 73%

“…Given that most odor discrimination tests for 73 dogs are behaviorally based and/or unstandardized, it is almost impossible to predict which 74 components of an odor a particular dog uses to identify the target (Göth,McLean,& Trevelyan,75 2003). For example, dogs that were trained to detect pure potassium chlorate failed to reliably 76 detect potassium chlorate-based explosive mixtures (Lazarowski & Dorman, 2014). This finding, 77 and others, highlight the potential limitations of training dogs to detect a specific target odor to 78 then indicate to the target when mixed with distractors (DeGreeff et al, 2017; Hayes,79 McGreevy, Forbes, Laing, & Stuetz, 2018).…”

Section: Introductionmentioning

confidence: 95%

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Decoding Odor Mixtures in the Dog Brain: An Awake fMRI Study

Prichard

Chhibber

King

et al. 2019

Preprint

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In working and practical contexts, dogs rely upon their ability to discriminate a target odor from distracting odors and other sensory stimuli. Few studies have examined odor discrimination using non-behavioral methods or have approached odor discrimination from the dog’s perspective. Using awake fMRI in 18 dogs, we examined the neural mechanisms underlying odor discrimination between two odors and a mixture of the odors. Neural activation was measured during the presentation of a target odor (A) associated with a food reward, a distractor odor (B) associated with nothing, and a mixture of the two odors (A+B). Changes in neural activation during the presentations of the odor stimuli in individual dogs were measured over time within three regions known to be involved with odor processing: the caudate nucleus, the amygdala, and the olfactory bulbs. Average activation within the amygdala showed that dogs maximally differentiated between odor stimuli based on the stimulus-reward associations by the first run, while activation to the mixture (A+B) was most similar to the no-reward (B) stimulus. To identify the neural representation of odor mixtures in the dog brain, we used a random forest classifier to compare multilabel (elemental) vs. multiclass (configural) models. The multiclass model performed much better than the multilabel (weighted-F1 0.44 vs. 0.14), suggesting the odor mixture was processed configurally. Analysis of the subset of high-performing dogs based on their brain classification metrics revealed a network of olfactory information-carrying brain regions that included the amygdala, piriform cortex, and posterior cingulate. These results add further evidence for the configural processing of odor mixtures in dogs and suggest a novel way to identify high-performers based on brain classification metrics.

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supporting

confidence: 73%

Section: Introductionmentioning

confidence: 95%

Decoding Odor Mixtures in the Dog Brain: An Awake fMRI Study

Prichard

Chhibber

King

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…For bulk detection, ideally materials would be detected and identified prior to use in terrorist activities. Towards this end, traditional bulk detection has been achieved via X-ray based instrumentation 43 , trained animals 45 , ion mobility spectroscopy [46][47][48][49] , terahertz spectroscopy, chemical sensors 50 and optical sensors. Typically at checkpoints, materials (less than bulk quantity) are tested for and collected via swabbing or vapor accumulation techniques.…”

Section: Introductionmentioning

confidence: 99%

Flexible SERS-based substrates: challenges and opportunities toward an Army relevant universal sensing platform

2015

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Generally the fabrication, assembly and evaluation of plasmonic nanostructures for surface enhanced Raman scattering (SERS) substrates has focused on static rigid substrates such as glass and silicon. However, these static substrates severely limit the application of plasmonic nanostructures as (i) they provide no means to alter the state of assembly of the nanostructures once they are formed or anchored on the surface i.e., not reconfigurable; and (ii) preclude applications which demand non-planar, flexible or conformal surfaces. The above considerations has led to the development of a novel class of SERS substrates based on flexible substrates such paper, polymer membranes and electrospun fibers. These flexible SERS media based on unconventional substrates such as paper offer distinct advantages compared to the conventional SERS substrates in that (i) flexible nature of the substrate enables conformal contact with the surfaces under investigation leading to efficient sample collection; (ii) porous nature of the SERS substrate (interstices between the fibers) provides efficient access to the analytes; (iii) high surface area of the 3D paper substrate results in large dynamic range of the chemical sensors; (iv) intricate network of fibers decorated with metal nanoparticles can provide potentially high density of electromagnetic hotspots; (v) intense light scattering caused by the fibrous structure of the substrate (e.g., paper) enables efficient light-metal interaction; and (vi) facile fabrication leads to efficient, robust, reliable, reusable and cost-effective SERS substrates. In this presentation, we will focus on the Army need for a more flexible (substrate surface and application) SERS substrate for universal sensing. This presentation will leverage from material presented at a flexible SERS (May 2014) workshop hosted by Dr. Srikanth Singamaneni at Washington University.

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“…In recent decades, canines have been reliably trained to detect explosives, ignitable liquids, narcotics, human scent and the discovered evidence has been successfully submitted in court of law [11][12][13][14][15][16][17][18][19][20]. Despite canines' wide potential for detection in many areas, they are most commonly used for explosive detection as a result of the growing threat of terrorism.…”

Section: A Non-contact Passive Approach For the Effective Collection mentioning

confidence: 99%

A Non-Contact Passive Approach for the Effective Collection of Target Explosive Volatiles for Canine Training Aid Development

Cl¹,

Am²,

Pa³

et al. 2016

Journal of Forensic Science & Criminology

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The use of real explosive materials for canine training involves inherent dangers, toxicity risks exposure, and often limited availability of the training material all of which may affect the reliable training of canine teams. For this reason, the development of a training aid suitable for daily operations is beneficial to provide safe and effective explosive detection training that can provide for enhanced detection capabilities. This study presents a non-contact passive approach for the collection of target volatile organic compounds (VOCs) emanating from real explosive materials to be used as potential canine training aids. This will also provide the ability for the creation of new training aids based on the rapid evolution of new explosive threats. Experiments were performed based on previously identified explosive signature volatiles such as 2-ethyl-1-hexanol (2E1H), 2,3-dimethyl-dinitrobutane (DMNB), and 2,4-dinitrotoluene (2,4-DNT). Composition 4 (C4) explosive material was used for the static collection of the 2E1H and DMNB, as well as single based smokeless powder for the collection of 2,4-DNT. The samples were collected in a controlled environment and cotton gauze pads were used as the collection material. A time optimization analysis was conducted for all three target volatiles in time intervals of ranging from 0.5 to 120 minutes. Solid phase microextraction (SPME) was used along with gas chromatographymass spectrometry/electron capture detection (GC-MS/ECD) for extraction and confirmation of target volatiles. The results show that collection of characteristic volatiles are obtained after 15 min of exposing the gauze pad to 2E1H and 30 min was optimal for DMNB and 2-4, DNT. Overall, the results demonstrated the possibility to perform static collection of signature VOCs from real explosive materials onto a gauze pad via a non-contact passive method for its potential use as effective canine training aid.

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Explosives detection by military working dogs: Olfactory generalization from components to mixtures

Cited by 99 publications

References 33 publications

Decoding Odor Mixtures in the Dog Brain: An Awake fMRI Study

Decoding Odor Mixtures in the Dog Brain: An Awake fMRI Study

Flexible SERS-based substrates: challenges and opportunities toward an Army relevant universal sensing platform

A Non-Contact Passive Approach for the Effective Collection of Target Explosive Volatiles for Canine Training Aid Development

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