Computational exploration of molecular receptive fields in the olfactory bulb reveals a glomerulus-centric chemical map

© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Progress in olfactory research is currently hampered by incomplete knowledge about chemical receptive ranges of primary receptors. Moreover, the chemical logic underlying the arrangement of computational units in the olfactory bulb has still not been resolved. We undertook a large-scale approach at characterising molecular receptive ranges (MRRs) of glomeruli in the dorsal olfactory bulb (dOB) innervated by the MOR18-2 olfactory receptor, also known as Olfr78, with human ortholog OR51E2. Guided by an iterative approach that combined biological screening and machine learning, we selected 214 odorants to characterise the response of MOR18-2 and its neighbouring glomeruli. We found that a combination of conventional physico-chemical and vibrational molecular descriptors performed best in predicting glomerular responses using nonlinear Support-Vector Regression. We also discovered several previously unknown odorants activating MOR18-2 glomeruli, and obtained detailed MRRs of MOR18-2 glomeruli and their neighbours. Our results confirm earlier findings that demonstrated tunotopy, that is, glomeruli with similar tuning curves tend to be located in spatial proximity in the dOB. In addition, our results indicate chemotopy, that is, a preference for glomeruli with similar physico-chemical MRR descriptions being located in spatial proximity. Together, these findings suggest the existence of a partial chemical map underlying glomerular arrangement in the dOB. Our methodology that combines machine learning and physiological measurements lights the way towards future high-throughput studies to deorphanise and characterise structure-activity relationships in olfaction.Peer reviewe

MemorZig : A Short-Term Memory-Based Algorithm for Efficient Odour Source Tracking

The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P8

Source term estimation of a hazardous airborne release using an unmanned aerial vehicle

Gaining information about an unknown gas source is a task of great importance with applications in several areas including: responding to gas leaks or suspicious smells, quantifying sources of emissions, or in an emergency response to an industrial accident or act of terrorism. In this paper, a method to estimate the source term of a gaseous release using measurements of concentration obtained from an unmanned aerial vehicle (UAV) is described. The source term parameters estimated include the three dimensional location of the release, its emission rate, and other important variables needed to forecast the spread of the gas using an atmospheric transport and dispersion model. The parameters of the source are estimated by fusing concentration observations from a gas detector on-board the aircraft, with meteorological data and an appropriate model of dispersion. Two models are compared in this paper, both derived from analytical solutions to the advection diffusion equation. Bayes’ theorem, implemented using a sequential Monte Carlo algorithm, is used to estimate the source parameters in order to take into account the large uncertainties in the observations and formulated models. The system is verified with novel, outdoor, fully automated experiments, where observations from the UAV are used to estimate the parameters of a diffusive source. The estimation performance of the algorithm is assessed subject to various flight path configurations and wind speeds. Observations and lessons learned during these unique experiments are discussed and areas for future research are identified

Forensic Science: Current State and Perspective by a Group of Early Career Researchers

© 2016, Springer Science+Business Media Dordrecht. Forensic science and its influence on policing and the criminal justice system have increased since the beginning of the twentieth century. While the philosophies of the forensic science pioneers remain the pillar of modern practice, rapid advances in technology and the underpinning sciences have seen an explosion in the number of disciplines and tools. Consequently, the way in which we exploit and interpret the remnant of criminal activity are adapting to this changing environment. In order to best exploit the trace, an interdisciplinary approach to both research and investigation is required. In this paper, nine postdoctoral research fellows from a multidisciplinary team discuss their vision for the future of forensic science at the crime scene, in the laboratory and beyond. This paper does not pretend to be exhaustive of all fields of forensic science, but describes a portion of the postdoctoral fellows’ interests and skills

On the use of autonomous unmanned vehicles in response to hazardous atmospheric release incidents

Recent events have induced a surge of interest in the methods of response to releases of hazardous materials or gases into the atmosphere. In the last decade there has been particular interest in mapping and quantifying emissions for regulatory purposes, emergency response, and environmental monitoring. Examples include: responding to events such as gas leaks, nuclear accidents or chemical, biological or radiological (CBR) accidents or attacks, and even exploring sources of methane emissions on the planet Mars. This thesis presents a review of the potential responses to hazardous releases, which includes source localisation, boundary tracking, mapping and source term estimation. [Continues.]</div

Formation-Based Odour Source Localisation Using Distributed Terrestrial and Marine Robotic Systems

This thesis tackles the problem of robotic odour source localisation, that is, the use of robots to find the source of a chemical release. As the odour travels away from the source, in the form of a plume carried by the wind or current, small scale turbulence causes it to separate into intermittent patches, suppressing any gradients and making this a particularly challenging search problem. We focus on distributed strategies for odour plume tracing in the air and in the water and look primarily at 2D scenarios, although novel results are also presented for 3D tracing. The common thread to our work is the use of multiple robots in formation, each outfitted with odour and flow sensing devices. By having more than one robot, we can gather observations at different locations, thus helping overcome the difficulties posed by the patchiness of the odour concentration. The flow (wind or current) direction is used to orient the formation and move the robots up-flow, while the measured concentrations are used to centre the robots in the plume and scale the formation to trace its limits. We propose two formation keeping methods. For terrestrial and surface robots equipped with relative or absolute positioning capabilities, we employ a graph-based formation controller using the well-known principle of Laplacian feedback. For underwater vehicles lacking such capabilities, we introduce an original controller for a leader-follower triangular formation using acoustic modems with ranging capabilities. The methods we propose underwent extensive experimental evaluation in high-fidelity simulations and real-world trials. The marine formation controller was implemented in MEDUSA autonomous vehicles and found to maintain a stable formation despite the multi-second ranging period. The airborne plume tracing algorithm was tested using compact Khepera robots in a wind tunnel, yielding low distance overheads and reduced tracing error. A combined approach for marine plume tracing was evaluated in simulation with promising results

A model of visual-olfactory integration for odour localisation in free-flying fruit flies

Flying fruit flies (Drosophila melanogaster) locate a concealed appetitive odour source most accurately in environments containing vertical visual contrasts. To investigate how visuomotor and olfactory responses may be integrated, we examine the free-flight behaviour of flies in three visual conditions, with and without food odour present. While odour localisation is facilitated by uniformly distributed vertical contrast as compared with purely horizontal contrast, localised vertical contrast also facilitates odour localisation, but only if the odour source is situated close to it. We implement a model of visuomotor control consisting of three parallel subsystems: an optomotor response stabilising the model fly\u27s yaw orientation; a collision avoidance system to saccade away from looming obstacles; and a speed regulation system. This model reproduces many of the behaviours we observe in flies, including visually mediated ‘rebound’ turns following saccades. Using recordings of real odour plumes, we simulate the presence of an odorant in the arena, and investigate ways in which the olfactory input could modulate visuomotor control. We reproduce the experimental results by using the change in odour intensity to regulate the sensitivity of collision avoidance, resulting in visually mediated chemokinesis. Additionally, it is necessary to amplify the optomotor response whenever odour is present, increasing the model fly\u27s tendency to steer towards features of the visual environment. We conclude that visual and olfactory responses of Drosophila are not independent, but that relatively simple interaction between these modalities can account for the observed visual dependence of odour source localisation

Formation-Based Odour Source Localisation Using Distributed Terrestrial and Marine Robotic Systems

This thesis tackles the problem of robotic odour source localisation, that is, the use of robots to find the source of a chemical release. As the odour travels away from the source, in the form of a plume carried by the wind or current, small scale turbulence causes it to separate into intermittent patches, suppressing any gradients and making this a particularly challenging search problem. We focus on distributed strategies for odour plume tracing in the air and in the water and look primarily at 2D scenarios, although novel results are also presented for 3D tracing. The common thread to our work is the use of multiple robots in formation, each outfitted with odour and flow sensing devices. By having more than one robot, we can gather observations at different locations, thus helping overcome the difficulties posed by the patchiness of the odour concentration. The flow (wind or current) direction is used to orient the formation and move the robots up-flow, while the measured concentrations are used to centre the robots in the plume and scale the formation to trace its limits. We propose two formation keeping methods. For terrestrial and surface robots equipped with relative or absolute positioning capabilities, we employ a graph-based formation controller using the well-known principle of Laplacian feedback. For underwater vehicles lacking such capabilities, we introduce an original controller for a leader-follower triangular formation using acoustic modems with ranging capabilities. The methods we propose underwent extensive experimental evaluation in high-fidelity simulations and real-world trials. The marine formation controller was implemented in MEDUSA autonomous vehicles and found to maintain a stable formation despite the multi-second ranging period. The airborne plume tracing algorithm was tested using compact Khepera robots in a wind tunnel, yielding low distance overheads and reduced tracing error. A combined approach for marine plume tracing was evaluated in simulation with promising results

A longitudinal study of cortical EEG to olfactory stimulation : involving inter- and intra- subjective responses

This thesis forms the largest and most systematic study of the topographical EEG response to odour. The evolutionary history of the olfactory sense is briefly presented and its relevance to humans in the present day is considered. This thesis examines the information processing that occurs in this sensory system. The type of processing that the olfactory system utilises at each anatomical stage is discussed. The character of olfactory information that may reach neocortical levels in humans is considered in the light of the technology available to detect such information. The neurogenesis of the EEG is considered, together with questions concerning its postulated functional significance. The empirical work carried out uses the most advanced methodology for this type of study. The large number of odourants and subjects, combined with the longitudinal element, make this the most ambitious study of this nature undertaken. The issues surrounding the analysis and interpretation of EEG data arc fully discussed and the impact of Chaos theory is considered. Five major analysis techniques were used on the data collected, but largely negative findings arc reported. The reasons for the failure of this experimental paradigm are discussed and improvements arc suggested for future work. The major contribution of this thesis lies in its exploration of the assumptions of the EEG response to odour. The thesis notes the lack of a conceptual framework that has hindered progress in the area of the "odour" EEG. Recent developments in neural network theory and Chaos theory are highlighted as possible alternative approaches to the modelling and understanding of the olfactory system

Efficiency of island homing by sea turtles under multimodal navigating strategies

A dot in the vastness of the Atlantic, Ascension Island remains a lifelong goal for the green sea turtles that hatched there, returning as adults every three or four years to nest. This navigating puzzle was brought to the scientific community's attention by Charles Darwin and remains a topic of considerable speculation. Various cues have been suggested, with orientation to geomagnetic field elements and following odour plumes to their island source among the most compelling. Via a comprehensive in silico investigation we test the hypothesis that multimodal cue following, in which turtles utilise multiple guidance cues, is the most effective strategy. Specifically, we combine agent-based and continuous-level modelling to simulate displaced virtual turtles as they attempt to return to the island. Our analysis shows how population homing efficiency improves as the number of utilised cues is increased, even under “extreme” scenarios where the overall strength of navigating information decreases. Beyond the paradigm case of green turtles returning to Ascension Island, we believe this could commonly apply throughout animal navigation