1. |
- Alexander, Stephen P. H., et al.
(author)
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The Concise Guide to PHARMACOLOGY 2023/24: G protein-coupled receptors
- 2023
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In: BRITISH JOURNAL OF PHARMACOLOGY. - : British pharmacological society. - 0007-1188 .- 1476-5381. ; 180
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Journal article (peer-reviewed)abstract
- The Concise Guide to PHARMACOLOGY 2023/24 is the sixth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of approximately 1800 drug targets, and about 6000 interactions with about 3900 ligands. There is an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes almost 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at . G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2023, and supersedes data presented in the 2021/22, 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
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2. |
- Christopoulos, Arthur, et al.
(author)
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THE CONCISE GUIDE TO PHARMACOLOGY 2021/22: G protein-coupled receptors.
- 2021
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In: British journal of pharmacology. - : Wiley. - 1476-5381 .- 0007-1188. ; 178 Suppl 1
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Research review (peer-reviewed)abstract
- The Concise Guide to PHARMACOLOGY 2021/22 is the fifth in this series of biennial publications. The Concise Guide provides concise overviews, mostly in tabular format, of the key properties of nearly 1900 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide constitutes over 500 pages, the material presented is substantially reduced compared to information and links presented on the website. It provides a permanent, citable, point-in-time record that will survive database updates. The full contents of this section can be found at http://onlinelibrary.wiley.com/doi/bph.15538. G protein-coupled receptors are one of the six major pharmacological targets into which the Guide is divided, with the others being: ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. The landscape format of the Concise Guide is designed to facilitate comparison of related targets from material contemporary to mid-2021, and supersedes data presented in the 2019/20, 2017/18, 2015/16 and 2013/14 Concise Guides and previous Guides to Receptors and Channels. It is produced in close conjunction with the Nomenclature and Standards Committee of the International Union of Basic and Clinical Pharmacology (NC-IUPHAR), therefore, providing official IUPHAR classification and nomenclature for human drug targets, where appropriate.
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3. |
- Bagheri, Zahra M., et al.
(author)
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An autonomous robot inspired by insect neurophysiology pursues moving features in natural environments
- 2017
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In: Journal of Neural Engineering. - : IOP Publishing. - 1741-2560 .- 1741-2552. ; 14:4
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Journal article (peer-reviewed)abstract
- Objective. Many computer vision and robotic applications require the implementation of robust and efficient target-tracking algorithms on a moving platform. However, deployment of a real-time system is challenging, even with the computational power of modern hardware. Lightweight and low-powered flying insects, such as dragonflies, track prey or conspecifics within cluttered natural environments, illustrating an efficient biological solution to the target-tracking problem. Approach. We used our recent recordings from 'small target motion detector' neurons in the dragonfly brain to inspire the development of a closed-loop target detection and tracking algorithm. This model exploits facilitation, a slow build-up of response to targets which move along long, continuous trajectories, as seen in our electrophysiological data. To test performance in real-world conditions, we implemented this model on a robotic platform that uses active pursuit strategies based on insect behaviour. Main results. Our robot performs robustly in closed-loop pursuit of targets, despite a range of challenging conditions used in our experiments; low contrast targets, heavily cluttered environments and the presence of distracters. We show that the facilitation stage boosts responses to targets moving along continuous trajectories, improving contrast sensitivity and detection of small moving targets against textured backgrounds. Moreover, the temporal properties of facilitation play a useful role in handling vibration of the robotic platform. We also show that the adoption of feed-forward models which predict the sensory consequences of self-movement can significantly improve target detection during saccadic movements. Significance. Our results provide insight into the neuronal mechanisms that underlie biological target detection and selection (from a moving platform), as well as highlight the effectiveness of our bio-inspired algorithm in an artificial visual system.
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4. |
- Bagheri, Zahra M, et al.
(author)
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Performance of an insect-inspired target tracker in natural conditions
- 2017
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In: Bioinspiration and Biomimetics. - : IOP Publishing. - 1748-3182 .- 1748-3190. ; 12:2
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Journal article (peer-reviewed)abstract
- Robust and efficient target-tracking algorithms embedded on moving platforms, are a requirement for many computer vision and robotic applications. However, deployment of a real-time system is challenging, even with the computational power of modern hardware. As inspiration, we look to biological lightweight solutions-lightweight and low-powered flying insects. For example, dragonflies pursue prey and mates within cluttered, natural environments, deftly selecting their target amidst swarms. In our laboratory, we study the physiology and morphology of dragonfly 'small target motion detector' neurons likely to underlie this pursuit behaviour. Here we describe our insect-inspired tracking model derived from these data and compare its efficacy and efficiency with state-of-the-art engineering models. For model inputs, we use both publicly available video sequences, as well as our own task-specific dataset (small targets embedded within natural scenes). In the context of the tracking problem, we describe differences in object statistics within the video sequences. For the general dataset, our model often locks on to small components of larger objects, tracking these moving features. When input imagery includes small moving targets, for which our highly nonlinear filtering is matched, the robustness outperforms state-of-the-art trackers. In all scenarios, our insect-inspired tracker runs at least twice the speed of the comparison algorithms.
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5. |
- Bagheri, Zahra M, et al.
(author)
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Properties of neuronal facilitation that improve target tracking in natural pursuit simulations.
- 2015
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In: Journal of the Royal Society Interface. - : The Royal Society. - 1742-5662 .- 1742-5689. ; 12:108
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Journal article (peer-reviewed)abstract
- Although flying insects have limited visual acuity (approx. 1°) and relatively small brains, many species pursue tiny targets against cluttered backgrounds with high success. Our previous computational model, inspired by electrophysiological recordings from insect 'small target motion detector' (STMD) neurons, did not account for several key properties described from the biological system. These include the recent observations of response 'facilitation' (a slow build-up of response to targets that move on long, continuous trajectories) and 'selective attention', a competitive mechanism that selects one target from alternatives. Here, we present an elaborated STMD-inspired model, implemented in a closed loop target-tracking system that uses an active saccadic gaze fixation strategy inspired by insect pursuit. We test this system against heavily cluttered natural scenes. Inclusion of facilitation not only substantially improves success for even short-duration pursuits, but it also enhances the ability to 'attend' to one target in the presence of distracters. Our model predicts optimal facilitation parameters that are static in space and dynamic in time, changing with respect to the amount of background clutter and the intended purpose of the pursuit. Our results provide insights into insect neurophysiology and show the potential of this algorithm for implementation in artificial visual systems and robotic applications.
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6. |
- Bagheri, Zahra, et al.
(author)
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Performance assessment of an insect-inspired target tracking model in background clutter
- 2014
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In: 2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014. - 9781479951994 ; , s. 822-826
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Conference paper (peer-reviewed)abstract
- Biological visual systems provide excellent examples of robust target detection and tracking mechanisms capable of performing in a wide range of environments. Consequently, they have been sources of inspiration for many artificial vision algorithms. However, testing the robustness of target detection and tracking algorithms is a challenging task due to the diversity of environments for applications of these algorithms. Correlation between image quality metrics and model performance is one way to deal with this problem. Previously we developed a target detection model inspired by physiology of insects and implemented it in a closed loop target tracking algorithm. In the current paper we vary the kinetics of a salience-enhancing element of our algorithm and test its effect on the robustness of our model against different natural images to find the relationship between model performance and background clutter.
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7. |
- Bagheri, Zahra, et al.
(author)
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Robustness and real-time performance of an insect inspired target tracking algorithm under natural conditions
- 2015
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In: Proceedings - 2015 IEEE Symposium Series on Computational Intelligence, SSCI 2015. - 9781479975600 ; , s. 97-102
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Conference paper (peer-reviewed)abstract
- Many computer vision tasks require the implementation of robust and efficient target tracking algorithms. Furthermore, in robotic applications these algorithms must perform whilst on a moving platform (ego motion). Despite the increase in computational processing power, many engineering algorithms are still challenged by real-Time applications. In contrast, lightweight and low-power flying insects, such as dragonflies, can readily chase prey and mates within cluttered natural environments, deftly selecting their target amidst distractors (swarms). In our laboratory, we record from 'target-detecting' neurons in the dragonfly brain that underlie this pursuit behavior. We recently developed a closed-loop target detection and tracking algorithm based on key properties of these neurons. Here we test our insect-inspired tracking model in open-loop against a set of naturalistic sequences and compare its efficacy and efficiency with other state-of-The-Art engineering models. In terms of tracking robustness, our model performs similarly to many of these trackers, yet is at least 3 times more efficient in terms of processing speed.
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8. |
- Barnett, Paul D, et al.
(author)
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Motion adaptation and the velocity coding of natural scenes
- 2010
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In: Current Biology. - : Elsevier BV. - 0960-9822 .- 1879-0445. ; 20:11, s. 994-999
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Journal article (peer-reviewed)abstract
- Estimating relative velocity in the natural environment is challenging because natural scenes vary greatly in contrast and spatial structure. Widely accepted correlation-based models for elementary motion detectors (EMDs) are sensitive to contrast and spatial structure and consequently generate ambiguous estimates of velocity [1]. Identified neurons in the third optic lobe of the hoverfly can reliably encode the velocity of natural images largely independent of contrast [2], despite receiving inputs directly from arrays of such EMDs [3, 4]. This contrast invariance suggests an important role for additional neural processes in robust encoding of image motion [2, 5, 6]. However, it remains unclear which neural processes are contributing to contrast invariance. By recording from horizontal system neurons in the hoverfly lobula, we show two activity-dependent adaptation mechanisms acting as near-ideal normalizers for images of different contrasts that would otherwise produce highly variable response magnitudes. Responses to images that are initially weak neural drivers are boosted over several hundred milliseconds. Responses to images that are initially strong neural drivers are reduced over longer time scales. These adaptation mechanisms appear to be matched to higher-order natural image statistics reconciling the neurons' accurate encoding of image velocity with the inherent ambiguity of correlation-based motion detectors.
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9. |
- Barnett, Paul, et al.
(author)
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Retinotopic organization of small-field-target-detecting neurons in the insect visual system.
- 2007
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In: Current Biology. - : Elsevier BV. - 0960-9822 .- 1879-0445. ; 17:7, s. 569-578
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Journal article (peer-reviewed)abstract
- BackgroundDespite having tiny brains and relatively low-resolution compound eyes, many fly species frequently engage in precisely controlled aerobatic pursuits of conspecifics. Recent investigations into high-order processing in the fly visual system have revealed a class of neurons, coined small-target-motion detectors (STMDs), capable of responding robustly to target motion against the motion of background clutter. Despite limited spatial acuity in the insect eye, these neurons display exquisite sensitivity to small targets. ResultsWe recorded intracellularly from morphologically identified columnar neurons in the lobula complex of the hoverfly Eristalis tenax. We show that these columnar neurons with exquisitely small receptive fields, like their large-field counterparts recently described from both male and female flies, have an extreme selectivity for the motion of small targets. In doing so, we provide the first physiological characterization of small-field neurons in female flies. These retinotopically organized columnar neurons include both direction-selective and nondirection-selective classes covering a large area of visual space. ConclusionsThe retinotopic arrangement of lobula columnar neurons sensitive to the motion of small targets makes a strong case for these neurons as important precursors in the local processing of target motion. Furthermore, the continued response of STMDs with such small receptive fields to the motion of small targets in the presence of moving background clutter places further constraints on the potential mechanisms underlying their small-target tuning.
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10. |
- Bekkouche, Bo M.B., et al.
(author)
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Comparison of Transparency and Shrinkage During Clearing of Insect Brains Using Media With Tunable Refractive Index
- 2020
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In: Frontiers in Neuroanatomy. - : Frontiers Media SA. - 1662-5129. ; 14
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Journal article (peer-reviewed)abstract
- Improvement of imaging quality has the potential to visualize previously unseen building blocks of the brain and is therefore one of the great challenges in neuroscience. Rapid development of new tissue clearing techniques in recent years have attempted to solve imaging compromises in thick brain samples, particularly for high resolution optical microscopy, where the clearing medium needs to match the high refractive index of the objective immersion medium. These problems are exacerbated in insect tissue, where numerous (initially air-filled) tracheal tubes branching throughout the brain increase the scattering of light. To date, surprisingly few studies have systematically quantified the benefits of such clearing methods using objective transparency and tissue shrinkage measurements. In this study we compare a traditional and widely used insect clearing medium, methyl salicylate combined with permanent mounting in Permount (“MS/P”) with several more recently applied clearing media that offer tunable refractive index (n): 2,2′-thiodiethanol (TDE), “SeeDB2” (in variants SeeDB2S and SeeDB2G matched to oil and glycerol immersion, n = 1.52 and 1.47, respectively) and Rapiclear (also with n = 1.52 and 1.47). We measured transparency and tissue shrinkage by comparing freshly dissected brains with cleared brains from dipteran flies, with or without addition of vacuum or ethanol pre-treatments (dehydration and rehydration) to evacuate air from the tracheal system. The results show that ethanol pre-treatment is very effective for improving transparency, regardless of the subsequent clearing medium, while vacuum treatment offers little measurable benefit. Ethanol pre-treated SeeDB2G and Rapiclear brains show much less shrinkage than using the traditional MS/P method. Furthermore, at lower refractive index, closer to that of glycerol immersion, these recently developed media offer outstanding transparency compared to TDE and MS/P. Rapiclear protocols were less laborious compared to SeeDB2, but both offer sufficient transparency and refractive index tunability to permit super-resolution imaging of local volumes in whole mount brains from large insects, and even light-sheet microscopy. Although long-term permanency of Rapiclear stored samples remains to be established, our samples still showed good preservation of fluorescence after storage for more than a year at room temperature.
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