ORCID Profile
0000-0001-6739-7581
Current Organisation
University of Adelaide
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Publisher: The Company of Biologists
Date: 2019
DOI: 10.1242/JEB.207316
Abstract: Dragonflies pursue and capture tiny prey and conspecifics with extremely high success rates. These moving targets represent a small visual signal on the retina and successful chases require accurate detection and lification by downstream neuronal circuits. This lification has been observed in a population of neurons called Small Target Motion Detectors (STMDs), through a mechanism we termed predictive gain modulation. As targets drift through the neuron's receptive field, spike frequency builds slowly over time. This increased likelihood of spiking or gain is modulated across the receptive field, enhancing sensitivity just ahead of the target's path, with suppression of activity in the remaining surround. Whilst some properties of this mechanism have been described, it is not yet known which stimulus parameters modulate the amount of response gain. Previous work suggested that the strength of gain enhancement was predominantly determined by the duration of the target's prior path. Here we show that predictive gain modulation is more than a slow build-up of responses over time. Rather, the strength of gain is dependent on the velocity of a prior stimulus combined with the current stimulus attributes (e.g. angular size). We also describe response variability as a major challenge of target detecting neurons and propose that the predictive gain modulation's role is to drive neurons towards response saturation, thus minimising neuronal variability despite noisy visual input signals.
Publisher: Society for Neuroscience
Date: 13-09-2019
DOI: 10.1523/JNEUROSCI.1431-19.2019
Abstract: The visual world projects a complex and rapidly changing image onto the retina of many animal species. This presents computational challenges for those animals reliant on visual processing to provide an accurate representation of the world. One such challenge is parsing a visual scene for the most salient targets, such as the selection of prey amid a swarm. The ability to selectively prioritize processing of some stimuli over others is known as 'selective attention'. We recently identified a dragonfly visual neuron called 'Centrifugal Small Target Motion Detector 1′ (CSTMD1) that exhibits selective attention when presented with multiple, equally salient targets. Here we conducted in vivo , electrophysiological recordings from CSTMD1 in wild-caught male dragonflies ( Hemicordulia tau ), while presenting visual stimuli on an LCD monitor. To identify the target selected in any given trial, we uniquely modulated the intensity of the moving targets (frequency tagging). We found that the frequency information of the selected target is preserved in the neuronal response, while the distracter is completely ignored. We also show that the competitive system that underlies selection in this neuron can be biased by the presentation of a preceding target on the same trajectory, even when it is of lower contrast than an abrupt, novel distracter. With this improved method for identifying and biasing target selection in CSTMD1, the dragonfly provides an ideal animal model system to probe the neuronal mechanisms underlying selective attention. SIGNIFICANCE STATEMENT We present the first application of frequency tagging to intracellular neuronal recordings, demonstrating that the frequency component of a stimulus is encoded in the spiking response of an in idual neuron. Using this technique as an identifier, we demonstrate that CSTMD1 'locks on' to a selected target and encodes the absolute strength of this target, even in the presence of abruptly appearing, high-contrast distracters. The underlying mechanism also permits the selection mechanism to switch between targets mid-trial, even among equivalent targets. Together, these results demonstrate greater complexity in this selective attention system than would be expected in a winner-takes-all network. These results are in contrast to typical findings in the primate and avian brain, but display intriguing resemblance to observations in human psychophysics.
Publisher: Springer International Publishing
Date: 2017
Publisher: Cold Spring Harbor Laboratory
Date: 25-03-2021
DOI: 10.1101/2021.03.24.436732
Abstract: Dragonflies are highly skilled and successful aerial predators that are even capable of selectively attending to one target within a swarm. Detection and tracking prey is likely to be driven by small target motion detector (STMD) neurons identified from several insect groups. Prior work has shown that dragonfly STMD responses are facilitated by targets moving on a continuous path, enhancing the response gain at the present and predicted future location of targets. In this study, we combined detailed morphological data with computational modelling to test whether a combination of dendritic morphology combined with the nonlinear properties of NMDA receptors could explain these observations. We developed a hybrid neuronal model of neurons within the dragonfly optic lobe, which integrates numerical and morphological components. The model was able to generate potent facilitation for targets moving on continuous trajectories, including a localized spotlight of maximal sensitivity close to the last seen target location, as also measured during in vivo recordings. The model did not, however, include a mechanism capable of producing a traveling or spreading wave of facilitation. Our data support a strong role for the high dendritic density seen in the dragonfly neuron in enhancing non-linear facilitation. An alternative model based on morphology of an unrelated type of motion processing neuron from a dipteran fly required more than 3 times higher synaptic gain in order to elicit similar levels of facilitation, despite having only 20% fewer synapses. Our data supports a potential role for NMDA receptors in target tracking and also demonstrates the feasibility of combining biologically plausible dendritic computations with more abstract computational models for basic processing as used in earlier studies.
Publisher: Cold Spring Harbor Laboratory
Date: 13-12-2018
DOI: 10.1101/496562
Abstract: The visual world projects a complex and rapidly changing image on to the retina, presenting a computational challenge for any animal relying on vision for an accurate view of the world. One such challenge is parsing a visual scene for the most salient targets, such as the selection of prey amidst a swarm. The ability to selectivity prioritize processing of some stimuli over others is known as selective attention. Previously, we identified a dragonfly visual neuron called Centrifugal Small Target Motion Detector 1 (CSTMD1) that exhibits selective attention when presented with multiple, equally salient features. Here we conducted electrophysiological recordings from CSTMD1 neurons in vivo, whilst presenting visual stimuli on a monitor display. To identify the target selected in any given trial, we modulated the intensity of moving targets, each with a unique frequency (frequency-tagging). We find that the frequency information of the selected stimulus is preserved in the neuronal response, whilst the distracter is completely ignored. We show that the competitive system that underlies selection in this neuron can be biased by the presentation of a preceding target on the same trajectory, even when it is of lower contrast to the distracter. With an improved method of identifying and biasing target selection in CSTMD1, the dragonfly provides an effective animal model system to probe the mechanisms underlying neuronal selective attention.
Publisher: Cold Spring Harbor Laboratory
Date: 11-04-2021
DOI: 10.1101/2021.04.11.439336
Abstract: Can mechanosensors in animal wings allow reconstruction of the wing aeroelastic states? Little is known about how flying animals utilize wing mechanosensation to monitor the dynamic state of their highly deformable wings. Odonata, dragonflies and damselflies, are a basal lineage of flying insects with excellent flight performance, and their wing mechanics have been studied extensively. Here, we present a comprehensive map of the wing sensory system for two Odonata species, including both the external sensor morphologies and internal neuroanatomy. We identified eight morphological classes of sensors most were mechanosensors innervated by a single neuron. Their innervation patterns and morphologies minimize axon length and allow morphological latency compensation. We further mapped the major veins of another 13 Odonata species across 10 families and identified consistent sensor distribution patterns, with sensor count scaling with wing length. Finally, we constructed a high-fidelity finite element model of a dragonfly wing for structural analysis. Our dynamic loading simulations revealed features of the strain fields that wing sensor arrays could detect to encode different wing deformation states. Taken together, this work marks the first step toward an integrated understanding of fly-by-feel control in animal flight.
Publisher: Cold Spring Harbor Laboratory
Date: 16-12-2018
DOI: 10.1101/496885
Abstract: Dragonflies pursue and capture tiny prey and conspecifics with extremely high success rates. These moving targets represent a small visual signal on the retina and successful chases require accurate detection and lification by downstream neuronal circuits. This lification has been observed in a population of neurons called Small Target Motion Detectors (STMDs), through a mechanism we termed predictive gain modulation. As targets drift through the receptive field responses build slowly over time. This gain is modulated across the receptive field, enhancing sensitivity just ahead of the targets path, with suppression of activity elsewhere in the surround. Whilst some properties of this mechanism have been described, it is not yet known which stimulus parameters are required to generate this gain modulation. Previous work suggested that the strength of gain enhancement was predominantly determined by the duration of the targets prior path. Here we show that the predictive gain modulation is more than a sluggish build-up of gain over time. Rather, gain is dependent on both past and present parameters of the stimulus. We also describe response variability as a major challenge of target detecting neurons and propose that the predictive gain modulations role is to drive neurons into response saturation, thus minimising neuronal variability despite noisy visual input signals.
Publisher: Cold Spring Harbor Laboratory
Date: 18-12-2018
DOI: 10.1101/496588
Abstract: An important task for any aerial creature is the ability to ascertain their own movement (ego-motion) through their environment. Neurons thought to underlie this behaviour have been well-characterised in many insect models including flies, moths and bees. However, dragonfly wide-field motion pathways remain undescribed. Some species of Dragonflies, such as Hemicordulia tau, engage in hawking behaviour, hovering in a single area for extended periods of time whilst also engaging in fast-moving patrols and highly dynamic pursuits of prey and conspecifics. These varied flight behaviours place very different constraints on establishing ego-motion from optic flow cues hinting at a sophisticated wide-field motion analysis system capable of detecting both fast and slow motion. We characterised wide-field motion sensitive neurons via intracellular recordings in Hemicordulia dragonflies finding similar properties to those found in other species. We found that the spatial and temporal tuning properties of these neurons were broadly similar but differed significantly in their adaptation to sustained motion. We categorised a total of three different subclasses, finding differences between subclasses in their motion adaptation and response to the broadband statistics of natural images. The differences found correspond well with the dynamics of the varied behavioural tasks hawking dragonflies perform. These findings may underpin the exquisite flight behaviours found in dragonflies. They also hint at the need for the great complexity seen in dragonfly early visual processing.
Publisher: Elsevier BV
Date: 02-2020
Publisher: Springer Science and Business Media LLC
Date: 29-04-2021
DOI: 10.1038/S41598-021-89240-1
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Publisher: Cold Spring Harbor Laboratory
Date: 29-01-2022
DOI: 10.1101/2022.01.28.478240
Abstract: Animals live in highly dynamic worlds, utilising sensorimotor circuits to rapidly process information and drive behaviours. For ex le, dragonflies are aerial predators which react to movements of prey within tens of milliseconds. These pursuits are likely controlled by identified neurons in the dragonfly, which have well-characterized physiological responses to moving targets. Predominantly, neural activity in these circuits are interpreted in the context of a rate code, where information is conveyed by changes in the number of spikes over a given time. However, such a description of neuronal activity is difficult to achieve in real-world, real-time scenarios. Here, we contrast a neuroscientists’ post-hoc view of spiking activity with the information available to the animal in real-time. We describe how performance of a rate code is readily overestimated and outline a rate code’s significant limitations in driving rapid behaviours.
Publisher: Frontiers Media SA
Date: 16-08-2021
DOI: 10.3389/FNCIR.2021.684872
Abstract: Dragonflies are highly skilled and successful aerial predators that are even capable of selectively attending to one target within a swarm. Detection and tracking of prey is likely to be driven by small target motion detector (STMD) neurons identified from several insect groups. Prior work has shown that dragonfly STMD responses are facilitated by targets moving on a continuous path, enhancing the response gain at the present and predicted future location of targets. In this study, we combined detailed morphological data with computational modeling to test whether a combination of dendritic morphology and nonlinear properties of NMDA receptors could explain these observations. We developed a hybrid computational model of neurons within the dragonfly optic lobe, which integrates numerical and morphological components. The model was able to generate potent facilitation for targets moving on continuous trajectories, including a localized spotlight of maximal sensitivity close to the last seen target location, as also measured during in vivo recordings. The model did not, however, include a mechanism capable of producing a traveling or spreading wave of facilitation. Our data support a strong role for the high dendritic density seen in the dragonfly neuron in enhancing non-linear facilitation. An alternative model based on the morphology of an unrelated type of motion processing neuron from a dipteran fly required more than three times higher synaptic gain in order to elicit similar levels of facilitation, despite having only 20% fewer synapses. Our data support a potential role for NMDA receptors in target tracking and also demonstrate the feasibility of combining biologically plausible dendritic computations with more abstract computational models for basic processing as used in earlier studies.
Publisher: eLife Sciences Publications, Ltd
Date: 25-07-2017
DOI: 10.7554/ELIFE.26478
Abstract: When a human catches a ball, they estimate future target location based on the current trajectory. How animals, small and large, encode such predictive processes at the single neuron level is unknown. Here we describe small target-selective neurons in predatory dragonflies that exhibit localized enhanced sensitivity for targets displaced to new locations just ahead of the prior path, with suppression elsewhere in the surround. This focused region of gain modulation is driven by predictive mechanisms, with the direction tuning shifting selectively to match the target’s prior path. It involves a large local increase in contrast gain which spreads forward after a delay (e.g. an occlusion) and can even transfer between brain hemispheres, predicting trajectories moved towards the visual midline from the other eye. The tractable nature of dragonflies for physiological experiments makes this a useful model for studying the neuronal mechanisms underlying the brain’s remarkable ability to anticipate moving stimuli.
Publisher: Cold Spring Harbor Laboratory
Date: 12-05-2020
DOI: 10.1101/2020.05.10.087437
Abstract: Dragonflies represent an ancient lineage of visual predators, which last shared a common ancestor with insect groups such as dipteran flies in the early Devonian, 406 million years ago [1,2]. Despite their important evolutionary status, and recent interest in them as a model for complex visual physiology and behavior, the most recent detailed description of the dragonfly optic lobe is itself more than a century old [3]. Many insects process visual information in optic lobes comprising 4 sequential, retinotopically organized neuropils: the lamina, medulla, lobula and a posterior lobula plate devoted to processing information about wide-field motion stimuli [4, 5]. Recent reports suggest that the dragonflies also follow this basic plan, with a ided lobula similar to those of flies, moths and butterflies [6, 7]. Here we refute this claim, showing that dragonflies have an unprecedentedly complex lobula comprising at least 4 sequential synaptic neuropils, in addition to two lobula plate like structures located on opposite sides of the brain. The second and third optic ganglia contain approximately twice as many synaptic layers as any other insect group yet studied. Using intracellular recording and labeling of neurons we further show that the most anterior lobe contains wide-field motion processing tangential neurons similar to those of the posterior lobula plate of dipteran flies. In addition to describing what is probably the most complex and unique optic lobe of any insect to date, our findings provide interesting insights to understanding the evolution of the insect optic lobe and serve as a reminder that the highly studied visual circuits of dipteran flies represent just a single derived form of these brain structures.
Publisher: eLife Sciences Publications, Ltd
Date: 20-05-2017
Publisher: Springer Science and Business Media LLC
Date: 17-02-2021
DOI: 10.1038/S41598-021-83559-5
Abstract: Dragonflies visually detect prey and conspecifics, rapidly pursuing these targets via acrobatic flights. Over many decades, studies have investigated the elaborate neuronal circuits proposed to underlie this rapid behaviour. A subset of dragonfly visual neurons exhibit exquisite tuning to small, moving targets even when presented in cluttered backgrounds. In prior work, these neuronal responses were quantified by computing the rate of spikes fired during an analysis window of interest. However, neuronal systems can utilize a variety of neuronal coding principles to signal information, so a spike train’s information content is not necessarily encapsulated by spike rate alone. One ex le of this is burst coding, where neurons fire rapid bursts of spikes, followed by a period of inactivity. Here we show that the most studied target-detecting neuron in dragonflies, CSTMD1, responds to moving targets with a series of spike bursts. This spiking activity differs from those in other identified visual neurons in the dragonfly, indicative of different physiological mechanisms underlying CSTMD1’s spike generation. Burst codes present several advantages and disadvantages compared to other coding approaches. We propose functional implications of CSTMD1’s burst coding activity and show that spike bursts enhance the robustness of target-evoked responses.
Publisher: Cold Spring Harbor Laboratory
Date: 20-03-2020
DOI: 10.1101/2020.03.18.996173
Abstract: Nanoparticles with desirable properties and functions have been actively developed for various bio-medical research, such as in vivo and in vitro sensors, imaging agents and delivery vehicles of therapeutics. However, an effective method to deliver nanoparticles into the intracellular environment is a major challenge and critical to many biological studies. Current techniques, such as intracellular uptake, electroporation and microinjection, each have their own set of benefits and associated limitations ( e.g. , aggregation and endosomal degradation of nanoparticles, high cell mortality and low throughput). Here, the well-established microelectrophoresis technique is applied for the first time to deliver nanoparticles into target cells, which overcomes some of these delivery difficulties. Semiconductive quantum dots, with average hydrodynamic diameter of 24.4 nm, have been successfully ejected via small electrical currents (−0.2 nA) through fine-tipped glass micropipettes as an ex le, into living human embryonic kidney cells (roughly 20 - 30μm in length). As proposed by previous studies, micropipettes were fabricated to have an average tip inner diameter of 206 nm for ejection but less than 500 nm to minimize the cell membrane damage and cell distortion. In addition, delivered quantum dots were found to stay monodispersed within the cells for approximately one hour. We believe that microelectrophoresis technique may serve as a simple and general strategy for delivering a variety of nanoparticles intracellularly in various biological systems.
Publisher: Society for Neuroscience
Date: 03-09-2019
DOI: 10.1523/JNEUROSCI.0143-19.2019
Abstract: Visual cues provide an important means for aerial creatures to ascertain their self-motion through the environment. In many insects, including flies, moths, and bees, wide-field motion-sensitive neurons in the third optic ganglion are thought to underlie such motion encoding however, these neurons can only respond robustly over limited speed ranges. The task is more complicated for some species of dragonflies that switch between extended periods of hovering flight and fast-moving pursuit of prey and conspecifics, requiring motion detection over a broad range of velocities. Since little is known about motion processing in these insects, we performed intracellular recordings from hawking, emerald dragonflies ( Hemicordulia spp. ) and identified a erse group of motion-sensitive neurons that we named lobula tangential cells (LTCs). Following prolonged visual stimulation with drifting gratings, we observed significant differences in both temporal and spatial tuning of LTCs. Cluster analysis of these changes confirmed several groups of LTCs with distinctive spatiotemporal tuning. These differences were associated with variation in velocity tuning in response to translated, natural scenes. LTCs with differences in velocity tuning ranges and optima may underlie how a broad range of motion velocities are encoded. In the hawking dragonfly, changes in LTC tuning over time are therefore likely to support their extensive range of behaviors, from hovering to fast-speed pursuits. SIGNIFICANCE STATEMENT Understanding how animals navigate the world is an inherently difficult and interesting problem. Insects are useful models for understanding neuronal mechanisms underlying these activities, with neurons that encode wide-field motion previously identified in insects, such as flies, hawkmoths, and butterflies. Like some Dipteran flies, dragonflies exhibit complex aerobatic behaviors, such as hovering, patrolling, and aerial combat. However, dragonflies lack halteres that support such erse behavior in flies. To understand how dragonflies might address this problem using only visual cues, we recorded from their wide-field motion-sensitive neurons. We found these differ strongly in the ways they respond to sustained motion, allowing them collectively to encode the very broad range of velocities experienced during erse behavior.
Publisher: Cold Spring Harbor Laboratory
Date: 16-09-2020
DOI: 10.1101/2020.09.14.297374
Abstract: Aerial predators, such as the dragonfly, determine the position and movement of their prey even when embedded in natural scenes. This task is likely supported by a group of optic lobe neurons with responses selective for moving targets of less than a few degrees. These Small Target Motion Detector (STMD) neurons are tuned to target velocity and show profound facilitation in responses to targets that move along continuous trajectories. When presented with a pair of targets, some STMDs competitively select one of the alternatives as if the other does not exist. Here we describe intracellular responses of STMD neurons to the visual presentation of many potential alternatives within cluttered environments comprised of natural scenes. We vary both target contrast and the background scene, across a range of target and background velocities. We find that background motion affects STMD responses indirectly, via the competitive selection of background features. We find that robust target discrimination is limited to scenarios when the target velocity is matched to, or greater than, background velocity. Furthermore, STMD target discriminability is modified by background direction. Backgrounds that move in the neuron’s anti-preferred direction result in the least performance degradation. Biological brains solve the difficult problem of visually detecting and tracking moving features in cluttered environments. We investigated this neuronal processing by recording intracellularly from dragonfly visual neurons that encode the motion of small moving targets subtending less than a few degrees (e.g. prey and conspecifics). However, dragonflies live in a complex visual environment where background features may interfere with tracking by reducing target contrast or providing competitive cues. We find that selective attention towards features drives much of the neuronal response, with background clutter competing with target stimuli for selection. Moreover, the velocity of features is an important component in determining the winner in these competitive interactions.
Publisher: Wiley
Date: 11-03-2021
Abstract: Nanoparticles with specific properties and functions have been developed for various biomedical research applications, such as in vivo and in vitro sensors, imaging agents and delivery vehicles of therapeutics. The development of an effective delivery method of nanoparticles into the intracellular environment is challenging and success in this endeavor would be beneficial to many biological studies. Here, the well‐established microelectrophoresis technique was applied for the first time to deliver nanoparticles into living cells. An optimal protocol was explored to prepare semiconductive quantum dots suspensions having high monodispersity with average hydrodynamic diameter of 13.2–35.0 nm. Micropipettes were fabricated to have inner tip diameters of approximately 200 nm that are larger than quantum dots for ejection but less than 500 nm to minimize damage to the cell membrane. We demonstrated the successful delivery of quantum dots via small electrical currents (–0.2 nA) through micropipettes into the cytoplasm of living human embryonic kidney cells (roughly 20–30 μm in length) using microelectrophoresis technique. This method is promising as a simple and general strategy for delivering a variety of nanoparticles into the cellular environment.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Joseph Fabian.