ORCID Profile
0000-0002-0902-803X
Current Organisation
University of Adelaide
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Artificial Intelligence and Image Processing not elsewhere classified | Sensory Systems | Neurosciences | Autonomous Vehicles | Control Systems, Robotics and Automation
ANZSRC Socio-Economic Objective (SEO)
Emerging Defence Technologies | Expanding Knowledge in Engineering | Expanding Knowledge in the Biological Sciences |
Related Links
Publications
Dragonfly Neurons Selectively Attend to Targets Within Natural Scenes
Publisher: Frontiers Media SA
Date: 05-04-2022
DOI: 10.3389/FNCEL.2022.857071
Abstract: Aerial predators, such as the dragonfly, determine the position and movement of their prey even when both are moving through complex, natural scenes. This task is likely supported by a group of neurons in the optic lobe which respond to moving targets that subtend less than a few degrees. These Small Target Motion Detector (STMD) neurons are tuned to both target size and velocity, whilst also exhibiting facilitated responses to targets traveling along continuous trajectories. When presented with a pair of targets, some STMDs generate spiking activity that represent a competitive selection of one target, as if the alternative does not exist (i.e., selective attention). Here, we describe intracellular responses of CSTMD1 (an identified STMD) to the visual presentation of targets embedded within cluttered, natural scenes. We examine CSTMD1 response changes to target contrast, as well as a range of target and background velocities. We find that background motion affects CSTMD1 responses via the competitive selection between features within the natural scene. Here, robust discrimination of our artificially embedded “target” is limited to scenarios when its velocity is matched to, or greater than, the background velocity. Additionally, the background’s direction of motion affects discriminability, though not in the manner observed in STMDs of other flying insects. Our results highlight that CSTMD1’s competitive responses are to those features best matched to the neuron’s underlying spatiotemporal tuning, whether from the embedded target or other features in the background clutter. In many scenarios, CSTMD1 responds robustly to targets moving through cluttered scenes. However, whether this neuronal system could underlie the task of competitively selecting slow moving prey against fast-moving backgrounds remains an open question.
Multi-focal video fusion with a beam splitter prism
Publisher: IEEE
Date: 11-2015
Bio-inspired small target discrimination in high dynamic range natural scenes
Publisher: IEEE
Date: 09-2008
Facilitation of dragonfly target-detecting neurons by slow moving features on continuous paths
Publisher: Frontiers Media SA
Date: 2012
Differential adaptation to visual motion allows robust encoding of optic flow in the dragonfly
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.
Performance assessment of an insect-inspired target tracking model in background clutter
Publisher: IEEE
Date: 12-2014
A predictive focus of gain modulation encodes target trajectories in insect vision
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.
Modeling Nonlinear Dendritic Processing of Facilitation in a Dragonfly Target-Tracking Neuron
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.
Controlled delivery of quantum dots using microelectrophoresis technique: Intracellular behavior and preservation of cell viability
Publisher: Elsevier BV
Date: 04-2022
DOI: 10.1016/J.BIOELECHEM.2021.108035
Abstract: The use of synthetic nanomaterials as contrast agents, sensors, and drug delivery vehicles in biological research primarily requires effective approaches for intracellular delivery. Recently, the well-accepted microelectrophoresis technique has been reported to exhibit the ability to deliver nanomaterials, quantum dots (QDs) as an ex le, into live cells, but information about cell viability and intracellular fate of delivered nanomaterials is yet to be provided. Here we show that cell viability following microelectrophoresis of QDs is strongly correlated with the amount of delivered QDs, which can be finely controlled by tuning the ejection duration to maintain long-term cell survival. We reveal that microelectrophoretic delivered QDs distribute homogeneously and present pure Brownian diffusion inside the cytoplasm without endosomal entrapment, having great potential for the study of dynamic intracellular events. We validate that microelectrophoresis is a powerful technique for the effective intracellular delivery of QDs and potentially various functional nanomaterials in biological research.
Biologically Inspired Small Target Detection Mechanisms
Publisher: IEEE
Date: 2007
Can a competitive neural network explain selective attention in insect target tracking neurons?
Publisher: IEEE
Date: 11-2013
Bio-inspired feature extraction and enhancement of targets moving against visual clutter during closed loop pursuit
Publisher: IEEE
Date: 09-2013
Modeling inhibitory interactions shaping neural responses of target neurons to multiple features
Publisher: IEEE
Date: 12-2011
Discrimination of Features in Natural Scenes by a Dragonfly Neuron
Publisher: Society for Neuroscience
Date: 11-05-2011
DOI: 10.1523/JNEUROSCI.0970-11.2011
Abstract: Flying insects engage in spectacular high-speed pursuit of targets, requiring visual discrimination of moving objects against cluttered backgrounds. As a first step toward understanding the neural basis for this complex task, we used computational modeling of insect small target motion detector (STMD) neurons to predict responses to features within natural scenes and then compared this with responses recorded from an identified STMD neuron in the dragonfly brain ( Hemicordulia tau ). A surprising model prediction confirmed by our electrophysiological recordings is that even heavily cluttered scenes contain very few features that excite these neurons, due largely to their exquisite tuning for small features. We also show that very subtle manipulations of the image cause dramatic changes in the response of this neuron, because of the complex inhibitory and facilitatory interactions within the receptive field.
Multicompartment Simulations of NMDA Receptor Based Facilitation in an Insect Target Tracking Neuron
Publisher: Springer International Publishing
Date: 2017
A Biologically Inspired Facilitation Mechanism Enhances the Detection and Pursuit of Targets of Varying Contrast
Publisher: IEEE
Date: 11-2014
Biomimetic target detection: Modeling 2<sup>nd</sup> order correlation of OFF and ON channels
Publisher: IEEE
Date: 04-2013
The visual neuroecology of anisoptera
Publisher: Elsevier BV
Date: 12-2020
The complex optic lobe of dragonflies
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.
Intracellular Delivery of Nanoparticles via Microelectrophoresis Technique: Feasibility demonstration
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.
Performance of a bio-inspired model for the robust detection of moving targets in high dynamic range natural scenes
Publisher: American Scientific Publishers
Date: 05-2010
Differential tuning to visual motion allows robust encoding of optic flow in the dragonfly
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.
Quantifying asynchrony of multiple cameras using aliased optical devices
Publisher: IEEE
Date: 11-2015
Dragonfly visual neurons selectively attend to features in naturalistic scenes
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.
Cytoplasmic delivery of quantum dots via microelectrophoresis technique
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.
Visual acuity of the honey bee retina and the limits for feature detection
Publisher: Springer Science and Business Media LLC
Date: 06-04-2017
DOI: 10.1038/SREP45972
Abstract: Visual abilities of the honey bee have been studied for more than 100 years, recently revealing unexpectedly sophisticated cognitive skills rivalling those of vertebrates. However, the physiological limits of the honey bee eye have been largely unaddressed and only studied in an unnatural, dark state. Using a bright display and intracellular recordings, we here systematically investigated the angular sensitivity across the light adapted eye of honey bee foragers. Angular sensitivity is a measure of photoreceptor receptive field size and thus small values indicate higher visual acuity. Our recordings reveal a fronto-ventral acute zone in which angular sensitivity falls below 1.9°, some 30% smaller than previously reported. By measuring receptor noise and responses to moving dark objects, we also obtained direct measures of the smallest features detectable by the retina. In the frontal eye, single photoreceptors respond to objects as small as 0.6° × 0.6°, with % reliability. This indicates that honey bee foragers possess significantly better resolution than previously reported or estimated behaviourally, and commonly assumed in modelling of bee acuity.
A Model for the Detection of Moving Targets in Visual Clutter Inspired by Insect Physiology
Publisher: Public Library of Science (PLoS)
Date: 30-07-2008
Correlation between OFF and ON Channels Underlies Dark Target Selectivity in an Insect Visual System
Publisher: Society for Neuroscience
Date: 07-08-2013
Properties of predictive gain modulation in a dragonfly visual neuron
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.
Discrete implementation of biologically inspired image processing for target detection
Publisher: IEEE
Date: 12-2011
Biologically Inspired Feature Detection Using Cascaded Correlations of off and on Channels
Publisher: Walter de Gruyter GmbH
Date: 2013
Abstract: Flying insects are valuable animal models for elucidating computational processes underlying visual motion detection. For ex le, optical flow analysis by wide-field motion processing neurons in the insect visual system has been investigated from both behavioral and physiological perspectives [1]. This has resulted in useful computational models with erse applications [2,3]. In addition, some insects must also extract the movement of their prey or conspecifics from their environment. Such insects have the ability to detect and interact with small moving targets, even amidst a swarm of others [4,5]. We use electrophysiological techniques to record from small target motion detector (STMD) neurons in the insect brain that are likely to subserve these behaviors. Inspired by such recordings, we previously proposed an ‘elementary’ small target motion detector (ESTMD) model that accounts for the spatial and temporal tuning of such neurons and even their ability to discriminate targets against cluttered surrounds [6-8]. However, other properties such as direction selectivity [9] and response facilitation for objects moving on extended trajectories [10] are not accounted for by this model. We therefore propose here two model variants that cascade an ESTMD model with a traditional motion detection model algorithm, the Hassenstein Reichardt ‘elementary motion detector’ (EMD) [11]. We show that these elaborations maintain the principal attributes of ESTMDs (i.e. spatiotemporal tuning and background clutter rejection) while also capturing the direction selectivity observed in some STMD neurons. By encapsulating the properties of biological STMD neurons we aim to develop computational models that can simulate the remarkable capabilities of insects in target discrimination and pursuit for applications in robotics and artificial vision systems.
A target-detecting visual neuron in the dragonfly locks on to selectively attended targets
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.
Bio-inspired target detection in natural scenes: Optimal thresholds and ego-motion
Publisher: SPIE
Date: 28-08-2008
DOI: 10.1117/12.804351
Recurrent Motion Neural Network for Low Resolution Drone Detection
Publisher: IEEE
Date: 29-11-2020
Photoreceptor signalling is sufficient to explain the detectability threshold of insect aerial pursuers
Publisher: The Company of Biologists
Date: 12-2017
DOI: 10.1242/JEB.166207
Abstract: An essential biological task for many flying insects is the detection of small, moving targets, such as when pursuing prey or conspecifics. Neural pathways underlying such ‘target-detecting’ behaviours have been investigated for their sensitivity and tuning properties (size, velocity). However, which stage of neuronal processing limits target detection is not yet known. Here, we investigated several skilled, aerial pursuers (males of four insect species), measuring the target-detection limit (signal-to-noise ratio) of light-adapted photoreceptors. We recorded intracellular responses to moving targets of varying size, extended well below the nominal resolution of single ommatidia. We found that the signal detection limit (2× photoreceptor noise) matches physiological or behavioural target-detection thresholds observed in each species. Thus, across a erse range of flying insects, in idual photoreceptor responses to changes in light intensity establish the sensitivity of the feature detection pathway, indicating later stages of processing are dedicated to feature tuning, tracking and selection.
Properties of predictive gain modulation in a dragonfly visual neuron
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.
Preattentive facilitation of target trajectories in a dragonfly visual neuron
Publisher: Springer Science and Business Media LLC
Date: 18-08-2022
DOI: 10.1038/S42003-022-03798-8
Abstract: The ability to pursue targets in visually cluttered and distraction-rich environments is critical for predators such as dragonflies. Previously, we identified Centrifugal Small-Target Motion Detector 1 (CSTMD1), a dragonfly visual neuron likely involved in such target-tracking behaviour. CSTMD1 exhibits facilitated responses to targets moving along a continuous trajectory. Moreover, CSTMD1 competitively selects a single target out of a pair. Here, we conducted in vivo, intracellular recordings from CSTMD1 to examine the interplay between facilitation and selection, in response to the presentation of paired targets. We find that neuronal responses to both in idual trajectories of simultaneous, paired targets are facilitated, rather than being constrained to the single, selected target. Additionally, switches in selection elicit suppression which is likely an important attribute underlying target pursuit. However, binocular experiments reveal these results are constrained to paired targets within the same visual hemifield, while selection of a target in one visual hemifield establishes ocular dominance that prevents facilitation or response to contralaterally presented targets. These results reveal that the dragonfly brain preattentively represents more than one target trajectory, to balance between attentional flexibility and resistance against distraction.
Sparse spike trains and the limitations of rate codes underlying rapid behaviour
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.
Author response: A predictive focus of gain modulation encodes target trajectories in insect vision
Publisher: eLife Sciences Publications, Ltd
Date: 20-05-2017
Assessment outcome is weakly correlated with lecture attendance: influence of learning style and use of alternative materials
Publisher: American Physiological Society
Date: 06-2012
Abstract: The relation between lecture attendance and learning is surprisingly weak, and the role of learning styles in this is poorly understood. We hypothesized that 1) academic performance is related to lecture attendance and 2) learning style influences lecture attendance and, consequently, affects performance. We also speculated that the availability of alternative resources would affect this relationship. Second-year Bachelor of Science physiology students ( n = 120) self-reported their lecture attendance in a block of 21 lectures (attendance not compulsory) and use of alternative resources. Overall self-reported lecture attendance was 73 ± 2%. Female students ( n = 71) attended more lectures (16.4 ± 0.6) than male students (14.3 ± 0.08, n = 49) and achieved a higher composite mark in all assessments (73.6% vs. 69.3%, P 0.02). Marks in the final exam were not statistically different between the sexes and correlated only weakly with lecture attendance ( r = 0.29, n = 49, P 0.04 for male students r = 0.10, n = 71, P = not significant for female students and r =0.21, n = 120, P 0.02 for the whole class). Of the students who passed the exam, poor attenders ( lectures) reported significantly more use of lecture recordings (37 ± 8%, n = 15, vs. 10 ± 1%, n = 85, P 0.001). In a VARK learning style assessment (where V is visual, A is auditory, R is reading/writing, and K is kinesthetic), students were multimodal, although female students had a slightly higher average percentage of the R learning style (preferred read/write) compared with male students (28.9 ± 0.9%, n = 63, vs. 25.3 ± 1.3%, n = 32, P 0.03). Lecture attendance was not correlated with measured learning style. We concluded that lecture attendance is only weakly correlated with academic performance and is not related to learning style. The substitution of alternative materials for lecture attendance appears to have a greater role than learning style in determining academic outcomes.
Performance of an insect-inspired target tracker in natural conditions
Publisher: IOP Publishing
Date: 16-02-2017
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 ex le, 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.
Modelling the temporal response properties of an insect small target motion detector
Publisher: IEEE
Date: 12-2011
Contrast sensitivity and the detection of moving patterns and features
Publisher: The Royal Society
Date: 19-02-2014
Abstract: Theories based on optimal s ling by the retina have been widely applied to visual ecology at the level of the optics of the eye, supported by visual behaviour. This leads to speculation about the additional processing that must lie in between—in the brain itself. But fewer studies have adopted a quantitative approach to evaluating the detectability of specific features in these neural pathways. We briefly review this approach with a focus on contrast sensitivity of two parallel pathways for motion processing in insects, one used for analysis of wide-field optic flow, the other for detection of small features. We further use a combination of optical modelling of image blur and physiological recording from both photoreceptors and higher-order small target motion detector neurons sensitive to small targets to show that such neurons operate right at the limits imposed by the optics of the eye and the noise level of single photoreceptors. Despite this, and the limitation of only being able to use information from adjacent receptors to detect target motion, they achieve a contrast sensitivity that rivals that of wide-field motion sensitive pathways in either insects or vertebrates—among the highest in absolute terms seen in any animal.
Properties of neuronal facilitation that improve target tracking in natural pursuit simulations
Publisher: The Royal Society
Date: 07-2015
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.
Modelling nonlinear dendritic processing of facilitation in a dragonfly target-tracking neuron
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.
Target-detecting neurons in the dragonfly ‘lock on’ to selectively attended targets
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.
Salience invariance with divisive normalization in higher-order insect neurons
Publisher: IEEE
Date: 10-2016
An autonomous robot inspired by insect neurophysiology pursues moving features in natural environments
Publisher: IOP Publishing
Date: 13-07-2017
Abstract: 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. 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. 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. 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.
Spike bursting in a dragonfly target-detecting neuron
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.
Selective Attention in an Insect Visual Neuron
Publisher: Elsevier BV
Date: 2013
DOI: 10.1016/J.CUB.2012.11.048
Abstract: Animals need attention to focus on one target amid alternative distracters. Dragonflies, for ex le, capture flies in swarms comprising prey and conspecifics, a feat that requires neurons to select one moving target from competing alternatives. Diverse evidence, from functional imaging and physiology to psychophysics, highlights the importance of such "competitive selection" in attention for vertebrates. Analogous mechanisms have been proposed in artificial intelligence and even in invertebrates, yet direct neural correlates of attention are scarce from all animal groups. Here, we demonstrate responses from an identified dragonfly visual neuron that perfectly match a model for competitive selection within limits of neuronal variability (r(2) = 0.83). Responses to in idual targets moving at different locations within the receptive field differ in both magnitude and time course. However, responses to two simultaneous targets exclusively track those for one target alone rather than any combination of the pair. Irrespective of target size, contrast, or separation, this neuron selects one target from the pair and perfectly preserves the response, regardless of whether the "winner" is the stronger stimulus if presented alone. This neuron is amenable to electrophysiological recordings, providing neuroscientists with a new model system for studying selective attention.
Robustness and Real-Time Performance of an Insect Inspired Target Tracking Algorithm Under Natural Conditions
Publisher: IEEE
Date: 12-2015
DOI: 10.1109/SSCI.2015.24
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ARC Future Fellowships - Grant ID: FT180100466
Start Date: 10-2018
End Date: 10-2023
Amount: $857,189.00
Funder: Australian Research Council
View Funded ActivityDiscovery Early Career Researcher Award - Grant ID: DE150100548
Start Date: 2015
End Date: 03-2018
Amount: $359,000.00
Funder: Australian Research Council
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