Biology subjects

Fabian, J. M.

Publications and source records attributed to Fabian, J. M..

3 recordsLinked to original sources

bioRxiv2018

Differential adaptation to visual motion allows robust encoding of optic flow in the dragonfly

1An important task for any aerial creature is the ability to ascertain their own movement (egomotion) 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.\n\nWe 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.\n\n2 Significance StatementUnderstanding how animals navigate the world is an inherently difficult and interesting problem. Insect models have elucidated the neuronal mechanisms, which underpin this process. Neurons that encode wide-field motion have been studied previously in insects such as flies, hawkmoths and butterflies. Dragonflies exhibit complex aerobatic behaviours such as hovering, patrolling and aerial combat but little is known of their optic physiology. Moreover, dragonflies lack multimodal inputs (such as halteres in flies), which help enable diverse behaviours. The present study characterises wide-field motion sensitive neurons in the dragonfly. We find that wide-field motion sensitive neurons in dragonflies exhibit multiple subtypes, differentiated by their motion adaptation enabling encoding of a broad range of velocities independent of background contrast.

neuroscience↗

bioRxiv2018

Properties of Predictive Gain Modulation in a Dragonfly Visual Neuron

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 amplification by downstream neuronal circuits. This amplification 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.

neuroscience↗

bioRxiv2018

Target-detecting neurons in the dragonfly lock on to selectively attended targets

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.\n\nSignificance StatementThis is a novel application of frequency tagging at the intracellular level, demonstrating that frequency information of a flickering stimulus is preserved in the response of an individual neuron. Using this technique, we show that the selective attention mechanism in an individual dragonfly visual neuron is able to lock on to the selected stimuli, in the presence of distracters, even those of abrupt onset or higher contrast. Conversely, unidentified factors allow selection to occasionally switch mid-trial to the other target. We therefore show that this neuronal network underlying selective attention is more complex than the traditionally modelled winner-takes-all framework.

neuroscience↗