Biology subjects

Wiederman, S. D.

Publications and source records attributed to Wiederman, S. D..

7 recordsLinked to original sources

bioRxiv2022

Sparse spike trains and the limitations of rate codes underlying rapid behaviour

Animals live in highly dynamic worlds, utilising sensorimotor circuits to rapidly process information and drive behaviours. For example, 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 codes significant limitations in driving rapid behaviours.

neuroscience↗

bioRxiv2021

Modelling nonlinear dendritic processing of facilitation in a dragonfly target-tracking neuron

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.

neuroscience↗

bioRxiv2020

Dragonfly visual neurons selectively attend to features in naturalistic scenes

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 neurons anti-preferred direction result in the least performance degradation. Significance StatementBiological 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.

physiology↗

bioRxiv2020

The complex optic lobe of dragonflies

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 divided 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.

neuroscience↗

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↗