Dragonfly visual neurons selectively attend to features in naturalistic scenes

Evans, Bernard J. E.; Fabian, Joseph M.; O’Carroll, David C.; Wiederman, Steven D.

doi:10.1101/2020.09.14.297374

Cited by 3 publications

(6 citation statements)

References 43 publications

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“…This is observed when neurons are firing spikes in bursts, with multiple action potentials occurring in brief succession, followed by a prolonged period of inactivity. The ISIs of the other neurons exhibit a broad log-normal distribution, representative of spike rates observed in previous studies and indicative of non-bursting neurons 7 , 13 , 14 .…”

Section: Resultssupporting

confidence: 67%

“…Animals were presented with a series of visual stimuli for classification, which included small drifting targets, moving bars, moving gratings and textured patterns. The lobula contains many STMD neurons, but three have been well-characterised; the centrifugal STMD, CSTMD1, and two binocular STMD neurons, BSTMD1 and BSTMD2 7 , 13 . Here we analyse recordings from these STMD neurons, as well as an ‘optic flow’ Lobula Tangential Cell 14 .…”

Section: Methodsmentioning

confidence: 99%

“…Here we analyse recordings from these STMD neurons, as well as an ‘optic flow’ Lobula Tangential Cell 14 . Each STMD neuron is identified by its small target selectivity, characteristic receptive field and action potential waveform 5 , 7 , 13 CSTMD1 has a large receptive field with a sharp transition at the visual midline, with targets traversing the contralateral hemisphere with respect to our recording location driving inhibition and the ipsilateral driving strong excitation. BSTMD1 has a large binocular receptive field, with a characteristic graded response in the contralateral hemisphere and a pure spiking response in the ipsilateral hemisphere.…”

Section: Methodsmentioning

confidence: 99%

“…The anatomy of all three STMD neurons presented here have been published elsewhere 5 , 7 , 13 , but we will briefly summarise them here. All three STMD neurons receive input in the lateral midbrain, and in the case of BSTMD1 also the medial lobula.…”

Section: Methodsmentioning

confidence: 99%

“…A subset of neurons in their lobula, the Small Target Motion Detectors (STMDs) are sensitive to the movement of small objects, and likely underlie the detection and tracking of targets during pursuits 4 . Most published work on dragonfly STMDs comes from a particularly interesting neuron, the Centrifugal Small Target Motion Detector neuron (CSTMD1) 5 – 13 . This neuron possesses remarkably complex response properties including predictive gain modulation 6 , 7 , 10 , 11 and selective attention 8 , 12 , proposed to underlie their interception of prey even amidst a swarm.…”

Section: Introductionmentioning

confidence: 99%

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Spike bursting in a dragonfly target-detecting neuron

Fabian

Wiederman

2021

Sci Rep

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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 example 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.

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Section: Resultssupporting

confidence: 67%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Spike bursting in a dragonfly target-detecting neuron

Fabian

Wiederman

2021

Sci Rep

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

Fabian

O’Carroll

Wiederman

2022

Preprint

Self Cite

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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.

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Localized and Long-Lasting Adaptation in Dragonfly Target-Detecting Neurons

Schwarz,

O'Carroll,

Evans

et al. 2024

eNeuro

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Some visual neurons in the dragonfly (Hemicordulia tau) optic lobe respond to small, moving targets, likely underlying their fast pursuit of prey and conspecifics. In response to repetitive targets presented at short intervals, the spiking activity of these “small target motion detector” (STMD) neurons diminishes over time. Previous experiments limited this adaptation by including intertrial rest periods of varying durations. However, the characteristics of this effect have never been quantified. Here, using extracellular recording techniques lasting for several hours, we quantified both the spatial and temporal properties of STMD adaptation. We found that the time course of adaptation was variable across STMD units. In any one STMD, a repeated series led to more rapid adaptation, a minor accumulative effect more akin to habituation. Following an adapting stimulus, responses recovered quickly, though the rate of recovery decreased nonlinearly over time. We found that the region of adaptation is highly localized, with targets displaced by ∼2.5° eliciting a naive response. Higher frequencies of target stimulation converged to lower levels of sustained response activity. We determined that adaptation itself is a target-tuned property, not elicited by moving bars or luminance flicker. As STMD adaptation is a localized phenomenon, dependent on recent history, it is likely to play an important role in closed-loop behavior where a target is foveated in a localized region for extended periods of the pursuit duration.

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Dragonfly visual neurons selectively attend to features in naturalistic scenes

Cited by 3 publications

References 43 publications

Spike bursting in a dragonfly target-detecting neuron

Spike bursting in a dragonfly target-detecting neuron

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

Localized and Long-Lasting Adaptation in Dragonfly Target-Detecting Neurons

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