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A predictive focus of gain modulation encodes target trajectories in insect vision
Open accessAbstract
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.
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![Figure 7. Direction selectivity is a result of spatial facilitation. (A) The direction experiment is repeated, now with a 4° jump forward into the spotlight. (B) Responses are facilitated for all directions (mean ± SEM, n = 5 dragonflies) with decreased direction selectivity (b1/b0). (C) Probes in the opposite direction to their corresponding primer reveal no facilitation or inhibition, except when jumped [J] into the spotlight (p=0.03). (D) The magnitude of direction selectivity builds on a faster timescale than the response onset. DOI: http://dx.doi.org/10.7554/eLife.26478.013](/paper-figures/645f8fd8f7a44631959868ac1ab59970/a-predictive-focus-of-gain-modulation-encodes-target-trajectories-in-insect-figure-7.jpg)

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“For example, neurons in the dragonfly visual lobes sensitive specifically to small moving targets show a modulated gain of function that predicts the anticipated position of the target based on its current trajectory [79].”
From Phenomenal interface theory: a model for basal consciousness (2025) · cites this paper as [79]
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“For example, neurons in the dragonfly visual lobes sensitive specifically to small moving targets show a modulated gain of function that predicts the anticipated position of the target based on its current trajectory [79].”
Metadata
- Authors
- Wiederman, S. D., Fabian, J. M., Dunbier, J. R., & O’Carroll, D. C.
- Affiliations
- The University of Adelaide (AU)
- Lund University (SE)
- Corresponding author
- Wiederman, Steven D
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2017-07-25
- Volume
- 6
- ISSN
- 2050-084X (ISSN-L)
- PMC
- PMC5526664
- OpenAlex
- W2737016124
- Cited by
- 68
- References
- 43
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 6 · 2023: 10 · 2022: 13 · 2021: 9 · 2020: 11 · 2019: 5 · 2018: 6 · 2017: 3
- FWCI
- 3.93
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- eLife (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Lund University Publications (Lund University) (submittedVersion)
- Funders
- Australian Research Council (DE150100548, DP130104572)
- Vetenskapsrådet (VR 2014-4904)
- Swedish Foundation for International Cooperation in Research and Higher Education (STINT 2012-2033)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurobiology and Insect Physiology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Keywords
- gain modulation, predictive coding, trajectory prediction, dragonflies, direction tuning, contrast gain, occlusion, interhemispheric transfer, insect vision
- MeSH terms
- Animals, Motion Perception, Neurons, Vision, Ocular, Odonata
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