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Modeling Nonlinear Dendritic Processing of Facilitation in a Dragonfly Target-Tracking Neuron.

Bo M B Bekkouche1, Patrick A Shoemaker2, Joseph M Fabian3

  • 1Department of Biology, Lund University, Lund, Sweden.

Frontiers in Neural Circuits
|September 6, 2021
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Summary
This summary is machine-generated.

Dragonfly neurons enhance prey tracking through dendritic morphology and NMDA receptor properties. This computational model explains how dragonflies focus on moving targets, aiding aerial predation.

Keywords:
BSTMD1NMDASTMDdragonflyfacilitationinsect brainlobulasmall target motion detector

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Area of Science:

  • Neuroscience
  • Computational Biology
  • Insect Physiology

Background:

  • Dragonflies are adept aerial predators, selectively tracking prey within swarms.
  • Small target motion detector (STMD) neurons are crucial for insect prey detection and tracking.
  • Dragonfly STMDs show enhanced responses to continuously moving targets.

Purpose of the Study:

  • To investigate if dendritic morphology and NMDA receptor properties explain enhanced STMD responses in dragonflies.
  • To develop a computational model integrating morphological and numerical data of dragonfly optic lobe neurons.

Main Methods:

  • Developed a hybrid computational model of dragonfly optic lobe neurons.
  • Integrated numerical and morphological components into the model.
  • Compared model performance with biological data and an alternative dipteran fly neuron model.

Main Results:

  • The model successfully generated facilitation for continuous target trajectories, creating a sensitivity spotlight.
  • The model's facilitation was linked to high dendritic density and nonlinear NMDA receptor properties.
  • The model did not replicate a spreading wave of facilitation.
  • An alternative model required significantly higher synaptic gain for similar facilitation.

Conclusions:

  • Dragonfly neuron morphology, particularly high dendritic density, plays a key role in nonlinear facilitation for target tracking.
  • NMDA receptors may contribute to the precise target tracking observed in dragonflies.
  • Combining biologically plausible dendritic computations with abstract models is feasible for understanding neural processing.