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Organization of descending neurons in the brain of the desert locust.

Erich M StaudacherMichel-Leon CiganFelix WenzAleksandra PollunSascha BeckMarius BeckFabienne RehJudith HaasUwe Homberg
Published in: The Journal of comparative neurology (2023)
In most animals, multiple external and internal signals are integrated by the brain, transformed and, finally, transmitted as commands to motor centers. In insects, the central complex is a motor control center in the brain, involved in decision-making and goal-directed navigation. In desert locusts, it encodes celestial cues in a compass-like fashion indicating a role in sky-compass navigation. While several descending brain neurons (DBNs) including two neurons transmitting sky compass signals have been identified in the locust, a complete analysis of DBNs and their relationship to the central complex is still lacking. As a basis for further studies, we used Neurobiotin tracer injections into a neck connective to map the organization of DBNs in the brain. Cell counts revealed a maximum of 324 bilateral pairs of DBNs with somata distributed in 14 ipsilateral and nine contralateral groups. These neurons invaded most brain neuropils, especially the posterior slope, posterior and ventro-lateral protocerebrum, the antennal mechanosensory and motor center, but less densely the lateral accessory lobes that are targeted by central-complex outputs. No arborizations were found in the central complex and only few processes in the mushroom body, antennal lobe, lobula, medulla, and superior protocerebrum. Double label experiments provide evidence for the presence of GABA, dopamine, tyramine, but not serotonin, in small sets of DBNs. The data show that some DBNs may be targeted directly by central-complex outputs, but many others are likely only indirectly influenced by central-complex networks, in addition to input from multiple other brain areas.
Keyphrases
  • resting state
  • white matter
  • functional connectivity
  • spinal cord
  • decision making
  • single cell
  • computed tomography
  • machine learning
  • drug delivery
  • spinal cord injury
  • artificial intelligence