4.8 Article

Response competition between neurons and antineurons in the mushroom body

Journal

CURRENT BIOLOGY
Volume 31, Issue 22, Pages 4911-+

Publisher

CELL PRESS
DOI: 10.1016/j.cub.2021.09.008

Keywords

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Funding

  1. Wellcome [209235/Z/17/Z, 106988/Z/15/Z, 090309/Z/09/Z]
  2. Gatsby Charitable Foundation [GAT3237]
  3. National Institutes of Health [RO1 DA30601]
  4. Wellcome Trust [209235/Z/17/Z, 090309/Z/09/Z, 106988/Z/15/Z] Funding Source: Wellcome Trust

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The mushroom bodies of Drosophila contain a circuitry compatible with race models of perceptual choice. Opponent pools of Kenyon cells accumulate evidence for changes in odor concentration, and connect to mushroom body output neurons which bias behavioral intent. All-to-all connectivity allows for correct and erroneous decisions, with dopaminergic reinforcement influencing choice probabilities through changes in synapse efficacy. The response competition network gives tangible form to features envisioned in theoretical models of mammalian decision making.
The mushroom bodies of Drosophila contain circuitry compatible with race models of perceptual choice. When flies discriminate odor intensity differences, opponent pools of cci3 core Kenyon cells (on and off cci3c KCs) accumulate evidence for increases or decreases in odor concentration. These sensory neurons and antineuronsconnect to a layer of mushroom body output neurons (MBONs) which bias behavioral intent in opposite ways. All-to-all connectivity between the competing integrators and their MBON partners allows for correct and erroneous decisions; dopaminergic reinforcement sets choice probabilities via reciprocal changes to the efficacies of on and off KC synapses; and pooled inhibition between cci3c KCs can establish equivalence with the drift-diffusion formalism known to describe behavioral performance. The response competition network gives tangible form to many features envisioned in theoretical models of mammalian decision making, but it differs from these models in one respect: the principal variables-the fill levels of the integrators and the strength of inhibition between them-are represented by graded potentials rather than spikes. In pursuit of similar computational goals, a small brain may thus prioritize the large information capacity of analog signals over the robustness and temporal processing span of pulsatile codes.

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