Peripheral preprocessing in Drosophila facilitates odor classification

• 成果类型: Article
• 署名作者: Puri, Palka; Wu, Shiuan-Tze; Su, Chih-Ying; Aljadeff, Johnatan
• 署名单位: University of California System; University of California San Diego; University of California System; University of California San Diego
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-12821
• DOI: 10.1073/pnas.2316799121
• 发表日期: 2024-05-21
• 关键词: olfactory representations; circuit; neurons; inhibition; BEHAVIOR; reveals

摘要

The mammalian brain implements sophisticated sensory processing algorithms along multilayered (deep) neural networks. Strategies that insects use to meet similar computational demands, while relying on smaller nervous systems with shallow architectures, remain elusive. Using Drosophila as a model, we uncover the algorithmic role of odor preprocessing by a shallow network of compartmentalized olfactory receptor neurons. Each compartment operates as a ratiometric unit for specific odor-mixtures. This computation arises from a simple mechanism: electrical coupling between two differently sized neurons. We demonstrate that downstream synaptic connectivity is shaped to optimally leverage amplification of a hedonic value signal in the periphery. Furthermore, peripheral preprocessing is shown to markedly improve novel odor classification in a higher brain center. Together, our work highlights a far-reaching functional role of the sensory periphery for downstream processing. By elucidating the implementation of powerful computations by a shallow network, we provide insights into general principles of efficient sensory processing algorithms.