Shallow networks run deep: Peripheral preprocessing facilitates odor classification.
Shallow networks run deep: Peripheral preprocessing facilitates odor classification.
复制标题
浅层网络运行得很深：外围预处理有利于气味分类。
DOI：
10.1101/2023.07.23.550211
复制
发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Aljadeff,Johnatan
中科院分区：
文献类型：
--
作者：
Puri,Palka;Wu,Shiuan-Tze;Su,Chih-Ying;Aljadeff,Johnatan
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.
