美国普林斯顿大学Mala Murthy等研究人员合作发现，将模型单元映射到视觉神经元可揭示社会行为的群体代码。该研究于2024年5月22日在线发表于国际一流学术期刊《自然》。

研究人员展示了一种新颖的建模方法，通过预测十几种神经元细胞类型的系统性扰动所引起的行为变化，确定深度神经网络内部单元与真实神经元之间的一一对应映射。研究人员引入的一个关键要素是“敲除训练”，即在训练过程中对网络进行扰动，使其与真实神经元在行为实验中的扰动相匹配。研究人员将这种方法用于模拟黑腹果蝇雄虫在复杂的视觉引导社交行为中的感觉运动转换。视觉投射神经元位于视叶和大脑中枢的交界处，形成一组离散的通道，先前的研究表明，每个通道编码一个特定的视觉特征，以驱动特定的行为。

该模型得出了不同的结论：视觉投射神经元的组合（包括那些参与非社会行为的神经元）驱动雄性与雌性的互动，形成了丰富的群体行为代码。总之，这个框架将各种神经扰动引起的行为效应整合到一个统一的模型中，提供了从刺激到神经元细胞类型再到行为的映射，并能在未来将大脑布线图谱纳入模型中。

据悉，在动物身上观察到的丰富多彩的行为是通过感觉处理和运动控制之间的相互作用产生的。要理解这些感觉运动转换，不仅需要建立模型来预测神经对感觉输入的反应，还需要预测每个神经元如何对行为做出因果贡献。

附：英文原文

Title: Mapping model units to visual neurons reveals population code for social behaviour

Author: Cowley, Benjamin R., Calhoun, Adam J., Rangarajan, Nivedita, Ireland, Elise, Turner, Maxwell H., Pillow, Jonathan W., Murthy, Mala

Issue&Volume: 2024-05-22

Abstract: The rich variety of behaviours observed in animals arises through the interplay between sensory processing and motor control. To understand these sensorimotor transformations, it is useful to build models that predict not only neural responses to sensory input1,2,3,4,5 but also how each neuron causally contributes to behaviour6,7. Here we demonstrate a novel modelling approach to identify a one-to-one mapping between internal units in a deep neural network and real neurons by predicting the behavioural changes that arise from systematic perturbations of more than a dozen neuronal cell types. A key ingredient that we introduce is ‘knockout training’, which involves perturbing the network during training to match the perturbations of the real neurons during behavioural experiments. We apply this approach to model the sensorimotor transformations of Drosophila melanogaster males during a complex, visually guided social behaviour8,9,10,11. The visual projection neurons at the interface between the optic lobe and central brain form a set of discrete channels12, and prior work indicates that each channel encodes a specific visual feature to drive a particular behaviour13,14. Our model reaches a different conclusion: combinations of visual projection neurons, including those involved in non-social behaviours, drive male interactions with the female, forming a rich population code for behaviour. Overall, our framework consolidates behavioural effects elicited from various neural perturbations into a single, unified model, providing a map from stimulus to neuronal cell type to behaviour, and enabling future incorporation of wiring diagrams of the brain15 into the model.

DOI: 10.1038/s41586-024-07451-8

Source: https://www.nature.com/articles/s41586-024-07451-8