Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA.
Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA; Center for Brain Science, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard Stem Cell Institute, Cambridge, MA 02138, USA; Biozentrum, University of Basel, 4056 Basel, Switzerland.
Neuron. 2019 Sep 25;103(6):1123-1134.e6. doi: 10.1016/j.neuron.2019.07.003. Epub 2019 Jul 31.
Discoveries in biological neural networks (BNNs) shaped artificial neural networks (ANNs) and computational parallels between ANNs and BNNs have recently been discovered. However, it is unclear to what extent discoveries in ANNs can give insight into BNN function. Here, we designed and trained an ANN to perform heat gradient navigation and found striking similarities in computation and heat representation to a known zebrafish BNN. This included shared ON- and OFF-type representations of absolute temperature and rates of change. Importantly, ANN function critically relied on zebrafish-like units. We furthermore used the accessibility of the ANN to discover a new temperature-responsive cell type in the zebrafish cerebellum. Finally, constraining the ANN by the C. elegans motor repertoire retuned sensory representations indicating that our approach generalizes. Together, these results emphasize convergence of ANNs and BNNs on stereotypical representations and that ANNs form a powerful tool to understand their biological counterparts.
生物神经网络 (BNN) 的发现塑造了人工神经网络 (ANN)，并且最近发现了 ANN 与 BNN 之间的计算并行性。然而，目前尚不清楚 ANN 的发现能够在多大程度上深入了解 BNN 的功能。在这里，我们设计并训练了一个 ANN 来执行热梯度导航，并发现其计算和热表示与已知的斑马鱼 BNN 惊人地相似。这包括对绝对温度和变化率的 ON 和 OFF 型表示的共享。重要的是，ANN 的功能严重依赖于类似斑马鱼的单元。此外，我们利用 ANN 的可访问性发现了斑马鱼小脑中的一种新的温度响应细胞类型。最后，通过限制 C. elegans 运动库对 ANN 进行约束，重新调整了感觉表示，表明我们的方法具有普遍性。总之，这些结果强调了 ANN 和 BNN 在典型表示上的趋同，并且 ANN 形成了理解其生物对应物的有力工具。
