Helen Wills Neuroscience Institute and Department of Bioengineering, University of California, Berkeley, Berkeley, United States.
Elife. 2022 Feb 10;11:e70493. doi: 10.7554/eLife.70493.
A key goal of social neuroscience is to understand the inter-brain neural relationship-the relationship between the neural activity of socially interacting individuals. Decades of research investigating this relationship have focused on the similarity in neural activity across brains. Here, we instead asked how neural activity differs between brains, and how that difference evolves alongside activity patterns shared between brains. Applying this framework to bats engaged in spontaneous social interactions revealed two complementary phenomena characterizing the inter-brain neural relationship: fast fluctuations of activity difference across brains unfolding in parallel with slow activity covariation across brains. A model reproduced these observations and generated multiple predictions that we confirmed using experimental data involving pairs of bats and a larger social group of bats. The model suggests that a simple computational mechanism involving positive and negative feedback could explain diverse experimental observations regarding the inter-brain neural relationship.
社会神经科学的一个主要目标是理解脑间神经关系——即社交互动个体之间的神经活动关系。几十年来，研究这一关系的重点一直放在大脑之间神经活动的相似性上。在这里，我们转而探讨大脑之间的神经活动有何不同，以及这种差异如何与大脑之间共享的活动模式一起演变。将这一框架应用于自发社交互动的蝙蝠身上，揭示了两个描述脑间神经关系的互补现象：大脑之间的活动差异快速波动，与大脑之间的缓慢活动协变并行不悖。一个模型再现了这些观察结果，并产生了多个预测，我们使用涉及成对蝙蝠和更大蝙蝠社会群体的实验数据证实了这些预测。该模型表明，一种涉及正反馈和负反馈的简单计算机制可以解释关于脑间神经关系的各种实验观察结果。
