丘脑-脑干吸引网络驱动着历史偏见的决定，这一成果由中国科学院脑科学与智能技术卓越创新中心穆宇课题组经过不懈努力而取得。该研究于2026年6月10日发表于国际一流学术期刊《自然》杂志上。

利用全脑细胞分辨率成像技术，研究人员在斑马鱼进行记忆引导的逃避动作中，发现了一个维持过去信息并偏向未来选择的等级电路。背丘脑的离散吸引子编码最近障碍物的位置，通过持续10-20秒的持续活动维持分类记忆。光遗传学操作的背丘脑消除或施加系列偏见。下游的后脑整合器接收来自丘脑的输入，并将其与当前的感觉线索相结合，产生反映多试验历史的分级反应。利用斑马鱼的综合脑图谱，研究小组构建了一个全脑计算模型，该模型概括了行为，并预测了异质性抑制亚型在实现灵活状态转换中的关键作用。这种吸引-积分器架构揭示了一种分层和模块化的计算，将机器人记忆保留与灵活的感觉整合结合起来，为历史偏见决策提供了一般原则。

据了解，自然环境通常是逐渐变化的，使其适应基于最近过去的偏见决策-一种被称为序列依赖的现象。行为过程中的大规模记录表明，连续依赖是决策的共同主题，在整个大脑中发现了过去经验的神经表征。然而，尚不清楚这种偏差是否来自具有特定历史计算的专用神经回路。

附：英文原文

Title: A thalamus–brainstem attractor network drives history-biased decisions

Author: Zhao, Shan, Shan, Heying, Liu, Xiao, Qian, Yu, Huang, Jingyao, Liu, Yi-Ran, Jiao, Zhenfei, Ye, Lichen, Cong, Lin, Wang, Xiaoou, Wang, Zhi-Yuan, Li, Danyang, Chen, Ming-Quan, Wang, Kai, Fu, Ling, Du, Xu-Fei, Wu, Si, Mu, Yu

Issue&Volume: 2026-06-10

Abstract: Natural environments often change gradually, making it adaptive to bias decisions on the basis of the recent past — a phenomenon known as serial dependence1,2,3. Large-scale recordings during behaviour have identified that serial dependence is a common motif for decision-making, with neural representations of past experiences found throughout the brain4,5,6,7,8,9,10,11. However, it remains unclear whether this bias arises from dedicated neural circuits with history-specific computations. Using whole-brain, cellular-resolution imaging in zebrafish performing memory-guided evasive manoeuvres12,13,14, we identified a hierarchical circuit that maintains past information and biases future choices. Discrete attractors in the dorsal thalamus encoded the position of the most recent obstacle, maintaining a categorical memory via persistent activity lasting 10–20s. Optogenetic manipulation of the dorsal thalamus abolished or imposed serial bias. A downstream hindbrain integrator received input from the thalamus and combined it with current sensory cues to produce graded responses reflecting multi-trial history. Leveraging a comprehensive brain atlas in zebrafish15, we constructed a whole-brain computational model that recapitulated behaviour and also predicted a key role for heterogeneous inhibitory subtypes in enabling flexible state transitions. This attractor–integrator architecture reveals a hierarchical and modular computation that unifies robust memory retention with flexible sensory integration, providing a general principle for history-biased decisions.

DOI: 10.1038/s41586-026-10623-3

Source: https://www.nature.com/articles/s41586-026-10623-3