提醒（2021-12-23）：由于嘉宾抱恙，本次活动将延期举办，新的活动时间确定后，将在本帖更新

时间：2021年12月23日下午16:00-17:30

腾讯会议ID：920-200-068

主题：Internal state dynamics shape brainwide activity and foraging behaviour

摘要：The brain has persistent internal states that can modulate every aspect of an animal’s mental experience. In complex tasks such as foraging, the internal state is dynamic. Using tracking microscopy to monitor whole-brain neuronal activity at cellular resolution in freely moving zebrafish larvae and DNN to track multiple objects in the images, we show that zebrafish spontaneously alternate between two persistent internal states during foraging for live prey (Paramecia). By analyzing the activities of ~10000 neurons in the brain, we uncover a dorsal raphe subpopulation with persistent activity that robustly encodes the exploitation state. The exploitation-state-encoding neurons, together with a multimodal trigger network that is associated with state transitions, form a stochastically activated nonlinear dynamical system. The activity of this oscillatory network correlates with a global retuning of sensorimotor transformations during foraging that leads to marked changes in both the motivation to hunt for prey and the accuracy of motor sequences during hunting. Our result reveals an important hidden variable that shapes the temporal structure of motivation and decision-making.

主讲人：李孟，博士，上海微系统所研究员，博士生导师。2009年哈尔滨工业大学仪器科学与技术专业获博士学位，先后在美国佐治亚医学院、哈佛大学从事博士后研究，2019年加入德国马克普朗克学会生物控制论研究所任研究科学家。2021年6月入职中科院上海微系统所。

李孟博士主要从事large-scale群体神经信号编解码研究，主要工作包括：1）解码了十万神经元量级的全脑神经信号，揭示了大脑内在状态动态转化的控制机理，建立了复杂高阶行为与大脑神经网络内在状态间的关系；2）提出了基于自信息理论的群体神经元信息编码算法，实现对群体神经元活动的盲解码；3）并尝试应用large-scale神经信号分析与建模方法解决脑科学和脑疾病问题。共发表论文26篇，包括第一作者（含共同第一作者）发表在Nature、Cerebral Cortex、Advanced Science等发表的论文11篇。其中Nature文章被Nature杂志以“News and Views”和“News Feature”形式进行重点介绍和评价。

 

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