Computational Brain Lab, Department of Computer Science, Rutgers University, Piscataway, NJ 08854, U.S.A.
Neural Comput. 2022 Sep 12;34(10):2047-2074. doi: 10.1162/neco_a_01532.
Astrocytes are nonneuronal brain cells that were recently shown to actively communicate with neurons and are implicated in memory, learning, and regulation of cognitive states. Interestingly, these information processing functions are also closely linked to the brain's ability to self-organize at a critical phase transition. Investigating the mechanistic link between astrocytes and critical brain dynamics remains beyond the reach of cellular experiments, but it becomes increasingly approachable through computational studies. We developed a biologically plausible computational model of astrocytes to analyze how astrocyte calcium waves can respond to changes in underlying network dynamics. Our results suggest that astrocytes detect synaptic activity and signal directional changes in neuronal network dynamics using the frequency of their calcium waves. We show that this function may be facilitated by receptor scaling plasticity by enabling astrocytes to learn the approximate information content of input synaptic activity. This resulted in a computationally simple, information-theoretic model, which we demonstrate replicating the signaling functionality of the biophysical astrocyte model with receptor scaling. Our findings provide several experimentally testable hypotheses that offer insight into the regulatory role of astrocytes in brain information processing.
星形胶质细胞是一种非神经元脑细胞，最近有研究表明其与神经元之间存在活跃的通讯，并参与记忆、学习和认知状态的调节。有趣的是，这些信息处理功能也与大脑在关键相变过程中的自我组织能力密切相关。研究星形胶质细胞和关键大脑动力学之间的机制联系超出了细胞实验的范围，但通过计算研究，这种联系变得越来越可行。我们开发了一个具有生物学合理性的星形胶质细胞计算模型，以分析星形胶质细胞钙波如何响应基础网络动力学变化做出响应。我们的结果表明，星形胶质细胞通过其钙波的频率来检测突触活动，并对神经元网络动力学的方向变化发出信号。我们表明，这种功能可能通过受体缩放可塑性来实现，使星形胶质细胞能够学习输入突触活动的近似信息内容。这导致了一个计算上简单的信息论模型，我们证明了该模型可以复制具有受体缩放功能的生物物理星形胶质细胞模型的信号功能。我们的研究结果提供了一些可通过实验验证的假说，为星形胶质细胞在大脑信息处理中的调节作用提供了深入的见解。
