Title: Emergent functions of noise-driven spontaneous activity: Homeostatic maintenance of criticality and memory consolidation Show Chinese title

Title: 噪声驱动的自发活动的涌现功能：临界性的稳态维持与记忆巩固

Abstract: Unlike digital computers, the brain exhibits spontaneous activity even during complete rest, despite the evolutionary pressure for energy efficiency. Inspired by the critical brain hypothesis, which proposes that the brain operates optimally near a critical point of phase transition in the dynamics of neural networks to improve computational efficiency, we postulate that spontaneous activity plays a homeostatic role in the development and maintenance of criticality. Criticality in the brain is associated with the balance between excitatory and inhibitory synaptic inputs (EI balance), which is essential for maintaining neural computation performance. Here, we hypothesize that both criticality and EI balance are stabilized by appropriate noise levels and spike-timing-dependent plasticity (STDP) windows. Using spiking neural network (SNN) simulations and in vitro experiments with dissociated neuronal cultures, we demonstrated that while repetitive stimuli transiently disrupt both criticality and EI balance, spontaneous activity can develop and maintain these properties and prolong the fading memory of past stimuli. Our findings suggest that the brain may achieve self-optimization and memory consolidation as emergent functions of noise-driven spontaneous activity. This noise-harnessing mechanism provides insights for designing energy-efficient neural networks, and may explain the critical function of sleep in maintaining homeostasis and consolidating memory. Show Chinese abstract

Abstract: 与数字计算机不同，即使在完全休息时，大脑也会表现出自发活动，尽管有能量效率的进化压力。 受临界大脑假说的启发，该假说提出大脑在神经网络动力学的相变临界点附近最优运行，以提高计算效率，我们假设自发活动在临界性的发育和维持中起稳态作用。 大脑中的临界性与兴奋性和抑制性突触输入（EI平衡）之间的平衡有关，这对于保持神经计算性能至关重要。 在这里，我们假设临界性和EI平衡都由适当的噪声水平和尖峰时间依赖可塑性（STDP）窗口稳定。 使用脉冲神经网络（SNN）模拟和分离的神经元培养的体外实验，我们证明了虽然重复刺激会暂时破坏临界性和EI平衡，但自发活动可以发展并维持这些特性，并延长对过去刺激的消退记忆。 我们的研究结果表明，大脑可能通过噪声驱动的自发活动实现自我优化和记忆巩固作为涌现功能。 这种利用噪声的机制为设计节能神经网络提供了见解，并可能解释睡眠在维持稳态和巩固记忆中的临界功能。