Inhibitory engrams in learning and memory consolidation

人脑是已知宇宙中最复杂的系统。尽管如此复杂，与其他系统如汽车或计算机相比，大脑不需要定期维修。相反，大脑有一种非凡的能力，可以在不损害先前学习的信息的情况下进行修改。这反映了塑性和稳定性之间的微妙平衡。可以说，这种权衡确保了我们能够灵活地满足不断变化的环境（可塑性）的需求，同时也保护了记忆免受干扰（稳定性）。可塑性和稳定性之间的这种权衡被认为是由稳态机制决定的。然而，这些机制的细节仍然知之甚少，特别是在学习的行为读出方面。这在一定程度上反映在人工神经网络的性能上，如果在新任务上进行训练，人工神经网络通常会忘记过去的学习，从而导致“灾难性遗忘”，这已成为人工智能面临的主要挑战之一。先前在动物、人类和计算模型中的研究表明，通过在兴奋性和抑制性活动之间建立平衡，在新的学习之后，大脑内的稳定性得以恢复。具体来说，虽然新的学习被认为首先在兴奋性连接处诱导可塑性，但这会导致整体活动的增加，随后必须通过抑制性连接的匹配变化来稳定。在这里，我们将研究人类大脑中的这种自我平衡机制。在我们的实验中，志愿者将通过学习图片和符号之间的关联来获得新的记忆。然后，我们将使用涉及非侵入性磁共振成像的神经成像技术来测量记忆抑制成分的变化。首先，我们将研究控制新学习后匹配抑制性连接形成的机制。具体来说，我们将询问学习后休息时的大脑活动如何建立匹配的抑制连接。其次，我们将研究这种自我平衡机制被破坏的情况，导致记忆的不稳定和干扰。为此，我们将使用单剂量的无害药物来模拟压力下大脑化学物质的自然变化。第三，我们将评估与新学习后立即出现记忆不稳定的短暂窗口相关的适应性优势。我们将测试当这个不稳定窗口延长时，我们是否可以促进不同记忆中共享特征的泛化。这些研究将共同揭示人类大脑如何调节可塑性和稳定性之间微调权衡的机械见解。在这样做的过程中，这些研究将提供一个重要的基础，从中确定记忆扭曲是如何在心理和神经系统疾病中出现的。

The human brain is the most complex system in the known universe. Yet despite this complexity, and in contrast to other systems such as cars or computers, the brain does not need to be regularly serviced. Instead, the brain has a remarkable ability to undergo modification without compromising previously learned information. This reflects a finely tuned trade-off between plasticity and stability. Arguably this trade-off ensures we have the flexibility to meet the demands of an ever-changing environment (plasticity) while also protecting memories from interference (stability). This trade-off between plasticity and stability is thought to be set by homeostatic mechanisms. However, the details of these mechanisms remain poorly understood, particularly in relation to behavioural read-outs of learning. This is in part reflected in the performance of artificial neural networks, which typically forget past learning if trained on new tasks, giving rise to 'catastrophic forgetting' which has emerged as one of the main challenges facing artificial intelligence. Previous studies in both animals, humans and computational models suggest stability within the brain is restored after new learning by establishing a balance between excitatory and inhibitory activity. Specifically, while new learning is thought to first induce plasticity at excitatory connections, this leads to an increase in overall activity which must later be stabilized by matched changes in inhibitory connections. Here, we will investigate this homeostatic mechanism in the human brain. In our experiments, volunteers will acquire new memories by learning sets of associations between pictures and symbols. We will then measure changes in the inhibitory component of a memory using neuroimaging techniques that involve non-invasive Magnetic Resonance Imaging. First, we will investigate mechanisms that control the formation of matched inhibitory connections after new learning. Specifically, we will ask how brain activity during rest after a learning session serves to build matched inhibitory connections. Second, we will investigate the circumstances under which this homeostatic mechanism is disrupted, leading to instability and disturbance in memory. To this end, we will use a single-dose of a non-harmful drug to mimic natural changes in our brain chemistry under stress. Third, we will assess the adaptive advantage associated with having a transient window of memory instability immediately after new learning. We will test whether we can promote generalization of shared features across different memories when this window of instability is prolonged. Together these studies will reveal mechanistic insight into how the human brain regulates a finely tuned trade-off between plasticity and stability. In doing so, these studies will provide an important basis from which to establish how memory distortions arise in psychological and neurological disorders.