Department of Bioengineering, Imperial College London, London, United Kingdom.
Elife. 2020 Apr 21;9:e56053. doi: 10.7554/eLife.56053.
Some neurons have stimulus responses that are stable over days, whereas other neurons have highly plastic stimulus responses. Using a recurrent network model, we explore whether this could be due to an underlying diversity in their synaptic plasticity. We find that, in a network with diverse learning rates, neurons with fast rates are more coupled to population activity than neurons with slow rates. This plasticity-coupling link predicts that neurons with high population coupling exhibit more long-term stimulus response variability than neurons with low population coupling. We substantiate this prediction using recordings from the Allen Brain Observatory, finding that a neuron's population coupling is correlated with the plasticity of its orientation preference. Simulations of a simple perceptual learning task suggest a particular functional architecture: a stable 'backbone' of stimulus representation formed by neurons with low population coupling, on top of which lies a flexible substrate of neurons with high population coupling.
有些神经元的刺激反应在数天内保持稳定，而其他神经元的刺激反应则具有高度可塑性。我们使用一个递归网络模型，探索这是否可能是由于其突触可塑性的潜在差异。我们发现，在具有不同学习率的网络中，快速率的神经元比慢速率的神经元与群体活动的耦合更强。这种可塑性-耦合关系预测，具有高群体耦合的神经元表现出比具有低群体耦合的神经元更多的长期刺激反应可变性。我们使用艾伦脑观测站的记录证实了这一预测，发现神经元的群体耦合与其方向偏好的可塑性相关。一个简单的感知学习任务的模拟表明了一种特殊的功能架构：由低群体耦合神经元形成的稳定的刺激表示“骨干”，在其之上是具有高群体耦合神经元的灵活基质。
