Center for Neurotechnology, University of Washington, Seattle, WA, USA.
Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA.
Nat Neurosci. 2024 Jul;27(7):1221-1235. doi: 10.1038/s41593-024-01673-9. Epub 2024 Jun 27.
Recent neurophysiological and neuroanatomical studies suggest a close interaction between sensory and motor processes across the neocortex. Here, I propose that the neocortex implements active predictive coding (APC): each cortical area estimates both latent sensory states and actions (including potentially abstract actions internal to the cortex), and the cortex as a whole predicts the consequences of actions at multiple hierarchical levels. Feedback from higher areas modulates the dynamics of state and action networks in lower areas. I show how the same APC architecture can explain (1) how we recognize an object and its parts using eye movements, (2) why perception seems stable despite eye movements, (3) how we learn compositional representations, for example, part-whole hierarchies, (4) how complex actions can be planned using simpler actions, and (5) how we form episodic memories of sensory-motor experiences and learn abstract concepts such as a family tree. I postulate a mapping of the APC model to the laminar architecture of the cortex and suggest possible roles for cortico-cortical and cortico-subcortical pathways.
最近的神经生理学和神经解剖学研究表明,新皮层中的感觉和运动过程之间存在密切的相互作用。在这里,我提出新皮层实现了主动预测编码(APC):每个皮层区域都估计潜在的感觉状态和动作(包括潜在的皮层内部的抽象动作),整个皮层可以预测多个层次的动作的后果。来自较高区域的反馈调节较低区域中状态和动作网络的动态。我展示了相同的 APC 架构如何解释(1)我们如何使用眼球运动识别物体及其部分,(2)为什么尽管有眼球运动,但感知似乎是稳定的,(3)我们如何学习组合表示,例如,部分-整体层次结构,(4)如何使用更简单的动作来规划复杂的动作,以及(5)我们如何形成感觉运动经验的情节记忆并学习抽象概念,例如家谱。我假设 APC 模型与皮层的分层结构之间存在映射,并提出了皮质-皮质和皮质-皮质下通路的可能作用。