Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
Electrical and Computer Engineering, Rice University, Houston, Texas.
Ann N Y Acad Sci. 2017 May;1396(1):144-165. doi: 10.1111/nyas.13329.
Information processing in the rodent hippocampus is fundamentally shaped by internally generated sequences (IGSs), expressed during two different network states: theta sequences, which repeat and reset at the ∼8 Hz theta rhythm associated with active behavior, and punctate sharp wave-ripple (SWR) sequences associated with wakeful rest or slow-wave sleep. A potpourri of diverse functional roles has been proposed for these IGSs, resulting in a fragmented conceptual landscape. Here, we advance a unitary view of IGSs, proposing that they reflect an inferential process that samples a policy from the animal's generative model, supported by hippocampus-specific priors. The same inference affords different cognitive functions when the animal is in distinct dynamical modes, associated with specific functional networks. Theta sequences arise when inference is coupled to the animal's action-perception cycle, supporting online spatial decisions, predictive processing, and episode encoding. SWR sequences arise when the animal is decoupled from the action-perception cycle and may support offline cognitive processing, such as memory consolidation, the prospective simulation of spatial trajectories, and imagination. We discuss the empirical bases of this proposal in relation to rodent studies and highlight how the proposed computational principles can shed light on the mechanisms of future-oriented cognition in humans.
啮齿动物海马体中的信息处理主要由内部产生的序列（IGS）形成，这些序列在两种不同的网络状态下表达：theta 序列，以与主动行为相关的约 8 Hz theta 节律重复和重置；与清醒休息或慢波睡眠相关的点状尖峰波-涟漪（SWR）序列。这些 IGS 具有多种多样的功能作用，这导致了一个碎片化的概念景观。在这里，我们提出了一个统一的 IGS 观点，即它们反映了一种推断过程，该过程从动物的生成模型中采样策略，由海马体特有的先验支持。当动物处于不同的动力学模式时，相同的推断会提供不同的认知功能，这些模式与特定的功能网络相关联。当推断与动物的动作感知周期耦合时，就会出现 theta 序列，支持在线空间决策、预测处理和情节编码。当动物与动作感知周期解耦时，就会出现 SWR 序列，此时它可能支持离线认知处理，例如记忆巩固、空间轨迹的前瞻性模拟和想象。我们讨论了该提议在啮齿动物研究中的实证基础，并强调了所提出的计算原理如何为人类前瞻性认知的机制提供启示。
