Yu Angela J, Dayan Peter
Gatsby Computational Neuroscience Unit, University College London, UK.
Neural Netw. 2002 Jun-Jul;15(4-6):719-30. doi: 10.1016/s0893-6080(02)00058-8.
Acetylcholine (ACh) plays an important role in a wide variety of cognitive tasks, such as perception, selective attention, associative learning, and memory. Extensive experimental and theoretical work in tasks involving learning and memory has suggested that ACh reports on unfamiliarity and controls plasticity and effective network connectivity. Based on these computational and implementational insights, we develop a theory of cholinergic modulation in perceptual inference. We propose that ACh levels reflect the uncertainty associated with top-down information, and have the effect of modulating the interaction between top-down and bottom-up processing in determining the appropriate neural representations for inputs. We illustrate our proposal by means of an hierarchical hidden Markov model, showing that cholinergic modulation of contextual information leads to appropriate perceptual inference.
乙酰胆碱(ACh)在多种认知任务中发挥着重要作用,如感知、选择性注意、联想学习和记忆。在涉及学习和记忆的任务中进行的大量实验和理论研究表明,ACh报告不熟悉程度,并控制可塑性和有效的网络连通性。基于这些计算和实现方面的见解,我们开发了一种关于胆碱能调制在感知推理中的理论。我们提出,ACh水平反映了与自上而下信息相关的不确定性,并在确定输入的适当神经表征时,具有调节自上而下和自下而上处理之间相互作用的作用。我们通过一个分层隐马尔可夫模型来说明我们的提议,表明胆碱能对上下文信息的调制会导致适当的感知推理。