Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, UK
Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, UK.
J R Soc Interface. 2017 Nov;14(136). doi: 10.1098/rsif.2017.0376.
Biological systems-like ourselves-are constantly faced with uncertainty. Despite noisy sensory data, and volatile environments, creatures appear to actively maintain their integrity. To account for this remarkable ability to make optimal decisions in the face of a capricious world, we propose a generative model that represents the beliefs an agent might possess about their own uncertainty. By simulating a noisy and volatile environment, we demonstrate how uncertainty influences optimal epistemic (visual) foraging. In our simulations, saccades were deployed less frequently to regions with a lower sensory precision, while a greater volatility led to a shorter inhibition of return. These simulations illustrate a principled explanation for some cardinal aspects of visual foraging-and allow us to propose a correspondence between the representation of uncertainty and ascending neuromodulatory systems, complementing that suggested by Yu & Dayan (Yu & Dayan 2005 , 681-692. (doi:10.1016/j.neuron.2005.04.026)).
生物系统——就像我们人类一样——时刻面临着不确定性。尽管感官数据嘈杂，环境变幻莫测，但生物似乎能够积极地维持自身的完整性。为了解释这种在变幻莫测的世界中做出最佳决策的非凡能力，我们提出了一个生成模型，该模型代表了一个主体可能对其自身不确定性的信念。通过模拟一个嘈杂和不稳定的环境，我们展示了不确定性如何影响最优认知（视觉）觅食。在我们的模拟中，扫视的频率会降低到感觉精度较低的区域，而较大的波动性会导致返回抑制时间变短。这些模拟说明了视觉觅食的一些重要方面的原则性解释——并允许我们提出不确定性表示与上行神经调质系统之间的对应关系，补充了 Yu 和 Dayan（Yu & Dayan 2005，681-692.（doi:10.1016/j.neuron.2005.04.026））提出的对应关系。
