Control of entropy in neural models of environmental state
Control of entropy in neural models of environmental state
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DOI：
10.7554/elife.39404
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发表时间：
2019-02-28
期刊：
影响因子：
7.7
通讯作者：
O'Reilly, Jill X.
中科院分区：
文献类型：
--
作者：
Muller, Timothy H.;Mars, Rogier B.;O'Reilly, Jill X.
人类和动物构建其环境的内部模型，以选择适当的行动方案。对当前环境状态的不确定性的表示是这些模型的一个关键特征，它控制着学习的速度，并直接影响选择行为。为了保持灵活性，考虑到不确定性会随着时间的推移而自然降低，大多数理论推理模型都包括一个专门的机制来提高模型的不确定性。在这里，我们探讨了一个长期存在的假设，即去甲肾上腺素参与决定神经模型的不确定性或熵，从而决定神经模型的灵活性。瞳孔直径，指标神经调节状态，包括去甲肾上腺素的释放，预测增加（而不是减少）熵在人类内侧眶额皮质编码的神经状态模型，使用多变量功能MRI测量。前扣带皮层的活动预测瞳孔直径。这些结果为神经状态模型中熵的自上而下的神经调节控制提供了证据。
Humans and animals construct internal models of their environment in order to select appropriate courses of action. The representation of uncertainty about the current state of the environment is a key feature of these models that controls the rate of learning as well as directly affecting choice behaviour. To maintain flexibility, given that uncertainty naturally decreases over time, most theoretical inference models include a dedicated mechanism to drive up model uncertainty. Here we probe the long-standing hypothesis that noradrenaline is involved in determining the uncertainty, or entropy, and thus flexibility, of neural models. Pupil diameter, which indexes neuromodulatory state including noradrenaline release, predicted increases (but not decreases) in entropy in a neural state model encoded in human medial orbitofrontal cortex, as measured using multivariate functional MRI. Activity in anterior cingulate cortex predicted pupil diameter. These results provide evidence for top-down, neuromodulatory control of entropy in neural state models.