Meta-awareness refers to the capacity to explicitly notice the current content of consciousness and has been identified as a key component for the successful control of cognitive states, such as the deliberate direction of attention. This paper proposes a formal model of meta-awareness and attentional control using hierarchical active inference. To do so, we cast mental action as policy selection over higher-level cognitive states and add a further hierarchical level to model meta-awareness states that modulate the expected confidence (precision) in the mapping between observations and hidden cognitive states. We simulate the example of mind-wandering and its regulation during a task involving sustained selective attention on a perceptual object. This provides a computational case study for an inferential architecture that is apt to enable the emergence of these central components of human phenomenology, namely, the ability to access and control cognitive states. We propose that this approach can be generalized to other cognitive states, and hence, this paper provides the first steps towards the development of a computational phenomenology of mental action and more broadly of our ability to monitor and control our own cognitive states. Future steps of this work will focus on fitting the model with qualitative, behavioural, and neural data.

中文翻译：

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出版商注：迈向心理行为的计算现象学：用深度参数主动推理建模元意识和注意力控制

元意识是指明确注意当前意识内容的能力，已被确定为成功控制认知状态的关键组成部分，例如有意识的注意力方向。本文提出了一个使用分层主动推理的元意识和注意力控制的正式模型。为此，我们将心理行为视为对更高级别认知状态的策略选择，并添加进一步的层次结构来模拟元意识状态，从而调节观察和隐藏认知状态之间映射的预期置信度（精度）。我们在涉及对感知对象的持续选择性注意的任务中模拟了走神及其调节的示例。这为推理架构提供了一个计算案例研究，该架构易于出现人类现象学的这些核心组件，即访问和控制认知状态的能力。我们建议这种方法可以推广到其他认知状态，因此，本文提供了发展心理行为计算现象学的第一步，以及更广泛地监测和控制我们自己的认知状态的能力。这项工作的未来步骤将集中在用定性、行为和神经数据拟合模型。本文提供了发展心理行为计算现象学的第一步，以及更广泛地发展我们监测和控制自己认知状态的能力。这项工作的未来步骤将集中在用定性、行为和神经数据拟合模型。本文提供了发展心理行为计算现象学的第一步，以及更广泛地发展我们监测和控制自己认知状态的能力。这项工作的未来步骤将集中在用定性、行为和神经数据拟合模型。