The work demonstrates that brain might reflect the external world causal
relationships in the form of a logically consistent and prognostic model of
reality, which shows up as consciousness. The paper analyses and solves the
problem of statistical ambiguity and provides a formal model of causal
relationships as probabilistic maximally specific rules. We suppose that brain
makes all possible inferences from causal relationships. We prove that the
suggested formal model has a property of an unambiguous inference: from
consistent premises we infer a consistent conclusion. It enables a set of all
inferences to form a consistent model of the perceived world. Causal
relationships may create fixed points of cyclic inter-predictable properties.
We consider the "natural" classification introduced by John St. Mill and
demonstrate that a variety of fixed points of the objects' attributes forms a
"natural" classification of the external world. Then we consider notions of
"natural" categories and causal models of categories, introduced by Eleanor
Rosch and Bob Rehder and demonstrate that fixed points of causal relationships
between objects attributes, which we perceive, formalize these notions. If the
"natural" classification describes the objects of the external world, and
"natural" concepts the perception of these objects, then the theory of
integrated information, introduced by G. Tononi, describes the information
processes of the brain for "natural" concepts formation that reflects the
"natural" classification. We argue that integrated information provides high
accuracy of the objects identification. A computer-based experiment is provided
that illustrates fixed points formation for coded digits.

大脑通过形成逻辑一致且具有预测能力的现实模型来反映外部世界的因果关系，表现为意识。同时，这篇论文解决了统计模糊性的问题并提供了因果关系的正式概率最大具体规则模型。我们认为大脑从因果关系中进行了所有可能的推理，并证明了所提出的模型具有明确的推理性质：从一致的前提我们推导出一致的结论，从而形成了对感知世界的一致模型。因果关系可以创造出循环可预测属性的固定点。我们考虑了约翰・S・密尔引入的 “自然” 分类，并展示了对象属性的各种固定点形成了外部世界的 “自然” 分类。然后我们考虑了埃莉诺・罗施和鲍勃・雷德引入的 “自然” 类别和因果模型的概念，并证明了我们感知到的对象属性的因果关系固定点形式化了这些概念。如果 “自然” 分类描述了外部世界的对象，而 “自然” 概念描述了对这些对象的感知，那么由 G・托诺尼提出的综合信息理论描述了大脑的 “自然” 概念形成的信息过程，反映了 “自然” 分类。我们认为综合信息提供了高度准确的对象识别能力。此外，本文还提供了一个基于计算机的实验，展示了编码数字的固定点形成。