From the phenomenology to the mechanisms of consciousness: Integrated Information Theory 3.0.
From the phenomenology to the mechanisms of consciousness: Integrated Information Theory 3.0.
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DOI：
10.1371/journal.pcbi.1003588
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发表时间：
2014-05
影响因子：
4.3
通讯作者：
Tononi G
中科院分区：
文献类型：
--
作者：
Oizumi M;Albantakis L;Tononi G
本文提出了意识 3.0 的综合信息理论 (IIT)，它融合了先前表述的多项进步。 IIT 从现象学公理出发：信息表明，每种体验都是特定的——它之所以如此，是因为它与其他体验有何不同；集成表示它是统一的——不可简化为非相互依赖的组件；排除说它有独特的边界和特定的时空纹理。这些公理被形式化为假设，规定了如何配置物理机制（例如神经元或逻辑门）来生成经验（现象学）。这些假设用于将内在信息定义为系统内“产生影响的差异”，并将集成信息定义为由整体指定的信息，该信息不能还原为其部分指定的信息。通过在个体机制层面和机制系统层面应用这些假设，IIT 得出了一个同一性：体验是一种最大程度不可约的概念结构（MICS，感受性空间中的概念群），而生成它的元素集构成了一个复合体。根据 IIT，MICS 指定体验的质量和综合信息 ΦMax 其数量。从该理论可以得出几个结果，包括：机制系统可以凝结成一个主要复合体和不重叠的次要复合体；指定体验质量的概念始终与综合体本身有关，并且仅与外部环境间接相关；解剖连接性影响复合体和相关的 MICS；即使其元素不活跃，复合体也可以生成 MICS；简单的系统可以是最低意识的；复杂的系统可能是无意识的；可能存在真正的“僵尸”——功能上等同于意识复合体的无意识前馈系统。综合信息理论（IIT）通过首先识别体验本身的基本属性：存在、组成、信息、整合和排除来研究意识与其物理基础之间的关系。印度理工学院随后假设意识的物理基础必须满足这些特性。我们开发了一个详细的数学框架，其中精确定义了组成、信息、积分和排除，并使其可操作。这使我们能够确定简单的机制系统（例如逻辑门或类似神经元的元素）可以在多大程度上形成可以解释意识基本属性的复合体。基于这种原则性方法，我们证明 IIT 可以解释许多关于意识和大脑的已知事实，得出具体的预测，并允许我们至少在原则上推断因果结构已知的系统的意识的数量和质量。例如，我们证明一些简单的系统可以是最低意识的，一些复杂的系统可以是无意识的，两个不同的系统可以在功能上等效，但一个是有意识的，另一个不是。
This paper presents Integrated Information Theory (IIT) of consciousness 3.0, which incorporates several advances over previous formulations. IIT starts from phenomenological axioms: information says that each experience is specific – it is what it is by how it differs from alternative experiences; integration says that it is unified – irreducible to non-interdependent components; exclusion says that it has unique borders and a particular spatio-temporal grain. These axioms are formalized into postulates that prescribe how physical mechanisms, such as neurons or logic gates, must be configured to generate experience (phenomenology). The postulates are used to define intrinsic information as “differences that make a difference” within a system, and integrated information as information specified by a whole that cannot be reduced to that specified by its parts. By applying the postulates both at the level of individual mechanisms and at the level of systems of mechanisms, IIT arrives at an identity: an experience is a maximally irreducible conceptual structure (MICS, a constellation of concepts in qualia space), and the set of elements that generates it constitutes a complex. According to IIT, a MICS specifies the quality of an experience and integrated information ΦMax its quantity. From the theory follow several results, including: a system of mechanisms may condense into a major complex and non-overlapping minor complexes; the concepts that specify the quality of an experience are always about the complex itself and relate only indirectly to the external environment; anatomical connectivity influences complexes and associated MICS; a complex can generate a MICS even if its elements are inactive; simple systems can be minimally conscious; complicated systems can be unconscious; there can be true “zombies” – unconscious feed-forward systems that are functionally equivalent to conscious complexes. Integrated information theory (IIT) approaches the relationship between consciousness and its physical substrate by first identifying the fundamental properties of experience itself: existence, composition, information, integration, and exclusion. IIT then postulates that the physical substrate of consciousness must satisfy these very properties. We develop a detailed mathematical framework in which composition, information, integration, and exclusion are defined precisely and made operational. This allows us to establish to what extent simple systems of mechanisms, such as logic gates or neuron-like elements, can form complexes that can account for the fundamental properties of consciousness. Based on this principled approach, we show that IIT can explain many known facts about consciousness and the brain, leads to specific predictions, and allows us to infer, at least in principle, both the quantity and quality of consciousness for systems whose causal structure is known. For example, we show that some simple systems can be minimally conscious, some complicated systems can be unconscious, and two different systems can be functionally equivalent, yet one is conscious and the other one is not.