Safron Adam
Indiana University, Bloomington, IN, United States.
Front Artif Intell. 2020 Jun 9;3:30. doi: 10.3389/frai.2020.00030. eCollection 2020.
The Free Energy Principle and Active Inference Framework (FEP-AI) begins with the understanding that persisting systems must regulate environmental exchanges and prevent entropic accumulation. In FEP-AI, minds and brains are predictive controllers for autonomous systems, where action-driven perception is realized as probabilistic inference. Integrated Information Theory (IIT) begins with considering the preconditions for a system to intrinsically exist, as well as axioms regarding the nature of consciousness. IIT has produced controversy because of its surprising entailments: quasi-panpsychism; subjectivity without referents or dynamics; and the possibility of fully-intelligent-yet-unconscious brain simulations. Here, I describe how these controversies might be resolved by integrating IIT with FEP-AI, where integrated information only entails consciousness for systems with perspectival reference frames capable of generating models with spatial, temporal, and causal coherence for self and world. Without that connection with external reality, systems could have arbitrarily high amounts of integrated information, but nonetheless would not entail subjective experience. I further describe how an integration of these frameworks may contribute to their evolution as unified systems theories and models of emergent causation. Then, inspired by both Global Neuronal Workspace Theory (GNWT) and the Harmonic Brain Modes framework, I describe how streams of consciousness may emerge as an evolving generation of sensorimotor predictions, with the precise composition of experiences depending on the integration abilities of synchronous complexes as self-organizing harmonic modes (SOHMs). These integrating dynamics may be particularly likely to occur via richly connected subnetworks affording body-centric sources of phenomenal binding and executive control. Along these connectivity backbones, SOHMs are proposed to implement turbo coding via loopy message-passing over predictive (autoencoding) networks, thus generating maximum a posteriori estimates as coherent vectors governing neural evolution, with alpha frequencies generating basic awareness, and cross-frequency phase-coupling within theta frequencies for access consciousness and volitional control. These dynamic cores of integrated information also function as global workspaces, centered on posterior cortices, but capable of being entrained with frontal cortices and interoceptive hierarchies, thus affording agentic causation. Integrated World Modeling Theory (IWMT) represents a synthetic approach to understanding minds that reveals compatibility between leading theories of consciousness, thus enabling inferential synergy.
自由能原理与主动推理框架(FEP-AI)始于这样一种认识:持续存在的系统必须调节与环境的交换并防止熵的积累。在FEP-AI中,心智和大脑是自主系统的预测控制器,其中行动驱动的感知被实现为概率推理。综合信息理论(IIT)始于考虑系统内在存在的前提条件以及关于意识本质的公理。IIT引发了争议,因为它有一些令人惊讶的推论:准泛心论;没有指涉物或动态的主观性;以及完全智能但无意识的大脑模拟的可能性。在这里,我描述了如何通过将IIT与FEP-AI整合来解决这些争议,其中综合信息仅意味着对于具有视角参照系的系统有意识,这些视角参照系能够为自我和世界生成具有空间、时间和因果连贯性的模型。如果没有与外部现实的那种联系,系统可能具有任意大量的综合信息,但仍然不会产生主观体验。我进一步描述了这些框架的整合如何可能有助于它们作为统一系统理论和涌现因果关系模型的发展。然后,受全局神经元工作空间理论(GNWT)和谐波大脑模式框架的启发,我描述了意识流如何作为不断演进的感觉运动预测的一代而出现,体验的精确组成取决于作为自组织谐波模式(SOHMs)的同步复合体的整合能力。这些整合动态尤其可能通过高度连接的子网发生,这些子网提供以身体为中心的现象绑定和执行控制源。沿着这些连接主干,SOHMs被提议通过在预测(自动编码)网络上的循环消息传递来实现turbo编码,从而生成作为支配神经进化的连贯向量的最大后验估计,阿尔法频率产生基本意识,theta频率内的跨频率相位耦合用于通达意识和意志控制。这些综合信息的动态核心也充当全局工作空间,以枕叶皮质为中心,但能够与额叶皮质和内感受层次结构同步,从而实现能动因果关系。综合世界建模理论(IWMT)代表了一种理解心智的综合方法,揭示了主要意识理论之间的兼容性,从而实现推理协同。