Yurchenko Sergey B
Independent Research Center of Brain and Consciousness, Andijan, Uzbekistan.
Front Integr Neurosci. 2022 Nov 4;16:928978. doi: 10.3389/fnint.2022.928978. eCollection 2022.
There are now dozens of very different theories of consciousness, each somehow contributing to our understanding of its nature. The science of consciousness needs therefore not new theories but a general framework integrating insights from those, yet not making it a still-born "Frankenstein" theory. First, the framework must operate explicitly on the stream of consciousness, not on its static description. Second, this dynamical account must also be put on the evolutionary timeline to explain the origins of consciousness. The Cognitive Evolution Theory (CET), outlined here, proposes such a framework. This starts with the assumption that brains have primarily evolved as volitional subsystems of organisms, inherited from primitive (fast and random) reflexes of simplest neural networks, only then resembling error-minimizing prediction machines. CET adopts the tools of critical dynamics to account for metastability, scale-free avalanches, and self-organization which are all intrinsic to brain dynamics. This formalizes the stream of consciousness as a discrete (transitive, irreflexive) chain of momentary states derived from critical brain dynamics at points of phase transitions and mapped then onto a state space as neural correlates of a particular conscious state. The continuous/discrete dichotomy appears naturally between the brain dynamics at the causal level and conscious states at the phenomenal level, each volitionally triggered from arousal centers of the brainstem and cognitively modulated by thalamocortical systems. Their objective observables can be entropy-based complexity measures, reflecting the transient level or quantity of consciousness at that moment.
目前有几十种截然不同的意识理论,每一种都在某种程度上有助于我们理解其本质。因此,意识科学需要的不是新理论,而是一个整合这些理论见解的通用框架,同时又不会使其成为一个胎死腹中的“科学怪人”理论。首先,该框架必须明确作用于意识流,而不是对其进行静态描述。其次,这种动态描述还必须置于进化时间线上,以解释意识的起源。本文概述的认知进化理论(CET)提出了这样一个框架。它首先假设大脑主要是作为生物体的意志子系统进化而来的,从最简单神经网络的原始(快速且随机)反射继承而来,之后才类似误差最小化预测机器。CET采用临界动力学工具来解释亚稳定性、无标度雪崩和自组织,这些都是大脑动力学的固有特征。这将意识流形式化为一个离散(可传递、非自反)的瞬时状态链,这些状态源自相变点的临界大脑动力学,然后映射到一个状态空间,作为特定意识状态的神经关联物。在因果层面的大脑动力学和现象层面的意识状态之间,连续/离散二分法自然出现,每一种状态都由脑干的唤醒中心意志性触发,并由丘脑皮质系统进行认知调节。它们的客观可观测指标可以是基于熵的复杂性度量,反映那一刻意识的瞬态水平或数量。