From the origins to the stream of consciousness and its neural correlates
Frontiers in Integrative Neuroscience November 4, 2022 DOI: 10.3389/fnint.2022.928978
Summary
AI-generated from the abstractConsciousness science has many competing theories but lacks a unifying framework. The Cognitive Evolution Theory (CET) proposes that brains evolved first as volitional subsystems from primitive reflexes, not as prediction machines. CET models the stream of consciousness as a discrete chain of momentary states arising from critical brain dynamics at phase transitions, mapped onto neural correlates. This framework integrates insights from existing theories by treating consciousness as a dynamical, evolutionary phenomenon. It uses entropy-based complexity measures as objective observables for the transient level of consciousness, linking continuous brain dynamics to discrete conscious states triggered by brainstem arousal and modulated by thalamocortical systems.
Study at a glance
| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key finding | The Cognitive Evolution Theory provides a unifying framework for consciousness by modeling it as a discrete chain of states derived from critical brain dynamics and evolutionary volitional origins. |
Abstract
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.