Brain's Qubit

Chapter 9: Brain as Processor

Cognitive Architectures for Consciousness

Having explored the rich phenomenology of contemplative states

(Chapters 2-4), the methods used to cultivate them (Chapter 5), and the

current neuroscientific understanding of their neural correlates

(Chapters 7-8), we now continue our exploration within Part

II by turning to the crucial theoretical challenge: developing

explanatory frameworks that can account for consciousness itself,

particularly in light of the data presented. How can we model the

relationship between brain activity and subjective experience? What

principles govern the emergence of awareness? This chapter begins our

examination of several major theoretical approaches, focusing on models

grounded primarily in cognitive science and

computational neuroscience.

These frameworks attempt to explain consciousness in terms of

specific information processing architectures, cognitive functions, or

computational principles thought to be implemented in the brain. They

often focus on identifying the functional prerequisites or computational

mechanisms necessary for conscious awareness to occur, effectively

viewing the brain as a sophisticated processor. We will examine three

influential families of theories: Predictive Processing

(and its extension, Active Inference), which views the brain as a

prediction engine; Integrated Information Theory (IIT),

which defines consciousness in terms of a system’s capacity for

integrated information; and Global Workspace Theory

(GWT), which models consciousness as information being

broadcast within a central cognitive workspace. For each, we will

outline its core ideas, discuss its potential application to

understanding contemplative states, and critically evaluate its

strengths and limitations. We will also briefly consider the relevance

and limits of drawing parallels between emergent behaviors in artificial

intelligence and the emergence of consciousness in biological systems, a

comparison often invoked in computational approaches. These cognitive

and computational models provide essential groundwork before we explore

information-centric and quantum perspectives in subsequent chapters.