Qualia as query act, the phenomenology of predictive error coding.

Consciousness, especially the subjective, ineffable quality of experience known as qualia, can be better understood by combining phenomenology with neuroscience. Drawing on Thomas Nagel's question about what it is like to be something and Husserlian phenomenology, the paper proposes that predictive error coding (PEC) offers a neuroscientific model for this integration. PEC treats the brain as an active inference system that continuously generates and updates predictions about sensory inputs. The concept of "query acts" is introduced to describe the brain's interrogative engagement with sensory information, linking phenomenological intentionality with predictive mechanisms.

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Abstract

This paper explores the intersection of phenomenology and neuroscience to address foundational questions about consciousness, particularly the nature of qualia-subjective, ineffable contents of experience. Drawing on Thomas Nagel's seminal inquiry into subjective experience and Husserlian phenomenology, we propose that phenomenological "What is it like?" questions can be integrated with neuroscientific models through predictive error coding (PEC). PEC reconceptualizes the brain as an active inference system, continuously generating and updating predictions about sensory inputs. We introduce the concept of "query acts" to describe the brain's interrogative engagement with sensory information, linking intentionality in phenomenology with predictive mechanisms in neuroscience. By framing qualia as dynamic processes arising from query acts rather than static entities, we bridge the explanatory gap between subjective experience and objective inquiry. This interdisciplinary framework highlights structural parallels between noetic processes in phenomenology and PEC in neuroscience, providing a novel perspective on the emergence of conscious experience. Additionally, we explore the implications of query acts for clinical interventions in psychiatric disorders and the development of context-sensitive artificial intelligence systems. This synthesis fosters deeper integration of philosophical and scientific approaches to understanding the nature of consciousness.