Zenodo (CERN European Organization for Nuclear Research)
July 9, 2026
Jiaping Wang
Consciousness arises as an engineering necessity: a self-referential closed loop is the optimal solution for a system that must persist under resource constraints. When temporal integration capacity crosses a critical threshold, the system inevitably attributes causal chains to a single persistent subject—the 'self.' Qualia are endogenous calibration signals of this loop, an optimal encoding format under evolutionary time pressure. The explanatory gap between first-person and third-person perspectives stems from time's irreversibility. A five-level consciousness spectrum and a resource-depletion explanatory spectrum for mental disorders are derived, along with four hard constraints for AGI.
Zenodo (CERN European Organization for Nuclear Research)
June 18, 2026
Jiaping Wang
A new theoretical model proposes that consciousness emerges from self-referential closed loops constrained by the brain's limited energy (20 watts), survival goals, and discrete inputs. It quantifies consciousness using three variables: temporal span, reconstructive activity, and closed-loop integrity. The model distinguishes two systems—automated memory archiving (System B) and temporal self-narrative (System A)—and describes a five-level consciousness spectrum (L0 to L3). Language is identified as a natural metric for these variables. The framework aims to unify explanations for sleepwalking, dreaming, anesthesia, empathy, and disorders like Alzheimer's, and sets thresholds for artificial general intelligence and distributed consciousness.
Zenodo (CERN European Organization for Nuclear Research)
June 18, 2026
Jiaping Wang
A hierarchical self-referential closed-loop model of consciousness is constructed from three axioms: finite resources, survival goals, and discrete inputs. The model uses temporal span, reconstruction activity, and closed-loop integrity to derive a five-level consciousness spectrum and distinguish two systems: automated material archiving and temporal self-narrative. Language is identified as a natural metric for these variables, with each grammatically complete sentence forming a micro self-referential loop. The framework provides unified explanations for phenomena including sleepwalking, dreaming, anesthesia, and hierarchical empathy, and proposes a differential diagnostic approach for Alzheimer's disease and vascular cognitive impairment. Testable experimental hypotheses are offered.
Zenodo (CERN European Organization for Nuclear Research)
June 18, 2026
Jiaping Wang
Existing theories of consciousness emphasize static causal structures but overlook the brain's 20-watt power constraint and temporal dynamics, failing to unify phenomena like parasomnias, clinical disorders, and cross-species differences. This paper proposes a hierarchical self-referential closed-loop model based on three axioms—limited resources, survival goals, and discrete inputs—quantified by temporal span (T), reconstructive activity (A), and closed-loop integrity (C). The model derives a two-step emergence geometry for self-reference, distinguishes System B (automated archiving) from System A (temporal narrative), and establishes a five-level consciousness spectrum (L0 to L3). Language is identified as a natural metric for T, A, and C, enabling a diagnostic framework for Alzheimer's disease versus vascular cognitive impairment. The framework unifies phenomena including hypoglycemic anxiety, sleepwalking, dreaming, anesthesia, and hierarchical empathy, and specifies thresholds for AGI and distributed consciousness.
Zenodo (CERN European Organization for Nuclear Research)
June 18, 2026
Jiaping Wang
A new hierarchical self-referential closed-loop model of consciousness is proposed, based on three axioms: limited resources, survival goals, and discrete inputs. It quantifies consciousness using temporal span, reconstructive activity, and closed-loop integrity, deriving a two-step emergence geometry and distinguishing two systems: automated memory archiving and temporal self-narrative. Language is identified as a natural metric for these variables, with each grammatically complete sentence constituting a micro self-referential loop. The model explains phenomena such as hypoglycemic anxiety, sleepwalking, dreaming, anesthesia, and hierarchical empathy, and specifies thresholds for artificial general intelligence and distributed consciousness. Testable experimental hypotheses are proposed.
Zenodo (CERN European Organization for Nuclear Research)
June 18, 2026
Jiaping Wang
Existing theories of consciousness overemphasize static causal structures while neglecting the brain's 20-watt power constraint and temporal dynamics. This paper proposes a hierarchical self-referential closed-loop model based on three axioms: limited resources, survival goals, and discrete inputs. The model quantifies consciousness using temporal span (T), reconstructive activity (A), and closed-loop integrity (C), deriving a two-step emergence geometry and distinguishing System B (automated archiving) from System A (temporal self-narrative). It explains phenomena such as sleepwalking, dreaming, anesthesia, and hierarchical empathy; identifies language as a natural metric for T, A, and C; and offers a diagnostic framework for Alzheimer's disease versus vascular cognitive impairment. The framework claims unified axioms, cross-domain explanatory power, and quantifiable variables.
Zenodo (CERN European Organization for Nuclear Research)
June 18, 2026
Jiaping Wang
Existing consciousness theories emphasize static causal structures but overlook the brain's 20-watt power constraint and temporal dynamics, failing to unify phenomena like parasomnias, clinical disorders, and cross-species differences. This paper proposes a hierarchical self-referential closed-loop model based on three axioms: limited resources, survival goals, and discrete inputs. The model quantifies consciousness via temporal span (T), reconstructive activity (A), and closed-loop integrity (C), deriving a two-step emergence geometry and distinguishing System B (automated archiving) from System A (temporal self-narrative). It identifies language as a natural metric for T, A, and C, and offers a diagnostic framework for Alzheimer's versus vascular cognitive impairment, along with unified explanations for sleepwalking, dreaming, anesthesia, and empathy.
Zenodo (CERN European Organization for Nuclear Research)
June 18, 2026
Jiaping Wang
A new theory of consciousness proposes that the brain's 20-watt power limit and the timing of neural activity are essential for explaining sleep disorders, clinical consciousness problems, and differences across species. The model uses three axioms—limited resources, survival goals, and discrete inputs—to define consciousness with three variables: temporal span, reconstruction activity, and closed-loop integrity. It describes how self-referential loops emerge through two steps, distinguishes two cognitive systems, explains forgetting and memory as narrative construction, and redefines qualia as internal calibration signals. The theory establishes a five-level consciousness spectrum, uses language as a measurement tool, and offers a diagnostic framework for Alzheimer's disease.
Zenodo (CERN European Organization for Nuclear Research)
June 18, 2026
Jiaping Wang
A new theoretical model of consciousness starts from three axioms—limited resources, survival priority, and discrete input—to construct a hierarchical self-referential closed-loop system. The model is quantified by temporal span (T), reconstruction activity (A), and closed-loop integrity (C). It explains how the brain allocates its 20-watt power budget between two main patterns: a low-power baseline (B-Configuration) and an overlay for self-referential loops (S-Configuration). Forgetting has a dual mechanism, memory is narrative construction, and qualia are endogenous calibration signals. The hard problem of consciousness is reframed as a parameter interval problem. A five-level consciousness spectrum is delineated, and a framework for Alzheimer's differential diagnosis is proposed.
Zenodo (CERN European Organization for Nuclear Research)
June 18, 2026
Jiaping Wang
A new theory of consciousness starts from three basic facts: the brain has limited energy (about 20 watts), it must keep the organism alive, and it receives information in discrete chunks. From these, the model describes consciousness as a self-referential closed loop with three measurable variables—temporal span, reconstructive activity, and closed-loop integrity. It explains phenomena like sleepwalking, dreaming, anesthesia, and differences across species, and proposes a five-level consciousness spectrum. Language is used as a natural measure: each complete sentence forms a tiny self-referential loop. The framework also offers a way to distinguish Alzheimer's disease from vascular cognitive impairment and suggests thresholds for artificial general intelligence and distributed consciousness.
Zenodo (CERN European Organization for Nuclear Research)
June 18, 2026
Jiaping Wang
A new theoretical model proposes that consciousness arises from a self-referential closed loop in the brain, constrained by its 20-watt power budget. The model starts with three axioms: limited resources, survival goals, and discrete inputs. It quantifies consciousness using temporal span, reconstruction activity, and closed-loop integrity. Two energy allocation patterns are identified: a low-power baseline configuration and a self-referential overlay. The model reframes the hard problem of consciousness as a parameter-interval problem, defines qualia as calibration signals, and proposes a five-level consciousness spectrum. It also offers a diagnostic framework for Alzheimer's disease and specifies thresholds for artificial general intelligence.