{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T06:03:54Z","timestamp":1789625034182,"version":"build-2803163510"},"reference-count":33,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T00:00:00Z","timestamp":1789603200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Comput. Neurosci."],"abstract":"<jats:p>Human conscious thought often appears as a diffuse, unstable, and only partly verbalizable field until attention, questioning, decision, or speech stabilizes it into a reportable form. This manuscript develops a quantum-inspired neural framework for that transition. The proposal does not claim that consciousness literally depends on microscopic quantum computation, that the brain implements a physical quantum computer, or that neuronal tissue maintains macroscopic quantum coherence. Instead, it uses the mathematical architecture of quantum theory\u2014state vectors, density matrices, projection operators, non-commuting measurements, interference, decoherence-like contextual stabilization, and state reduction\u2014as a formal language for modeling the transformation from latent conscious potential to reportable thought. In the proposed framework, pre-report consciousness is represented as a high-dimensional latent neural-cognitive state over candidate thoughts. This state evolves under a neural-cognitive Hamiltonian shaped by memory, salience, affect, attention, language, task demands, and spontaneous associative dynamics. A question such as \u201cWhat are you thinking about?\u201d is modeled as a measurement context that selects a basis and projects the latent state into a reportable cognitive eigenstate. The framework, therefore, treats an introspective report not as a passive readout of a pre-existing mental object but as an active state-reducing operation. Illustrative simulations demonstrate three formal consequences: (1) Non-commuting introspective questions generate order effects; (2) selective reporting reduces candidate-state entropy and suppresses off-diagonal latent coherence; and (3) overlapping candidate thoughts can produce interference-like probability structures. The model generates testable predictions for experience sampling, electroencephalography (EEG)\/magnetoencephalography (MEG)\/functional magnetic resonance imaging (fMRI) representational decoding, intracranial recordings, and perturbation studies: Introspective reports should depend on question order; spoken reports should reduce latent-state entropy more strongly than silent attention; ambiguous thought states should exhibit interference-like probability signatures; and neural activity should transition from high-dimensional latent dynamics toward lower-dimensional, report-stabilized states. Neural state reduction provides a computational bridge among quantum cognition, consciousness science, metacognition, global access, and the neuroscience of reportability.<\/jats:p>","DOI":"10.3389\/fncom.2026.1865388","type":"journal-article","created":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T05:33:45Z","timestamp":1789623225000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Neural state reduction: a quantum-inspired framework for how latent conscious thought becomes reportable"],"prefix":"10.3389","volume":"20","author":[{"given":"A. 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