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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.17064144 |
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Table of Contents:
- <p>This work introduces a filtration-based model of decision-making grounded in the Possest–PQF framework. Rejecting classical notions of representation, finality, and linear computation, the model proposes that <span><strong>phase coherence in neural activity</strong></span> operates as a bifurcating filtration mechanism rather than a goal-oriented process. Through the lens of <span><strong>Recursio Intensitatis</strong></span>, we analyze EEG data as a dynamic topological field of accessible trajectories, wherein decision points emerge not as endpoints, but as reorganizations of intensities within a metastable membrane.</p> <p>We test this model using real EEG recordings from RSVP tasks, constructing cubical complexes and persistent diagrams to detect shifts in bruzdy (furrows of filtration). The results reveal that phase synchronization correlates with transitions in accessibility fields, offering a reproducible, computationally viable and ontologically novel account of cognitive dynamics. Three test predicates (P1–P3) are formulated to verify bifurcational filtering without presupposing representational closure.</p> <p>This study contributes to the ongoing reconfiguration of intelligence theory, proposing a <span><strong>non-representational, intensity-driven ontology of cognition</strong></span>, and offering a reproducible method for identifying decision bifurcations in empirical neural data. Unlike mainstream AGI models, this approach prioritizes <span><strong>filtration over function</strong></span>, <span><strong>availability over computation</strong></span>, and <span><strong>Recursio over convergence</strong></span>.</p> <blockquote><span><strong>Keywords</strong></span>: PQF, Recursio Intensitatis, phase coherence, EEG, filtration, decision bifurcation, topological dynamics, AGI, Possest.</blockquote> <p> </p>