Hasan Niazi

Explaining Cognitive and Perceptual Phenomena Through Resonance of Closed Neural Network Geometries (RCNNG): A Unified Framework

This revision introduces several key improvements to the RCNNG manuscript: Observer Reformulation: The observer definition was rewritten using the functional notation O(t)=R(G(t)) to remove any implication of an independent monitoring entity and to align it with RCNNG’s resonance...

Explaining Cognitive and Perceptual Phenomena Through Resonance of Closed Neural Network Geometries (RCNNG): A Unified Framework

This preprint presents the updated and expanded formulation of the RCNNG framework, a geometric–resonant theory proposing a unified foundation for perception, cognition, and conscious experience. In RCNNG, the fundamental units of mental processing are Closed Recurrent Geometries...

An Innovative Perspective to Profound Functions of the Brain: Hypothesis of Resonance of Closed Neural Network Geometries

This work presents the Resonance of Closed Neural Network Geometries (RCNNG) hypothesis, proposing that perception and consciousness arise from the formation and stabilization of Closed Resonant Geometries (CRGs) within adaptive recurrent neural networks. Structured and repeated...