THE LASER COGNITION (LC): A Multilevel Neurocognitive, Mathematical, and Cybernetic Framework of Awareness-Guided Attentional Illumination, Neural-Pattern Integration, and Novel Idea Emergence

AbstractThe Laser Cognition (LC) is a proposed multilevel theoretical framework for investigating how selective attention, conscious access, curiosity-guided inquiry, associative recruitment, and representational integration may contribute to the emergence and evaluation of novel ideas. Its central explanatory metaphor is laser illumination: a complex cognitive field contains multiple thoughts, memories, representations, and potential relationships, while a selected cognitive target receives processing priority. The framework uses this metaphor to organize a proposed mechanism linking cognitive-field activation, attentional targeting, awareness-mediated processing, focus regulation, associative recruitment, integrative recombination, candidate generation, and metacognitive evaluation.LC retains the distinction between the full theory, its default mechanism, and its canonical primary case. The primary case is the Laser-Spotlight Cognitive Genesis Case (LSCGC); the proposed default mechanism is the Laser Cognition Default Mechanism (LC-DM); and its principal operational cycle is the Laser-Guided Cognitive Integration Cycle (LGCIC).The framework is formalized using a weighted cognitive graph, a dual-route attentional-targeting model, a normalized attentional-allocation function, a focus-stability measure, an associative-recruitment equation, a cognitive-integration index, a probabilistic candidate-emergence model, and a feedback-control representation. The mathematical expressions constitute proposed model specifications, not established equations of human neural operation. Awareness, attention, curiosity, affective engagement, cognitive flexibility, and metacognitive monitoring are treated as related but conceptually distinct constructs.The architecture includes eighteen layers, a multidomain research structure, eight initial research hypotheses, explicit falsifiability requirements, a cross-system functional generalization framework, a fourteen-step research protocol, and a twenty-part manuscript structure. Human cognition is the primary explanatory domain. Applications to artificial intelligence, large language models, artificial general intelligence, and possible artificial superintelligence are framed as hypotheses about functional or computational correspondence rather than established claims of shared consciousness or identical mechanisms.LC is presented as a theory-development and validation framework. Its explanatory value, novelty, causal assumptions, parameter identifiability, empirical adequacy, and cross-domain applicability remain subject to systematic literature review, mathematical audit, empirical testing, model comparison, and replication.