This review synthesizes current understanding of metacognitive processes across neuroscientific, clinical, and educational domains. Metacognition, defined broadly to encompass knowledge/awareness, and monitoring/regulation of one’s cognitive processes spans both neurological and psychological domains. This quality holds significant implications for human development. Neuroimaging evidence suggests that metacognition relies on distributed networks spanning prefrontal-parietal circuits, with connections to the anterior cingulate and hippocampus. These regions demonstrate experience-dependent structural changes, as well as regulate the cognitive processes that drive neuroplastic behavior. The bifurcated model of metacognition, which distinguishes between metacognitive knowledge and regulation, represent an embodied perspective of a prediction based problem-solving framework that can be used to inform the development of clinical and educational interventions seeking to support neurodiversity. Evidence suggests that targeted intensive cognitive training may produce neural changes through well-characterized neuroplastic mechanisms. However, establishing causal links between metacognitive training specifically and structural brain reorganization requires additional research with appropriate neuroimaging protocols and control conditions. These converging lines of evidence establish a metacognitive problem-solving axis encompassing neural, cognitive, and behavioral functioning as the primary mechanism for controlled psychobiological reorganization. By focusing an individual’s powers of problem solving upon their own development and understanding of their own problem-solving process, clinical interventions can be developed that are less coercive and more supportive of individual neurodiversity. The neurological implications of metacognition suggest that individuals can be supported in developing the optimal environments, procedures, and pedagogies to improve their learning and development, in turn affecting their underlying neurological architecture.
Philip Ralph Hulbig (Tue,) studied this question.