Breath and Brain Function with Algorithm Technology
Yusuke Miyake
MPRA Paper from University Library of Munich, Germany
Abstract:
This study introduces an innovative interdisciplinary framework linking neuroscience,psychiatry, and health economics to analyze how nasal breathing, particularly left nostril breathing (LNB), influences brain activity and psychiatric disorders, including attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder, and epilepsy. Traditional pharmacological treatments, while effective, often pose substantial side effects and economic burdens. In contrast, emerging evidence from neuroscientific studies using functional magnetic resonance imaging (fMRI) reveals that LNB selectively improves critical regions of the right hemisphere of the brain, specifically the prefrontal cortex, amygdala, hippocampus and insular cortex, thus improving emotional stability, cognitive performance, and autonomic regulation without adverse effects. Integrating advanced artificial intelligence (AI) algorithms and personalized medical data (e.g., EEG, MRI, blood tests) optimizes therapeutic strategies, precisely aligning patient needs with targeted interventions. By modeling healthcare interactions through endogenous growth theory and R&D-driven market dynamics, this research highlights how AI-driven personalized medical solutions can improve productivity, reduce healthcare expenditures and significantly increase societal welfare and economic growth. This paper thus presents a pioneering contribution to medical economics, proposing a sustainable and effective healthcare model optimized by neuroscience and AI technologies.
Keywords: Left Nostril Breathing (LNB); Psychiatric Disorders; Brain Function; Artificial Intelligence (AI); Health Economics; Endogenous Growth Model; R\&D; Algorithm Economy; Personalized Medicine. (search for similar items in EconPapers)
JEL-codes: D83 I11 I18 O31 O33 (search for similar items in EconPapers)
Date: 2025-05-11
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:124699
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