Affiliation:
1. Department of Computer Science & Engineering, Jhulelal Institute of Technology, Nagpur, India
Abstract
This chapter explores innovative methodologies at the intersection of neuroscience, psychology, and technology to advance our understanding of ADHD. By combining multimodal data integration, virtual reality (VR), longitudinal data analysis, and deep phenotyping, researchers gain comprehensive insights. The integration of diverse data sources is facilitated by advanced machine learning and artificial intelligence. VR environments provide controlled simulations for assessing attention and impulse control in real-life scenarios. Longitudinal studies track individuals over time, mapping symptom progression and treatment responses. Deep phenotyping enhances ADHD subtype characterization, encompassing cognitive profiles, sensory processing, emotional regulation, and executive functions. This integrated approach offers a nuanced understanding of ADHD heterogeneity, potentially informing precise diagnostics and personalized interventions. Ethical considerations and careful validation are emphasized as researchers navigate this integrative approach's uncharted territories.