Towards an Inter-Personalized Computational Psychiatry

Mental health is a multidimensional challenge, marked by rapid brain changes and essential interpersonal relationships. This complicates the application of traditional statistical methods and neuropsychiatric approaches classically focused on isolated individuals. The combination of artificial intelligence and multi-brain neuroscience offers an innovative path towards a holistic understanding that encompasses neurobiological, behavioral and social scales. These advanced technologies facilitate the analysis of dynamics and interactions, whether between genes, neurons, or even individuals. This more integrative perspective paves the way for inter-personalized computational psychiatry. Combining mathematical tools and models with an ecosocial approach promises to reinvent the detection and treatment of psychiatric disorders, but also opens the way to medicine beyond the individual.

Learning Objectives: 

1. Explain the basic principles of computational psychiatry.

2. Review how multi-brain neuroscience can integrate biological, behavioral, and social factors in mental health.

3. Summarize the potential of inter-personalized computational psychiatry in improving psychiatric care.