Digital Twin Brain: Generating Multitask Behavior from Connectomes for Personalized Therapy.

ABSTRACT: Objective: This study introduces and validates a digital twin brain framework designed to translate an individual's brain connectome into predictions of multitask neurobehavioral dynamics and personalized functional modulations. Impact Statement: We introduce a novel 2-component architecture-where a hypernetwork personalizes a main network from an individual's connectome-establishing a mechanistic platform to simulate and design personalized interventions by directly linking connectomes to behavior. Introduction: Personalized psychiatry requires digital twin models that can predict functions across multiple domains, such as affective and cognitive processing, from an individual's unique neurobiology. However, existing models struggle to bridge the gap between brain str

SUBMITTER: Takahashi Y 

PROVIDER: S-EPMC12895553 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature