NeuroVitalizer: Decoding Multimodal TBI Markers for Optimized Recovery
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Traumatic brain injury (TBI) occurs when mechanical forces shake the brain and disrupt normal brain function, affecting biological processes like cellular, molecular, and electrical functions. These processes are highly interconnected, making it difficult to fully understand TBI recovery with traditional single-discipline methods. Current approaches often fail to address the complexity of TBI even in mild to moderate cases, creating an urgent need for new methods to overcome existing limits in data collection, integration, and interpretation across multiple subdisciplines. In this project, I will set up a new framework for a comprehensive and systematic analysis of recovery processes post-trauma and the effect of electrical stimulation (ES) in in vitro models for mild to moderate TBI, which allows for a detailed examination in a controlled environment. Our experimental workflow will integrate insights on cellular morphology from microscopy images, electrical activity, and network synchronization from multi-electrode array recordings, protein expression changes from immunostaining, and cell viability and stress markers found in the cell medium. Calcium imaging will provide insights into ionic homeostasis maintenance. An AI-driven data fusion approach will facilitate the analysis of these multimodal datasets revealing hidden patterns and relationships that traditional approaches cannot uncover. Specifically, we want to address questions such as
This project introduces a cutting-edge method by integrating a multimodal data fusion setup and AI-based synthesis to tackle TBI recovery from multiple angles, capturing the complexity that standard approaches miss. Funding: European Research Council (ERC) - Starting Grant awarded in September 2025 |
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