From Neuroscience to Startup: Developing an AI-Driven EEG Tool for Early Detection of Cognitive Impairment

Abstract:

Early detection of cognitive impairment remains a major challenge in modern healthcare. Current screening methods rely heavily on subjective cognitive assessments, often leading to delayed or missed diagnoses. This gap highlights the urgent need for objective, accessible, and scalable solutions.

This seminar presents the scientific and translational journey behind NeuReveal, a startup emerging from neuroscience and AI-driven medical research. The core innovation, the NEED (Neuromonitoring EEG for Early Detection of Dementia) tool, combines portable electroencephalography (EEG), a targeted stimulation protocol (Mnemosyne), and explainable artificial intelligence (CACTUS) to extract objective brain biomarkers for the early detection of cognitive impairment.  

The talk will cover the scientific background underpinning the approach, the mission of NeuReveal, and how the team navigated the transition from academic research to a startup, including organisational choices and interdisciplinary collaboration. It will also address the challenges encountered in building the company. Preliminary results from a pilot study will be presented, demonstrating promising potential for scalable early screening.

Finally, the seminar will reflect on key lessons learned during this process and provide practical insights for researchers interested in translating scientific innovation into real-world impact.

About the authors:

Rosmary Blanco (PhD Student in Computational Neuroscience)

Rosmary is a biotechnologist with experience in data recordings and analysis in the neurological, neurosurgical, and neurorehabilitation fields. She specializes in clinical network neuroscience and has skills in complex electrophysiological signal processing, particularly EEG source functional connectivity and network analysis. Her main interest is studying the large-scale network principles governing neuronal communication, cognition, and human behavior through computational approaches, personalized medicine, and clinical decision support.

Luca Gherardini (PhD Student in Computational Intelligence)

Luca holds a PhD in Medicine from Queen’s University Belfast and a Master’s of Science degree in Computer Science from the University of Modena and Reggio Emilia. His research spans several fields, such as Machine Learning, multi-agent systems, neuroscience, and autonomous driving.