Can digital twins be useful?
Personalized hybrid brain models uniting electromagnetism with physiology — neurotwins or NeTs — are poised to play a fundamental role in understanding and optimizing the effects of stimulation at the individual level. We ambition to deliver disruptive solutions through model-driven, individualized therapy.
Personalized brain models can capture novel neuroscience insights, reduce uncertainty in diagnosis, and provide the foundation for therapeutic breakthroughs. This can be achieved by taking into account for individual biophysical and physiological characteristics.
In this project we will develop advanced brain models that characterize individual pathology and predict the physiological effects of transcranial electromagnetic stimulation, and use them to design optimal brain stimulation protocols in Alzheimer's disease.
Neuropsychiatric disorders are a leading cause of global disability-adjusted life years, and solutions are lacking. Can digital twins be useful? At least in some cases, we hold they will be central to progress.
Recent findings suggest that non-invasive brain stimulation may be a valuable option in conditions such as epilepsy or Alzheimer's (AD). Still, a better understanding of mechanisms and patient-specific factors is needed.
Personalized hybrid brain models uniting the physics of electromagnetism with physiology —neurotwins or NeTs— are poised to play a fundamental role in understanding and optimizing the effects of stimulation at the individual level. We ambition to deliver disruptive solutions through model-driven, individualized therapy. We will build a computational framework —weaved and validated across scales and levels of detail— to represent the mechanisms of interaction of electric fields with brain networks and assimilate neuroimaging data. This will allow us to characterize the dynamical landscape of the individual brain and define strategies to restore healthy dynamics. Benefitting from existing databases of healthy and AD individuals, we will deliver the first human and rodent NeTs predicting the effects of stimulation on dynamics. We will then collect detailed multimodal measurements in mice and humans to improve the predictive power of local and whole-brain models under the effects of electrical stimulation and translate these findings into a technology pipeline for the design of new personalized neuromodulation protocols which we will test in a cohort of AD patients and healthy controls in randomized double-blinded studies.
With research at the intersecting frontier of nonlinear dynamics, network theory, biophysics, engineering, neuroscience, clinical research, and ethics, Neurotwin will deliver model-driven breakthroughs in basic and clinical neuroscience, with patients ultimately benefiting from safe, individualized therapy solutions.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101017716