This lecture presents two recent clinical case studies using TVB: stroke recovery and dementia (due to Alzheimer’s Disease (AD)).
Using a multi-scale neurophysiological model based on empirical multi-modal neuroimaging data, we show how local and global biophysical parameters characterize changes in individualized patient-specific brain dynamics, predict recovery of motor function for stroke patients, and correlate with individual differences in cognition for AD patients.
Topics covered in this lesson by Randy McIntosh
- General introduction to stroke
- TVB simulation workflow for stroke patients
- Structural reconstruction: “Virtual Brain Transplant”
- Parameter space exploration and fitting
- General introduction to dementia
- TVB simulation workflow for patients with dementia
- Pre-processing issues related to atrophy
- Two-stage modeling: sub- and full-brain network model
- Cognition predictor: model parameters vs. metrics of neuroimaging data