Related Experiment Video
Updated: Apr 1, 2026
09:57
Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization
Published on: September 20, 2024
3.9K
Optimal stimulus scheduling for active estimation of evoked brain networks
MohammadMehdi Kafashan1, ShiNung Ching
1Department of Electrical and Systems Engineering, Washington University in St. Louis, MO 63130, USA.
Journal of Neural Engineering
|October 9, 2015
Summary
This study introduces an optimal probing strategy for understanding dynamic neural networks, crucial for neural mapping. The method efficiently schedules probes to reveal time-varying connections in real-time applications.
Area of Science:
- Neuroscience
- Systems Biology
- Control Theory
Background:
- Estimating neural connectivity is vital for understanding brain function.
- Dynamic networks, where connections change over time, present unique challenges for mapping.
Purpose of the Study:
- To develop an optimal probing strategy for learning connections in evoked dynamic networks.
- To apply this to neural mapping and connectivity estimation.
Main Methods:
- Formulated the evoked network in state-space.
- Adapted optimal sensor scheduling principles.
- Employed expectation-maximization for online parameter updates.
Main Results:
- The greedy probing strategy has a convenient form and is optimal over a finite horizon under certain conditions.
- Demonstrated the approach's efficacy through numerical examples.
Conclusions:
- The proposed method offers a principled way to actively probe time-varying neuronal connections.
- The real-time implementable method is suitable for stimulation-based cortical mapping of dynamic networks.
