Controlling Neural Oscillations and Synchrony
Author Information
Author(s): Lena Salfenmoser, Klaus Obermayer
Primary Institution: Technische Universitaet Berlin
Hypothesis
Can we adapt optimal control theory to manage oscillations and synchrony in neural population dynamics without a specified reference trajectory?
Conclusion
The study successfully demonstrates new cost functionals that allow for the control of oscillations and synchrony in neural networks without needing a precise reference trajectory.
Supporting Evidence
- The study introduces three new cost functionals that enhance the application of optimal control theory to neural dynamics.
- Control strategies were successfully applied to both single-node and multi-node neural models.
- The methods allow for the control of oscillations without needing a precise reference trajectory.
Takeaway
This research shows how to control brain waves and synchronization in groups of neurons using new mathematical methods, making it easier to study and influence brain activity.
Methodology
The study uses non-linear optimal control theory to compute efficient stimulation for neural population dynamics, applying various cost functionals to control oscillations and synchrony.
Limitations
The methods require a defined target frequency for oscillations and may not effectively induce frequency synchrony with fixed phase shifts.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website