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Quantification of Filamentous Actin F-actin Puncta in Rat Cortical Neurons
Published on: February 10, 2016
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Induction and Quantification of Excitability Changes in Human Cortical Networks
Corey J Keller1,2,3,4,5, Yuhao Huang2, Jose L Herrero6
1Department of Neurosurgery, ckeller1@stanford.edu.
Summary
Human brain stimulation can alter cortical excitability. Baseline brain network connectivity accurately predicts which brain regions will change, paving the way for personalized brain stimulation therapies.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Neurophysiology
Background:
- Brain stimulation is a growing therapeutic tool for neuropsychiatric disorders.
- Understanding how stimulation induces lasting brain changes is crucial for personalization.
- Current knowledge on the precise mechanisms and locations of stimulation-induced plasticity is limited.
Purpose of the Study:
- To investigate how direct electrical brain stimulation alters cortical excitability in humans.
- To determine if a single stimulation session can induce lasting excitability changes.
- To model these changes based on individual subjects' baseline brain connectivity.
Main Methods:
- Applied repetitive direct electrical stimulation to prefrontal, temporal, and motor cortices in eight human subjects.
- Measured corticocortical-evoked potentials (CCEPs) before and after stimulation to assess excitability.
- Utilized individual prestimulation connectivity profiles to predict regions exhibiting excitability changes.
Main Results:
- Found that 10 Hz stimulation induced persistent (≥10 min) potentiation and suppression of excitability in specific regions.
- Identified that anatomical proximity and high-amplitude CCEPs predicted regions of excitability change.
- Achieved high accuracy (72-95%) in predicting responsive regions using baseline connectivity, significantly improving model performance.
Conclusions:
- Baseline connectivity profiles accurately predict brain regions susceptible to stimulation-induced changes.
- This predictive capability forms a foundation for personalizing brain stimulation protocols.
- The findings contribute to understanding human brain dynamics post-stimulation and optimizing treatment strategies.
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