Related Experiment Video
Updated: Aug 8, 2025
10:58
TMS: Using the Theta-Burst Protocol to Explore Mechanism of Plasticity in Individuals with Fragile X Syndrome and Autism
Published on: December 28, 2010
17.0K
Macroscopic resting state model predicts theta burst stimulation response: A randomized trial
Neda Kaboodvand1,2,3, Behzad Iravani1,2, Martijn P van den Heuvel4
1Department of Neurology and Neurological Sciences, Stanford University, Stanford, California, United States of America.
Plos Computational Biology
|March 6, 2023
Summary
Whole-brain modeling identified distinct depression subtypes, predicting treatment response to repetitive transcranial magnetic stimulation (rTMS). This approach advances precision medicine for treatment-resistant depression.
Area of Science:
- Neuroscience
- Computational Psychiatry
- Medical Imaging
Background:
- Treatment-resistant depression (TRD) has limited remission rates, necessitating improved therapeutic strategies.
- Depression's heterogeneity requires personalized approaches beyond current treatments.
- Whole-brain modeling offers a framework to integrate multimodal data and understand disease complexity.
Purpose of the Study:
- To stratify patients with treatment-resistant depression into distinct subtypes using whole-brain modeling.
- To investigate if identified subtypes predict differential response to repetitive transcranial magnetic stimulation (rTMS).
- To explore baseline brain dynamics associated with treatment responsiveness.
Main Methods:
- Applied computational whole-brain modeling and probabilistic nonparametric fitting to resting-state fMRI data from 42 TRD patients.
- Stratified patients into subtypes based on baseline attractor dynamics.
- Assessed treatment response to active (rTMS) versus sham intervention.
Main Results:
- Identified two distinct depression subtypes with differing baseline phenotypic behaviors.
- Subtype stratification predicted differential response to active rTMS, not sham treatment.
- Patients with higher treatment response showed blunted intrinsic frequency dynamics (lower global metastability and synchrony) at baseline.
Conclusions:
- Whole-brain modeling can effectively stratify depression subtypes.
- This stratification predicts individualized response to rTMS, paving the way for precision psychiatry.
- Understanding intrinsic brain dynamics is crucial for tailoring depression treatments.
