Cortical Inhibition Drives iTBS Efficacy in Treatment-Resistant Depression
Presented During:
Friday, June 27, 2025: 11:30 AM - 12:45 PM
Brisbane Convention & Exhibition Centre
Room:
Great Hall
Poster No:
385
Submission Type:
Abstract Submission
Authors:
Davide Momi1, Zheng Wang2, Mohammad Oveisi2, Zafiris Daskalakis3, Christoph Zrenner2, Reza Zomorrodi2, Rebecca Strafella2, Fidel Vila Rodriguez4, Yoshihiro Noda5, Jonathanr Downar6, Jennifer Lissemore1, Manish Saggar1, Nolan Williams1, Corey Keller1, Daniel Blumberger2, Daphne Voineskos2, John Griffiths2
Institutions:
1Stanford University, Stanford, CA, 2Centre for Addiction and Mental Health, Toronto, Ontario, 3UC San Diego, San Diego, CA, 4UBC Department of Psychiatry, Division of Neuroscience and Translational Psychiatry, Vancouver, British Columbia, 5Keio University School of Medicine, Tokyo, Japan, 6Department of Psychiatry, Toronto Western Hospital, Toronto, Ontario
First Author:
Co-Author(s):
Fidel Vila Rodriguez
UBC Department of Psychiatry, Division of Neuroscience and Translational Psychiatry
Vancouver, British Columbia
UBC Department of Psychiatry, Division of Neuroscience and Translational Psychiatry
Vancouver, British Columbia
Introduction:
Depression remains a significant global health challenge, with Intermittent Theta Burst Stimulation (iTBS) targeting the left dorsolateral prefrontal cortex (DLPFC) as a promising intervention for treatment-resistant depression. However, the neurophysiological mechanisms driving its clinical efficacy are not fully understood.
Methods:
The analyses conducted in this study consist of four components: (i) stimulation-evoked responses, (ii) construction of anatomical connectivity priors using diffusion-weighted MRI tractography, (iii) simulation of whole-brain dynamics with a connectome-based neural mass model, and (iv) fitting of the model to individual-subject scalp EEG data (Figure 1).
We analyzed pre- and post-iTBS EEG data from 90 MDD patients. Single-pulse TMS-EEG evoked responses and HRSD-17 depression scale scores were recorded before and after 30 sessions of iTBS over 6 weeks (Figure 1A). iTBS was applied to the L-DLPFC, with 200 pulses per session.
The Jansen-Rit model, a neural mass model with pyramidal, excitatory, and inhibitory populations, was embedded in 200 brain regions (Schaefer atlas, Figure 1B). Anatomical connectivity priors were derived from group-average streamline counts in the HCP dataset. TMS-induced excitation was modeled as a voltage offset to the excitatory population. Regional time series were projected to EEG channel space via a lead field matrix, generating simulated EEG activity. Model optimization, using the ADAM algorithm, fit simulated responses to empirical data. For details regarding the computational model and the parameters estimation please refer to Momi et al., 2023, 2024.
Stimulus-evoked spectral power (2–50 Hz) was computed for pre- and post-iTBS sessions. Statistical comparisons used permutation testing and cluster-based thresholding to assess significant changes, averaged across subjects to compare responders and non-responders. Relationships between spectral changes and Jansen-Rit model parameters were also analyzed.
We analyzed pre- and post-iTBS EEG data from 90 MDD patients. Single-pulse TMS-EEG evoked responses and HRSD-17 depression scale scores were recorded before and after 30 sessions of iTBS over 6 weeks (Figure 1A). iTBS was applied to the L-DLPFC, with 200 pulses per session.
The Jansen-Rit model, a neural mass model with pyramidal, excitatory, and inhibitory populations, was embedded in 200 brain regions (Schaefer atlas, Figure 1B). Anatomical connectivity priors were derived from group-average streamline counts in the HCP dataset. TMS-induced excitation was modeled as a voltage offset to the excitatory population. Regional time series were projected to EEG channel space via a lead field matrix, generating simulated EEG activity. Model optimization, using the ADAM algorithm, fit simulated responses to empirical data. For details regarding the computational model and the parameters estimation please refer to Momi et al., 2023, 2024.
Stimulus-evoked spectral power (2–50 Hz) was computed for pre- and post-iTBS sessions. Statistical comparisons used permutation testing and cluster-based thresholding to assess significant changes, averaged across subjects to compare responders and non-responders. Relationships between spectral changes and Jansen-Rit model parameters were also analyzed.
·Figure 1. Overview of study design and methodological workflow for subject-specific connectome-based whole-brain modeling of TMS evoked potentials.
Results:
To investigate iTBS effects on evoked spectral power, we compared time-frequency responses between responders and non-responders. Responders showed a significant reduction in 3–10 Hz power post-iTBS, while non-responders exhibited no such change, highlighting a low-frequency power decrease specific to responders (Figure 2A). This reduction correlated negatively with changes in excitatory-to-pyramidal cell connection strength (r = -0.56, p < 0.001; Figure 2B), suggesting that increased inhibition, driven by iTBS, diminishes low-frequency evoked responses.
Simulations reducing excitatory-to-pyramidal connection strength by 10%, 30%, and 50% mirrored this pattern, with a pronounced decrease in TEP amplitudes, particularly in late components, as seen in a participant with severe MDD (Figure 2C). Group-level comparisons between original and simulated spectra with 50% inhibition revealed reduced low-frequency power, aligning with responders' empirical findings (Figure 2D).
Finally, Global Mean Field Amplitude (GMFA) analyses showed reduced late-component amplitudes post-iTBS in responders, consistent with Stafella et al. (2023), and simulations replicated this effect. These results suggest iTBS-induced inhibitory modulation underpins observed spectral and amplitude changes.
Simulations reducing excitatory-to-pyramidal connection strength by 10%, 30%, and 50% mirrored this pattern, with a pronounced decrease in TEP amplitudes, particularly in late components, as seen in a participant with severe MDD (Figure 2C). Group-level comparisons between original and simulated spectra with 50% inhibition revealed reduced low-frequency power, aligning with responders' empirical findings (Figure 2D).
Finally, Global Mean Field Amplitude (GMFA) analyses showed reduced late-component amplitudes post-iTBS in responders, consistent with Stafella et al. (2023), and simulations replicated this effect. These results suggest iTBS-induced inhibitory modulation underpins observed spectral and amplitude changes.
·Figure 2. Low frequency suppression of evoked power is associated with inhibitory modulation.
Conclusions:
Using our novel computational framework for personalized brain stimulation modelling, in this work we have presented new insights into the physiology of clinical iTBS responses. Characterizing both the predictive features and the underlying mechanisms of iTBS depression therapies is important not only as a basic question in systems and cognitive neuroscience, but also as a foundation for clinical applications concerned with changes in excitability and connectivity due to neuropathologies and their associated therapies.
Brain Stimulation:
TMS 2
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Other Methods
Novel Imaging Acquisition Methods:
EEG
Multi-Modal Imaging
Keywords:
Computational Neuroscience
Electroencephaolography (EEG)
Modeling
Psychiatric
Psychiatric Disorders
Transcranial Magnetic Stimulation (TMS)
Treatment
Other - Depression
1|2Indicates the priority used for review
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Provide references using APA citation style.
- Momi, D., Wang, Z., & Griffiths, J. D. (2023). TMS-evoked responses are driven by recurrent large-scale network dynamics. eLife, 12, e83232. https://doi.org/10.7554/eLife.83232
- Momi, D., Wang, Z., Parmigiani, S., Mikulan, E., Bastiaens, S. P., Oveisi, M. P., Kadak, K., Gaglioti, G., Waters, A. C., Hill, S., Pigorini, A., Keller, C. J., & Griffiths, J. D. (2024). Stimulation mapping and whole-brain modeling reveal gradients of excitability and recurrence in cortical networks (p. 2024.02.26.581277). bioRxiv. https://doi.org/10.1101/2024.02.26.581277
- Schaefer, A., Kong, R., Gordon, E. M., Laumann, T. O., Zuo, X.-N., Holmes, A. J., Eickhoff, S. B., & Yeo, B. T. T. (2018). Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI. Cerebral Cortex (New York, N.Y.: 1991), 28(9), 3095–3114. https://doi.org/10.1093/cercor/bhx179
- Strafella, R., Momi, D., Zomorrodi, R., Lissemore, J., Noda, Y., Chen, R., Rajji, T. K., Griffiths, J. D., Vila-Rodriguez, F., Downar, J., Daskalakis, Z. J., Blumberger, D. M., & Voineskos, D. (2023). Identifying Neurophysiological Markers of Intermittent Theta Burst Stimulation in Treatment-Resistant Depression Using Transcranial Magnetic Stimulation–Electroencephalography. Biological Psychiatry, 94(6), 454–465. https://doi.org/10.1016/j.biopsych.2023.04.011