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A potential target for noninvasive neuromodulation of PTSD symptoms derived from focal brain lesions in veterans

Nature Neuroscience (2024)Cite this article

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Abstract

Neuromodulation trials for the treatment of posttraumatic stress disorder (PTSD) have yielded mixed results, and the optimal neuroanatomical target remains unclear. Here we analyzed three datasets to study brain circuitry causally linked to PTSD in military veterans. In veterans with penetrating traumatic brain injury, lesion locations that reduced probability of PTSD were preferentially connected to a circuit including the medial prefrontal cortex, amygdala and anterolateral temporal lobe. In veterans without lesions, PTSD was specifically associated with increased connectivity within this circuit. Reduced functional connectivity within this circuit after transcranial magnetic stimulation correlated with symptom reduction, even though the circuit was not directly targeted. This lesion-based ‘PTSD circuit’ may serve as a target for clinical trials of neuromodulation in veterans with PTSD.

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Fig. 1: Anatomical distribution of lesion locations.
Fig. 2: Lesion network mapping procedure.
Fig. 3: Split-half cross-validation confirmed that the PTSD circuit predicts clinical variance in an independent sample.
Fig. 4: Individualized FC within the PTSD circuit is abnormal in patients with PTSD.
Fig. 5: Comparison with published TMS targets.

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Data availability

The functional connectivity data employed in this study are available online through the Harvard Dataverse at https://doi.org/10.7910/DVN/ILXIKS. Individual patient data cannot be shared publicly because imaging and psychiatric scales may contain identifiable information. Multiple datasets from multiple institutions are reported in this paper; data are available upon reasonable request with an approved data use agreement with the institution at which each dataset was collected. Data sharing will be subject to the policies and procedures of the institution where each dataset was collected. Questions regarding the Vietnam Head Injury Study can be directed to Dr. Jordan Grafman (jgrafman@northwestern.edu). The final PTSD network map is available on NeuroVault (https://neurovault.org/images/886976/) and on our website (http://siddiqi.bwh.harvard.edu/data-code).

Code availability

The pipeline used to prepare the functional connectivity data is available at https://github.com/bchcohenlab/BIDS_to_CBIG_fMRI_Preproc2016. Statistical analyses were performed in MATLAB R2021b. Custom MATLAB scripts for spatial permutation testing are available on our website (https://siddiqi.bwh.harvard.edu/data-code/) and via Zenodo at https://doi.org/10.5281/zenodo.12668537 (ref. 72).

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Acknowledgements

We acknowledge the support of the 393 participants who volunteered for the studies that were analyzed in this paper. We also acknowledge discussions to conceptualize this project in collaboration with K. Johnson, G. Harper and C. Anderson of Neuronetics Inc., which led to an investigator-initiated grant for the present work. In addition, the investigators were funded by the following sources: S.H.S.: the NIH (grant nos. K23MH121657 and R21MH126271), the Brain and Behavior Research Foundation Young Investigator Grant, the Baszucki Brain Research Fund and the Department of Veterans Affairs (grant no. I01CX002293). M.D.F.: funded by the Nancy Lurie Marks Foundation, the Kaye Family Research Endowment, the Baszucki Brain Research Fund and the NIH (grant nos. R01MH113929, R21MH126271, R56AG069086, R01MH115949 and R01AG060987). N.S.P.: grant nos. I21 RX002032, I50 RX002864, U01 MH123427 and P20 GM130452.

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Authors and Affiliations

  1. Center for Brain Circuit Therapeutics, Brigham and Women’s Hospital, Boston, MA, USA

    Shan H. Siddiqi, Stephan T. Palm, Michael A. Ferguson & Michael D. Fox

  2. Department of Psychiatry, Mass General Brigham, Harvard Medical School, Boston, MA, USA

    Shan H. Siddiqi

  3. Center for Neurorestoration and Neurotechnology, Providence VA Healthcare System, Providence, RI, USA

    Noah S. Philip, Amanda R. Arulpragasam & Jennifer Barredo

  4. Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA

    Noah S. Philip, Amanda R. Arulpragasam & Jennifer Barredo

  5. Acacia Mental Health, Sunnyvale, CA, USA

    David M. Carreon

  6. Department of Psychiatry, Duke University School of Medicine, Durham, NC, USA

    Heather Bouchard & Rajendra A. Morey

  7. Department of Psychiatry, Durham VA Medical Center, Durham, NC, USA

    Heather Bouchard & Rajendra A. Morey

  8. Department of Neurology, Mass General Brigham, Harvard Medical School, Boston, MA, USA

    Michael A. Ferguson & Michael D. Fox

  9. Departments of Physical Medicine and Rehabilitation, Northwestern Feinberg School of Medicine, Chicago, IL, USA

    Jordan H. Grafman

  10. Department of Neurology, Northwestern Feinberg School of Medicine, Chicago, IL, USA

    Jordan H. Grafman

  11. Department of Psychiatry, Northwestern Feinberg School of Medicine, Chicago, IL, USA

    Jordan H. Grafman

  12. Shirley Ryan AbilityLab, Chicago, IL, USA

    Jordan H. Grafman

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Contributions

S.H.S., J.H.G. and M.D.F. designed the study. S.H.S. and S.T.P. were responsible for analysis and code development. J.H.G., R.A.M., N.S.P. and D.M.C. collected data. S.H.S., H.B. and J.B. were responsible for image processing. A.R.A. and M.A.F. were responsible for quality appraisal. S.H.S. and M.D.F. prepared the paper, with input from all authors.

Corresponding author

Correspondence to Shan H. Siddiqi.

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Competing interests

There are no personal financial conflicts of interest related to the present results. S.H.S. is an owner of intellectual property involving the use of individualized resting-state network mapping to target TMS, which was filed in 2016, has yielded no royalties and does not cover the present work. S.H.S. is also a scientific consultant for Magnus Medical, received investigator-initiated research funding from Neuronetics (2019) and Brainsway (2022), received speaking fees from Brainsway (2021) and Otsuka (for PsychU.org, 2021), and is a shareholder in Brainsway (publicly traded) and Magnus Medical (not publicly traded). M.D.F. is a scientific consultant for Magnus Medical. M.D.F. also owns independent intellectual property involving the use of functional connectivity to target TMS for depression, which was filed in 2013, has yielded no royalties and does not cover the present work. N.S.P. received clinical trial support (through VA contracts) from Wave Neuroscience and Neurolief, serves on the scientific advisory board for Pulvinar Neuro and serves as a consultant for Motif Neurotech. The other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Full PTSD circuit.

(a) The peak location in the PTSD circuit was the tapetum, which connects the two hippocampi to each other. Depicted here is the peak coordinate (−12, −38, 20) (pFWE=0.035 with Westfall-Young correction for multiple comparisons) at the magenta crosshairs, a peak voxel cluster in green (pFWE<0.05, detection p < 0.001, cluster size=888 mm3), overlaid on a map with uncorrected p < 0.05 which depicts the extent of the cluster into both medial temporal lobes. (b) We identified regions that were positively correlated (yellow) and negatively correlated (blue) to lesion locations that reduce probability of PTSD. To investigate whether the positive correlations (the “PTSD+ circuit”) or the negative correlations (the “PTSD- circuit”) were more relevant, we used both to predict PTSD diagnosis in a split-half analysis. PTSD risk was independently predicted by lesion overlap with the PTSD+ circuit (Pearson r = 0.18, p = 0.01), but not the PTSD- circuit (Pearson r = 0.02, p = 0.8). Permutation testing confirmed that the PTSD+ circuit was a significantly stronger predictor than the PTSD- circuit (mean difference Pearson r = 0.14, p = 0.02). Similar results were observed when excluding patients with subthreshold PTSD (Pearson r = 0.21 vs r = 0.03, p = 0.01).

Extended Data Fig. 2 PTSD circuit was independent of relevant covariates.

Nearly-identical circuits were generated when the primary analysis was repeated after (a) excluding subthreshold PTSD, (b) using a continuous measure of PTSD, (c) controlling for alcoholism risk, (d) controlling for MMSE, and (e) not controlling for BDI.

Extended Data Fig. 3 TMS-induced change in the PTSD circuit correlated with change in PTSD symptoms.

(a) PTSD was negatively associated with resting-state functional connectivity within our PTSD circuit, after controlling for TBI and depression. (b) The right DLPFC stimulation region showed marked inter-individual variability in connectivity to the PTSD circuit. 35% of participants showed positive connectivity (40% in the active group, 30% in the sham group). Thus, we hypothesized that there may also be variability in treatment-induced change. (c) In the active arm of a clinical trial, treatment-induced change in connectivity was negatively correlated with treatment-induced change in PTSD symptoms. In the sham arm, there was no relationship between PTSD improvement and connectivity change. There was a significant active-sham interaction on a linear mixed model (t = 3.32, p < 0.005). Note that data were rank-transformed in this dataset due to high influence of outliers in datasets with small sample sizes, but similar results were observed when not using a rank transform.

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Supplementary Tables 1 and 2, Figs. 1–3 and Box 1.

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Siddiqi, S.H., Philip, N.S., Palm, S.T. et al. A potential target for noninvasive neuromodulation of PTSD symptoms derived from focal brain lesions in veterans. Nat Neurosci (2024). https://doi.org/10.1038/s41593-024-01772-7

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