Striatal functional gradients differentiate people with OCD from controls
Poster No:
413
Submission Type:
Abstract Submission
Authors:
Lachlan Webb1, Luke Hearne2, Ye Tian3, Luca Cocchi4
Institutions:
1QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 2QIMR Berghofer Medical Research Institute, Herston, Queensland, 3Department of Psychiatry, The University of Melbourne, Melbourne, Australia, 4Queensland Institute for Medical Research, Brisbane, QLD
First Author:
Co-Author(s):
Introduction:
Preclinical and clinical studies have shown that obsessive-compulsive disorder (OCD) is associated with marked alterations in cortico-striatal brain circuit activity. However, if and how these changes map onto context-specific differences in striatal functional gradient topologies that link to clinical status remain poorly understood. Mapping of striatal functional gradients in humans (Tian, Margulies, Breakspear, & Zalesky, 2020) allows the 'fingerprinting' of cortical connectivity patterns between subcortical units and the estimations of functional gradients defining continuous variations across the topography of the striatum. Information on potential changes in OCD striatal topology is important to advance knowledge on the brain basis of the disorder, delineate reliable biomarkers, and orient the development of targeted therapies like neuromodulation.
Methods:
We calculated spatial striatal gradients linked to functional patterns of cortical connectivity in a sample of 52 people with OCD, aged 18-50 who have had a clinical diagnosis of OCD for at least 12 months, and 45 matched controls (Hearne et al., 2023). Data was collected while individuals underwent a 12-minute eyes-open resting state acquisition, and a threat-safety reversal task lasting 17 min. The functional brain images were preprocessed using a combination of fMRIprep (Esteban et al., 2019) and Nilearn. For the fear reversal task, we employed generalised psychophysiological interaction (PPI) analysis to estimate task-based FC changes specifically related to task conditions (Friston et al., 1997).
Striatal similarity matrices were calculated between sub-cortical voxels based on either the correlation of each voxel to the dimensionally reduced resting-state cortical time series or the PPI coefficient t statistics (Tian, Margulies, Breakspear, & Zalesky, 2020; Borne et al., 2023). After averaging the similarity matrices per group, the graph Laplacian was applied to estimate the first and second non-constant gradient. Permutation tests shuffling the group label were used to ascribe significant group differences in gradient magnitude.
Using our unique longitudinal dataset of 47 people with OCD (Cocchi et al., 2023), we investigated possible associations between changes in individual striatal gradient topology at rest and symptom severity. Individual gradients were calculated at the two timepoints, and the spatial correlation to the control group average gradient was calculated. The proportion of people with OCD that increased or decreased in correlation were compared between those who improved or worsened in Y-BOCS.
Striatal similarity matrices were calculated between sub-cortical voxels based on either the correlation of each voxel to the dimensionally reduced resting-state cortical time series or the PPI coefficient t statistics (Tian, Margulies, Breakspear, & Zalesky, 2020; Borne et al., 2023). After averaging the similarity matrices per group, the graph Laplacian was applied to estimate the first and second non-constant gradient. Permutation tests shuffling the group label were used to ascribe significant group differences in gradient magnitude.
Using our unique longitudinal dataset of 47 people with OCD (Cocchi et al., 2023), we investigated possible associations between changes in individual striatal gradient topology at rest and symptom severity. Individual gradients were calculated at the two timepoints, and the spatial correlation to the control group average gradient was calculated. The proportion of people with OCD that increased or decreased in correlation were compared between those who improved or worsened in Y-BOCS.
Results:
The striatal topology in control and OCD (Fig 1A and B) was similar to that observed in previous work (Tian, Margulies, Breakspear, & Zalesky, 2020), with peak gradient magnitude separating the caudate, NAcc, and putamen (Fig 1C and D). However, results showed opposing group differences in the two main gradient topologies at rest. These differences occurred in putamen and caudate clusters (Fig 1E). Gradients linked to the appraisal of safety also showed a marked group difference in the globus plallidus.
A higher proportion of individuals who had an improvement in symptoms showed increased similarity between individual OCD gradients and the average control gradients across time (Fig 1F) compared to individuals who didn't improve, though this trend was not statistically significant (χ2=2.59, p=0.27).
A higher proportion of individuals who had an improvement in symptoms showed increased similarity between individual OCD gradients and the average control gradients across time (Fig 1F) compared to individuals who didn't improve, though this trend was not statistically significant (χ2=2.59, p=0.27).
Conclusions:
The current results support core deregulations in the functional organisation of the striatum in OCD pathophysiology. Specifically, our findings suggest that OCD-induced changes in the striatal functional topology are context-specific, and that topological normalisation at rest may mirror an improvement in symptom severity. These results encourage studies assessing neural mechanisms driving changes in the dynamic reorganisation of striatal topology in OCD and the development of therapies targeting striatal plasticity.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 2
Other Methods
Keywords:
Obessive Compulsive Disorder
Sub-Cortical
Other - gradient
1|2Indicates the priority used for review
Abstract Information
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information. Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.
Please indicate which methods were used in your research:
For human MRI, what field strength scanner do you use?
Which processing packages did you use for your study?
Provide references using APA citation style.
2. Cocchi, L. et al. (2023). Effects of transcranial magnetic stimulation of the rostromedial prefrontal cortex in obsessive–compulsive disorder: a randomized clinical trial. Nature Mental Health, 1(8), 555-563. doi:10.1038/s44220-023-00094-0
3. Esteban, O. et al. (2019). fMRIPrep: a robust preprocessing pipeline for functional MRI. Nature Methods, 16(1), 111-116. doi:10.1038/s41592-018-0235-4
4. Friston, K. J. et al. (1997). Psychophysiological and modulatory interactions in neuroimaging. Neuroimage, 6(3), 218-229. doi:10.1006/nimg.1997.0291
5. Hearne, L. J. et al. (2023). Revisiting deficits in threat and safety appraisal in obsessive-compulsive disorder. Human Brain Mapping, 44(18), 6418-6428. doi:https://doi.org/10.1002/hbm.26518
6. Naze, S. et al. (2022). Mechanisms of imbalanced frontostriatal functional connectivity in obsessive-compulsive disorder. Brain, 146(4), 1322-1327. doi:10.1093/brain/awac425
7. Tian, Y. et al. (2020). Topographic organization of the human subcortex unveiled with functional connectivity gradients. Nature Neuroscience, 23(11), 1421-1432. doi:10.1038/s41593-020-00711-6