Depression is marked by differences in structural covariance between deep-brain nuclei and sensorimotor cortex
Background: Depression impacts nearly 3% of the global adult population. Symptomatology is likely related to regions encompassing frontoparietal, somatosensory, and salience networks. Questions regarding deep brain nuclei (DBN), including the substantia nigra (STN), subthalamic nucleus (STN), and re...
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| Language: | English |
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Elsevier
2025-04-01
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| Series: | NeuroImage |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811925001296 |
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| author | Siraj Lyons Isak Beck Brendan E. Depue |
| author_facet | Siraj Lyons Isak Beck Brendan E. Depue |
| author_sort | Siraj Lyons |
| collection | DOAJ |
| description | Background: Depression impacts nearly 3% of the global adult population. Symptomatology is likely related to regions encompassing frontoparietal, somatosensory, and salience networks. Questions regarding deep brain nuclei (DBN), including the substantia nigra (STN), subthalamic nucleus (STN), and red nucleus (RN) remain unanswered. Methods: Using an existing structural neuroimaging dataset including 86 individuals (Baranger et al., 2021; nDEP = 39), frequentist and Bayesian logistic regressions assessed whether DBN volumes predict diagnosis, then structural covariance analyses in FreeSurfer tested diagnostic differences in deep brain volume and cortical morphometry covariance. Exploratory correlations tested relationships between implicated cortical regions and Hamilton Depression Rating Scale (HAM-D) scores. Results: Group differences emerged in deep brain/cortical covariance. Right RN volume covaried with left parietal operculum volume and central sulcus thickness, while left RN and right STN volumes covaried with right occipital pole volume. Positive relationships were observed within the unaffected group and negative relationships among those with depression. These cortical areas did not correlate with HAM-D scores. Simple DBN volumes did not predict diagnostic group. Conclusion: Structural codependence between DBN and cortical regions may be important in depression, potentially for sensorimotor features. Future work should focus on causal mechanisms of DBN involvement with sensory integration. |
| format | Article |
| id | doaj-art-d6638bfb92ad4313a362b05dccaaa2b1 |
| institution | OA Journals |
| issn | 1095-9572 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj-art-d6638bfb92ad4313a362b05dccaaa2b12025-08-20T02:25:45ZengElsevierNeuroImage1095-95722025-04-0131012112710.1016/j.neuroimage.2025.121127Depression is marked by differences in structural covariance between deep-brain nuclei and sensorimotor cortexSiraj Lyons0Isak Beck1Brendan E. Depue2Department of Psychological and Brain Sciences, University of Louisville, Louisville, KY, United States; Corresponding author.Human Systems Engineering, Arizona State University, Mesa, AZ, United StatesDepartment of Psychological and Brain Sciences, University of Louisville, Louisville, KY, United States; Department of Anatomical Sciences and Neurobiology, University of Louisville, Louisville, KY, United StatesBackground: Depression impacts nearly 3% of the global adult population. Symptomatology is likely related to regions encompassing frontoparietal, somatosensory, and salience networks. Questions regarding deep brain nuclei (DBN), including the substantia nigra (STN), subthalamic nucleus (STN), and red nucleus (RN) remain unanswered. Methods: Using an existing structural neuroimaging dataset including 86 individuals (Baranger et al., 2021; nDEP = 39), frequentist and Bayesian logistic regressions assessed whether DBN volumes predict diagnosis, then structural covariance analyses in FreeSurfer tested diagnostic differences in deep brain volume and cortical morphometry covariance. Exploratory correlations tested relationships between implicated cortical regions and Hamilton Depression Rating Scale (HAM-D) scores. Results: Group differences emerged in deep brain/cortical covariance. Right RN volume covaried with left parietal operculum volume and central sulcus thickness, while left RN and right STN volumes covaried with right occipital pole volume. Positive relationships were observed within the unaffected group and negative relationships among those with depression. These cortical areas did not correlate with HAM-D scores. Simple DBN volumes did not predict diagnostic group. Conclusion: Structural codependence between DBN and cortical regions may be important in depression, potentially for sensorimotor features. Future work should focus on causal mechanisms of DBN involvement with sensory integration.http://www.sciencedirect.com/science/article/pii/S1053811925001296Red nucleusSubthalamic nucleusSubstantia nigraDeep brain nucleiDepressionStructural morphometry |
| spellingShingle | Siraj Lyons Isak Beck Brendan E. Depue Depression is marked by differences in structural covariance between deep-brain nuclei and sensorimotor cortex NeuroImage Red nucleus Subthalamic nucleus Substantia nigra Deep brain nuclei Depression Structural morphometry |
| title | Depression is marked by differences in structural covariance between deep-brain nuclei and sensorimotor cortex |
| title_full | Depression is marked by differences in structural covariance between deep-brain nuclei and sensorimotor cortex |
| title_fullStr | Depression is marked by differences in structural covariance between deep-brain nuclei and sensorimotor cortex |
| title_full_unstemmed | Depression is marked by differences in structural covariance between deep-brain nuclei and sensorimotor cortex |
| title_short | Depression is marked by differences in structural covariance between deep-brain nuclei and sensorimotor cortex |
| title_sort | depression is marked by differences in structural covariance between deep brain nuclei and sensorimotor cortex |
| topic | Red nucleus Subthalamic nucleus Substantia nigra Deep brain nuclei Depression Structural morphometry |
| url | http://www.sciencedirect.com/science/article/pii/S1053811925001296 |
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