Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Differential impact of cerebral small vessel disease on thalamic regulation of anxiety: insights from 7T MRI

Molecular Psychiatry volume 30, pages 4142–4150 (2025)Cite this article

Subjects

Abstract

Little is known about how thalamic vascular patterns interact with small vessel diseases (SVDs) to influence affective symptoms. Here we collected 7-Telsa magnetic resonance imaging (MRI) data from 84 individuals with SVD and analyzed the influences of thalamic vascular pattern on affective symptoms, aiming to elucidate the underlying mechanisms driven by brain structure and function in the context of SVD. Subjects with a combined arterial supply by tuberothalamic and paramedian arteries to the right thalamus exhibited a lower Hamilton Anxiety scale (HAMA) score. When grouped by SVD burden, the same correlation remained in subjects with low SVD burden, whereas no difference was observed in the high SVD burden group. Interestingly, interaction effects of SVD and thalamic vascular pattern were also found affecting thalamic volume and resting-state brain activity in ventromedial prefrontal cortex (vmPFC). With moderated mediation analysis, right thalamic vascular pattern was indicated to affect anxiety through both direct (vascular pattern → HAMA score) and indirect (vascular pattern → thalamic volume → HAMA score) pathways. But high SVD burden interrupted the effects of right thalamic vascular pattern on HAMA score and thalamic volume. The finding that subjects with a combined arterial supply to the right thalamus exhibited a lower level of anxiety may suggest a novel vascular resilience for regulating anxiety. However, this vascular compensation mechanism was found to be impaired by elevated SVD burden and the disrupted inhibitory vmPFC activity caused by impaired thalamus. The findings of the present study provide a new underlying mechanism for affective disorders with SVD involved.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Definition of thalamic vascular pattern.
Fig. 2: Effects of right thalamic vascular pattern and SVD burden on affective symptoms.
Fig. 3: Effects of right thalamic vascular pattern and SVD burden on brain function and structure.
Fig. 4: Final moderated mediation model.

Similar content being viewed by others

Data availability

The data that support the findings of this study are available from the cor- responding authors upon reasonable request.

References

  1. Pessoa L. A network model of the emotional brain. Trends Cogn Sci. 2017;21:357–71.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Malezieux M, Klein AS, Gogolla N. Neural circuits for emotion. Annu Rev Neurosci. 2023;46:211–31.

    Article  CAS  PubMed  Google Scholar 

  3. Scharf AC, Gronewold J, Eilers A, Todica O, Moenninghoff C, Doeppner TR, et al. Depression and anxiety in acute ischemic stroke involving the anterior but not paramedian or inferolateral thalamus. Front Psychol. 2023;14:1218526.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Liebermann D, Ostendorf F, Kopp UA, Kraft A, Bohner G, Nabavi DG, et al. Subjective cognitive-affective status following thalamic stroke. J Neurol. 2013;260:386–96.

    Article  PubMed  Google Scholar 

  5. Li S, Kumar Y, Gupta N, Abdelbaki A, Sahwney H, Kumar A, et al. Clinical and neuroimaging findings in thalamic territory infarctions: a review. J Neuroimaging. 2018;28:343–9.

    Article  PubMed  Google Scholar 

  6. Schmahmann JD. Vascular syndromes of the thalamus. Stroke. 2003;34:2264–78.

    Article  PubMed  Google Scholar 

  7. Cooper CM, Chin Fatt CR, Liu P, Grannemann BD, Carmody T, Almeida JRC, et al. Discovery and replication of cerebral blood flow differences in major depressive disorder. Mol Psychiatry. 2020;25:1500–10.

    Article  PubMed  Google Scholar 

  8. Tang WK, Chen YK, Lu JY, Mok VC, Xiang YT, Ungvari GS, et al. Microbleeds and post-stroke emotional lability. J Neurol Neurosurg Psychiatry. 2009;80:1082–6.

    Article  CAS  PubMed  Google Scholar 

  9. Bordes S, Werner C, Mathkour M, McCormack E, Iwanaga J, Loukas M, et al. Arterial supply of the thalamus: a comprehensive review. World Neurosurg. 2020;137:310–8.

    Article  PubMed  Google Scholar 

  10. Lin E, Kamel H, Gupta A, RoyChoudhury A, Girgis P, Glodzik L. Incomplete circle of Willis variants and stroke outcome. Eur J Radiol. 2022;153:110383.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Clancy U, Gilmartin D, Jochems ACC, Knox L, Doubal FN, Wardlaw JM. Neuropsychiatric symptoms associated with cerebral small vessel disease: a systematic review and meta-analysis. Lancet Psychiatry. 2021;8:225–36.

    Article  PubMed  Google Scholar 

  12. Li X, Qin RR, Chen J, Jiang HF, Tang P, Wang YJ, et al. Neuropsychiatric symptoms and altered sleep quality in cerebral small vessel disease. Front Psychiatry. 2022;13:882922.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Clancy U, Ramirez J, Chappell FM, Doubal FN, Wardlaw JM, Black SE. Neuropsychiatric symptoms as a sign of small vessel disease progression in cognitive impairment. Cereb Circ Cogn Behav. 2022;3:100041.

    PubMed  PubMed Central  Google Scholar 

  14. Direk N, Perez HS, Akoudad S, Verhaaren BF, Niessen WJ, Hofman A, et al. Markers of cerebral small vessel disease and severity of depression in the general population. Psychiatry Res Neuroimaging. 2016;253:1–6.

    Article  PubMed  Google Scholar 

  15. Spalletta G, Iorio M, Vecchio D, Piras F, Ciullo V, Banaj N, et al. Subclinical cognitive and neuropsychiatric correlates and hippocampal volume features of brain white matter hyperintensity in healthy people. J Pers Med. 2020;10:172.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Hannawi Y, Vaidya D, Yanek LR, Johansen MC, Kral BG, Becker LC, et al. Association of vascular properties with the brain white matter hyperintensity in middle-aged population. J Am Heart Assoc. 2022;11:e024606.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Doubal FN, MacLullich AM, Ferguson KJ, Dennis MS, Wardlaw JM. Enlarged perivascular spaces on MRI are a feature of cerebral small vessel disease. Stroke. 2010;41:450–4.

    Article  PubMed  Google Scholar 

  18. Greenberg SM, Vernooij MW, Cordonnier C, Viswanathan A, Al-Shahi Salman R, Warach S, et al. Cerebral microbleeds: a guide to detection and interpretation. Lancet Neurol. 2009;8:165–74.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Vermeer SE, Longstreth WT Jr., Koudstaal PJ. Silent brain infarcts: a systematic review. Lancet Neurol. 2007;6:611–9.

    Article  PubMed  Google Scholar 

  20. Staals J, Makin SD, Doubal FN, Dennis MS, Wardlaw JM. Stroke subtype, vascular risk factors, and total MRI brain small-vessel disease burden. Neurology. 2014;83:1228–34.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Cao QL, Sun Y, Hu H, Wang ZT, Tan L, Yu JT, et al. Association of cerebral small vessel disease burden with neuropsychiatric symptoms in non-demented elderly: a longitudinal study. J Alzheimers Dis. 2022;89:583–92.

    Article  PubMed  Google Scholar 

  22. Wang Y, Yang Y, Wang T, Nie S, Yin H, Liu J. et al. Correlation between white matter hyperintensities related gray matter volume and cognition in cerebral small vessel disease. J Stroke Cerebrovasc Dis. 2020;29:105275.

    Article  PubMed  Google Scholar 

  23. Guo C, Wang B, Huo Y, Shan L, Qiao T, Yang Z, et al. The effects of P2 segment of posterior cerebral artery to thalamus blood supply pattern on gait in cerebral small vessel disease: A 7 T MRI based study. Neurobiol Dis. 2024;190:106372.

    Article  CAS  PubMed  Google Scholar 

  24. Kato H, Yoshikawa T, Oku N, Imaizumi M, Takasawa M, Kimura Y, et al. Statistical parametric analysis of cerebral blood flow in vascular dementia with small-vessel disease using Tc-HMPAO SPECT. Cerebrovasc Dis. 2008;26:556–62.

    Article  PubMed  Google Scholar 

  25. Ter Telgte A, van Leijsen EMC, Wiegertjes K, Klijn CJM, Tuladhar AM, de Leeuw FE. Cerebral small vessel disease: from a focal to a global perspective. Nat Rev Neurol. 2018;14:387–98.

    Article  PubMed  Google Scholar 

  26. Zhang X, Suo X, Yang X, Lai H, Pan N, He M, et al. Structural and functional deficits and couplings in the cortico-striato-thalamo-cerebellar circuitry in social anxiety disorder. Transl Psychiatry. 2022;12:26.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Zhang Y, Zhang Y, Ai H, Van Dam NT, Qian L, Hou G, et al. Microstructural deficits of the thalamus in major depressive disorder. Brain Commun. 2022;4:fcac236.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Xu J, Chen H, Hu Z, Ke Z, Qin R, Chen Y, et al. Characteristic patterns of functional connectivity-mediated cerebral small vessel disease-related cognitive impairment and depression. Cereb Cortex. 2024;34:bhad468.

    Article  PubMed  Google Scholar 

  29. Datta R, Bacchus MK, Kumar D, Elliott MA, Rao A, Dolui S, et al. Fast automatic segmentation of thalamic nuclei from MP2RAGE acquisition at 7 Tesla. Magn Reson Med. 2021;85:2781–90.

    Article  CAS  PubMed  Google Scholar 

  30. Jerman T, Pernus F, Likar B, Spiclin Z. Enhancement of vascular structures in 3D and 2D angiographic images. IEEE Trans Med Imaging. 2016;35:2107–18.

    Article  PubMed  Google Scholar 

  31. Chao-Gan Y, Yu-Feng Z. DPARSF: A MATLAB toolbox for “Pipeline” data analysis of resting-state fMRI. Front Syst Neurosci. 2010;4:13.

    PubMed  PubMed Central  Google Scholar 

  32. Hayes AF PROCESS: a versatile computational tool for mediation, moderation, and conditional process analysis. 2012.

  33. Zhang X, Cheng B, Yang X, Suo X, Pan N, Chen T, et al. Emotional intelligence mediates the protective role of the orbitofrontal cortex spontaneous activity measured by fALFF against depressive and anxious symptoms in late adolescence. Eur Child Adolesc Psychiatry. 2023;32:1957–67.

    Article  PubMed  Google Scholar 

  34. Xue S, Kong F, Song Y, Liu J. Neural correlates of social interaction anxiety and their relation to emotional intelligence: a resting-state fMRI study. Neurosci Lett. 2024;818:137475.

    Article  CAS  PubMed  Google Scholar 

  35. Adrian-Ventura J, Fabregat-Nabas J, Costumero V, Avila C. Underlying differences in resting-state activity metrics related to sensitivity to punishment. Behav Brain Res. 2023;437:114152.

    Article  PubMed  Google Scholar 

  36. Etkin A, Wager TD. Functional neuroimaging of anxiety: a meta-analysis of emotional processing in PTSD, social anxiety disorder, and specific phobia. Am J Psychiatry. 2007;164:1476–88.

    Article  PubMed  PubMed Central  Google Scholar 

  37. van Sloten TT, Sigurdsson S, van Buchem MA, Phillips CL, Jonsson PV, Ding J, et al. Cerebral small vessel disease and association with higher incidence of depressive symptoms in a general elderly population: The AGES-Reykjavik Study. Am J Psychiatry. 2015;172:570–8.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Fang Y, Qin T, Liu W, Ran L, Yang Y, Huang H, et al. Cerebral small-vessel disease and risk of incidence of depression: a meta-analysis of longitudinal cohort studies. J Am Heart Assoc. 2020;9:e016512.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Ozel F, Hilal S, de Feijter M, van der Velpen I, Direk N, Ikram MA, et al. Associations of neuroimaging markers with depressive symptoms over time in middle-aged and elderly persons. Psychol Med. 2023;53:4355–63.

    Article  PubMed  Google Scholar 

  40. Zhang Y, Zhu C, Chen H, Duan X, Lu F, Li M, et al. Frequency-dependent alterations in the amplitude of low-frequency fluctuations in social anxiety disorder. J Affect Disord. 2015;174:329–35.

    Article  PubMed  Google Scholar 

  41. Wang W, Hou J, Qian S, Liu K, Li B, Li M, et al. Aberrant regional neural fluctuations and functional connectivity in generalized anxiety disorder revealed by resting-state functional magnetic resonance imaging. Neurosci Lett. 2016;624:78–84.

    Article  CAS  PubMed  Google Scholar 

  42. Dymond S, Dunsmoor JE, Vervliet B, Roche B, Hermans D. Fear generalization in humans: systematic review and implications for anxiety disorder research. Behav Ther. 2015;46:561–82.

    Article  PubMed  Google Scholar 

  43. van Meurs B, Wiggert N, Wicker I, Lissek S. Maladaptive behavioral consequences of conditioned fear-generalization: a pronounced, yet sparsely studied, feature of anxiety pathology. Behav Res Ther. 2014;57:29–37.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Lissek S, Kaczkurkin AN, Rabin S, Geraci M, Pine DS, Grillon C. Generalized anxiety disorder is associated with overgeneralization of classically conditioned fear. Biol Psychiatry. 2014;75:909–15.

    Article  PubMed  Google Scholar 

  45. El-Bar N, Laufer O, Yoran-Hegesh R, Paz R. Over-generalization in youth with anxiety disorders. Soc Neurosci. 2017;12:76–85.

    Article  PubMed  Google Scholar 

  46. Dunsmoor JE, Paz R. Fear generalization and anxiety: behavioral and neural mechanisms. Biol Psychiatry. 2015;78:336–43.

    Article  PubMed  Google Scholar 

  47. Kenwood MM, Kalin NH, Barbas H. The prefrontal cortex, pathological anxiety, and anxiety disorders. Neuropsychopharmacology. 2022;47:260–75.

    Article  PubMed  Google Scholar 

  48. Li Y, Lopez-Huerta VG, Adiconis X, Levandowski K, Choi S, Simmons SK, et al. Distinct subnetworks of the thalamic reticular nucleus. Nature. 2020;583:819–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Li H, Jacob MA, Cai M, Duering M, Chamberland M, Norris DG, et al. Regional cortical thinning, demyelination and iron loss in cerebral small vessel disease. Brain. 2023;146:4659–73.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Liu R, Yue Y, Hou Z, Yuan Y, Wang Q. Risk factors associated with cognitions for late-onset depression based on anterior and posterior default mode sub-networks. J Affect Disord. 2018;235:544–50.

    Article  PubMed  Google Scholar 

  51. Wardlaw JM, Smith C, Dichgans M. Small vessel disease: mechanisms and clinical implications. Lancet Neurol. 2019;18:684–96.

    Article  PubMed  Google Scholar 

  52. Liu H, Hao Z, Qiu S, Wang Q, Zhan L, Huang L, et al. Grey matter structural alterations in anxiety disorders: a voxel-based meta-analysis. Brain Imaging Behav. 2024;18:456–74.

    Article  PubMed  Google Scholar 

  53. Moon CM, Kim GW, Jeong GW. Whole-brain gray matter volume abnormalities in patients with generalized anxiety disorder: voxel-based morphometry. Neuroreport. 2014;25:184–9.

    Article  CAS  PubMed  Google Scholar 

  54. Gainotti G. Emotions and the right hemisphere: can new data clarify old models? Neuroscientist. 2019;25:258–70.

    Article  PubMed  Google Scholar 

  55. Gunturkun O, Strockens F, Ocklenburg S. Brain lateralization: a comparative perspective. Physiol Rev. 2020;100:1019–63.

    Article  PubMed  Google Scholar 

  56. Sato W, Aoki S. Right hemispheric dominance in processing of unconscious negative emotion. Brain Cogn. 2006;62:261–6.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82271956, No. 62331021), Shanghai Municipal Science and Technology Major Project (No. 2018SHZDZX01), Shanghai Municipal Science and Technology Explorer Project (No. 23TS1400500).

Author information

Author notes

  1. These authors contributed equally: Bei Wang, Cen Guo.

Authors and Affiliations

  1. Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China

    Bei Wang & He Wang

  2. Department of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China

    Cen Guo, Yajing Huo & Yan Han

  3. MR Research Collaboration Team, Siemens Healthineers Ltd., Shanghai, China

    Ying-Hua Chu

  4. Department of Radiology, Shanghai Fourth People’s Hospital Affiliated to Tongji University School of Medicine, Shanghai, China

    Boyu Zhang & He Wang

  5. Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Guanshu Liu

  6. F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA

    Guanshu Liu

  7. Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China

    He Wang

Authors
  1. Bei Wang
    View author publications

    Search author on:PubMed Google Scholar

  2. Cen Guo
    View author publications

    Search author on:PubMed Google Scholar

  3. Ying-Hua Chu
    View author publications

    Search author on:PubMed Google Scholar

  4. Yajing Huo
    View author publications

    Search author on:PubMed Google Scholar

  5. Boyu Zhang
    View author publications

    Search author on:PubMed Google Scholar

  6. Guanshu Liu
    View author publications

    Search author on:PubMed Google Scholar

  7. Yan Han
    View author publications

    Search author on:PubMed Google Scholar

  8. He Wang
    View author publications

    Search author on:PubMed Google Scholar

Contributions

BW and CG contributed to the study concept and design, analysis and interpretation of data, statistical analysis, and drafting/revising the manuscript for content. YC, YH, and BZ took part in the acquisition and interpretation of data. GL revised the manuscript. HW and YH participated in study concept and design, data acquisition and interpretation. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Yan Han or He Wang.

Ethics declarations

Ethics approval and consent

This study was approved by the Ethics Committee of Yueyang Hospital (Approval no. 2020-060), and all methods were performed in accordance with the relevant guidelines and regulations. Written informed consent was obtained from all participants.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, B., Guo, C., Chu, YH. et al. Differential impact of cerebral small vessel disease on thalamic regulation of anxiety: insights from 7T MRI. Mol Psychiatry 30, 4142–4150 (2025). https://doi.org/10.1038/s41380-025-02994-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41380-025-02994-2

This article is cited by

Search

Advanced search

Quick links