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.

  • Research Highlight
  • Published:

The new normal: neural network adaptations in late-life depression

Neuropsychopharmacology (2025)Cite this article

Subjects

Access through your institution
Buy or subscribe

Interestingly, in the study by Gerlach et al., connectivity patterns linked to relapse risk in patients with late-life depression (LLD) were more similar to those in healthy individuals than those in stable remitters. Such contrarian insights offer great opportunities for disruption, suggesting that stable remission may represent a shift to a distinct, reorganized neural configuration (a “new normal”) rather than a return to a healthy state.

Gerlach et al. compared baseline intrinsic brain network connectivity patterns predictive of relapse in 47 stable remitters and 25 relapsing with 39 healthy controls [1]. They analyzed resting-state functional MRI (fMRI) connectivity across 28 network connectivity patterns in seven networks with three parcellation schemes using the “Higher Criticism” method to identify sparse signals. Compared with healthy controls, participants with LLD exhibited lower connectivity within the somatomotor (SMN), salience (SN), and visual networks. Patients with LLD also showed greater connectivity of visual network and SMN with default mode (DMN) and limbic networks; executive control (EC) to the DMN; and dorsal attention to the limbic network. Surprisingly, lower DMN-SN, DMN-SMN, and ECN-SMN connectivity was associated with a longer time to relapse in the survival analysis. Conversely, greater within-SMN connectivity was associated with shorter time to relapse.

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

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

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

Fig. 1: Pathophysiological mechanisms and network states in late-life depression.

References

  1. Gerlach A, Karim H, Kolobaric A, Boyd B, Kahru K, Krafty R, et al. Network homeostasis: functional brain network alterations and relapse in remitted late-life depression. Neuropsychopharmacology. 2025. https://doi.org/10.1038/s41386-025-02138-8.

  2. Alexopoulos GS. Mechanisms and treatment of late-life depression. Transl Psychiatry. 2019;9:188.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Haroon E, Miller AH, Sanacora G. Inflammation, glutamate, and glia: a trio of trouble in mood disorders. Neuropsychopharmacology. 2017;42:193–215.

    Article  CAS  PubMed  Google Scholar 

  4. Chen X, Beltran DJ, Tsygankova VD, Woolwine BJ, Patel T, Baer W, et al. Kynurenines increase MRS metabolites in basal ganglia and decrease resting-state connectivity in frontostriatal reward circuitry in depression. Transl Psychiatry. 2021;11:456.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Haroon E, Miller AH. Inflammation effects on brain glutamate in depression: mechanistic considerations and treatment implications. Curr Top Behav Neurosci. 2017;31:173–98.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The figures were created in Biorender, Inc with permission.

Funding

R01MH107033 (EH), R01MH132059 (EH), R01MH128872 (AHM), R01MH087604 (AHM), and R01MH112076 (EH/AHM).

Author information

Authors and Affiliations

  1. Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, 101 Woodruff Circle, 6th Floor, Rm 6003, Atlanta, GA, 30322, USA

    Ebrahim Haroon & Andrew H. Miller

  2. Emory Behavioral Immunology Program, Emory University School of Medicine, 101 Woodruff Circle, 4th Floor, Atlanta, GA, 30322, USA

    Ebrahim Haroon & Andrew H. Miller

Authors
  1. Ebrahim Haroon
    View author publications

    Search author on:PubMed Google Scholar

  2. Andrew H. Miller
    View author publications

    Search author on:PubMed Google Scholar

Contributions

EH: conceptualization, design and writing AHM: conceptualization, design and writing

Corresponding author

Correspondence to Ebrahim Haroon.

Ethics declarations

Competing interests

EH has no competing interests or conflicts. AHM is a paid consultant for Cerevel Therapeutics, Freedom Biosciences, Sirtsei Pharmaceuticals, Inc., but does not have any competing interests or conflicts.

Additional information

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Haroon, E., Miller, A.H. The new normal: neural network adaptations in late-life depression. Neuropsychopharmacol. (2025). https://doi.org/10.1038/s41386-025-02145-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41386-025-02145-9

Search

Advanced search

Quick links