Agudelo, C., Aizenstein, H. J., Karp, J. F., & Reynolds, C. F. 3rd (2015). Applications of magnetic resonance imaging for treatment-resistant late-life depression. Dialogues Clin Neurosci, 17 (2), 151–169. https://doi.org/10.31887/DCNS.2015.17.2/cagudelo

Article  PubMed  PubMed Central  Google Scholar 

Aizenstein, H. J., Baskys, A., Boldrini, M., Butters, M. A., Diniz, B. S., Jaiswal, M. K., & Tene, O. (2016). Vascular depression consensus report - a critical update. Bmc Medicine, 14 (1), 161. https://doi.org/10.1186/s12916-016-0720-5

Article  PubMed  PubMed Central  Google Scholar 

Bär, K. J., Köhler, S., Cruz, F., Schumann, A., Zepf, F. D., & Wagner, G. (2020). Functional consequences of acute tryptophan depletion on raphe nuclei connectivity and network organization in healthy women. Neuroimage, 207, 116362. https://doi.org/10.1016/j.neuroimage.2019.116362

Article  CAS  PubMed  Google Scholar 

Blondel, V. D., Guillaume, J. L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008 (10), P10008. https://doi.org/10.1088/1742-5468/2008/10/P10008

Article  Google Scholar 

Brodaty, H., Luscombe, G., Parker, G., Wilhelm, K., Hickie, I., Austin, M. P., & Mitchell, P. (2001). Early and late onset depression in old age: Different aetiologies, same phenomenology. Journal of Affective Disorders, 66 (2–3), 225–236. https://doi.org/10.1016/s0165-0327(00)00317-7

Article  CAS  PubMed  Google Scholar 

Colon-Perez, L. M., Turner, S. M., Lubke, K. N., Pompilus, M., Febo, M., & Burke, S. N. (2019). Multiscale Imaging reveals aberrant functional Connectome Organization and elevated dorsal Striatal Arc expression in Advanced Age. eNeuro, 6 (6). https://doi.org/10.1523/eneuro.0047-19.2019

Crossley, N. A., Fox, P. T., & Bullmore, E. T. (2016). Meta-connectomics: Human brain network and connectivity meta-analyses. Psychological Medicine, 46 (5), 897–907. https://doi.org/10.1017/s0033291715002895

Article  CAS  PubMed  PubMed Central  Google Scholar 

Diniz, B. S., Butters, M. A., Albert, S. M., Dew, M. A., & Reynolds, C. F. 3rd (2013). Late-life depression and risk of vascular Dementia and Alzheimer’s Disease: Systematic review and meta-analysis of community-based cohort studies. British Journal of Psychiatry, 202 (5), 329–335. https://doi.org/10.1192/bjp.bp.112.118307

Article  Google Scholar 

Disabato, B. M., & Sheline, Y. I. (2012). Biological basis of late life depression. Curr Psychiatry Rep, 14 (4), 273–279. https://doi.org/10.1007/s11920-012-0279-6

Article  PubMed  PubMed Central  Google Scholar 

Figueroa, C. A., Cabral, J., Mocking, R. J. T., Rapuano, K. M., van Hartevelt, T. J., Deco, G., & Ruhé, H. G. (2019). Altered ability to access a clinically relevant control network in patients remitted from major depressive disorder. Human Brain Mapping, 40 (9), 2771–2786. https://doi.org/10.1002/hbm.24559

Article  PubMed  PubMed Central  Google Scholar 

Geerlings, M. I., & Gerritsen, L. (2017). Late-Life Depression, hippocampal volumes, and hypothalamic-pituitary-adrenal Axis Regulation: A systematic review and Meta-analysis. Biological Psychiatry, 82 (5), 339–350. https://doi.org/10.1016/j.biopsych.2016.12.032

Article  CAS  PubMed  Google Scholar 

Hajek, A., Brettschneider, C., Ernst, A., Lange, C., Wiese, B., Prokein, J., & König, H. H. (2015). Complex coevolution of depression and health-related quality of life in old age. Quality of Life Research, 24 (11), 2713–2722. https://doi.org/10.1007/s11136-015-1005-8

Article  PubMed  Google Scholar 

Heser, K., Bleckwenn, M., Wiese, B., Mamone, S., Riedel-Heller, S. G., Stein, J., & Wagner, M. (2016). Late-life depressive symptoms and lifetime history of Major Depression: Cognitive deficits are largely due to Incipient Dementia rather than Depression. Journal of Alzheimer’s Disease, 54 (1), 185–199. https://doi.org/10.3233/jad-160209

Article  PubMed  Google Scholar 

Janssen, J., Hulshoff Pol, H. E., de Leeuw, F. E., Schnack, H. G., Lampe, I. K., Kok, R. M., & Heeren, T. J. (2007). Hippocampal volume and subcortical white matter lesions in late life depression: Comparison of early and late onset depression. Journal of Neurology, Neurosurgery and Psychiatry, 78 (6), 638–640. https://doi.org/10.1136/jnnp.2006.098087

Article  PubMed  PubMed Central  Google Scholar 

Leicht, E. A., & Newman, M. E. (2008). Community structure in directed networks. Physical Review Letters, 100 (11), 118703. https://doi.org/10.1103/PhysRevLett.100.118703

Article  CAS  PubMed  Google Scholar 

LeMoult, J., & Gotlib, I. H. (2019). Depression: A cognitive perspective. Clinical Psychology Review, 69, 51–66. https://doi.org/10.1016/j.cpr.2018.06.008

Article  PubMed  Google Scholar 

Li, W., Ward, D., Liu, B., Chen, X., Jones, G., Antuono, J. L., & Goveas, P. G., J. S (2015). Disrupted small world topology and modular organisation of functional networks in late-life depression with and without amnestic mild cognitive impairment. Journal of Neurology, Neurosurgery and Psychiatry, 86 (10), 1097–1105. https://doi.org/10.1136/jnnp-2014-309180

Article  PubMed  Google Scholar 

Li, M., Zheng, G., Zheng, Y., Xiong, Z., Xia, R., Zhou, W., & Chen, L. (2017). Alterations in resting-state functional connectivity of the default mode network in amnestic mild cognitive impairment: An fMRI study. Bmc Medical Imaging, 17 (1), 48. https://doi.org/10.1186/s12880-017-0221-9

Article  PubMed  PubMed Central  Google Scholar 

Liu, X., Jiang, W., & Yuan, Y. (2018). Aberrant default Mode Network underlying the cognitive deficits in the patients with late-onset depression. Frontiers in Aging Neuroscience, 10, 310. https://doi.org/10.3389/fnagi.2018.00310

Article  PubMed  PubMed Central  Google Scholar 

Luppa, M., Sikorski, C., Motzek, T., Konnopka, A., König, H. H., & Riedel-Heller, S. G. (2012). Health service utilization and costs of depressive symptoms in late life - a systematic review. Curr Pharm Des, 18 (36), 5936–5957. https://doi.org/10.2174/138161212803523572

Article  CAS  PubMed  Google Scholar 

Mai, N., Zhong, X., Chen, B., Peng, Q., Wu, Z., Zhang, W., & Ning, Y. (2017). Weight Rich-Club analysis in the White Matter Network of Late-Life Depression with Memory deficits. Frontiers in Aging Neuroscience, 9, 279. https://doi.org/10.3389/fnagi.2017.00279

Article  PubMed  PubMed Central  Google Scholar 

Mai, N., Wu, Y., Zhong, X., Chen, B., Zhang, M., & Ning, Y. (2020). Determining the effects of LLD and MCI on brain decline according to machine learning and a structural covariance network analysis. Journal of Psychiatric Research, 126, 43–54. https://doi.org/10.1016/j.jpsychires.2020.04.011

Article  PubMed  Google Scholar 

Mai, N., Wu, Y., Zhong, X., Chen, B., Zhang, M., Peng, Q., & Ning, Y. (2021). Different Modular Organization between Early Onset and late Onset Depression: A study base on Granger Causality Analysis. Frontiers in Aging Neuroscience, 13, 625175. https://doi.org/10.3389/fnagi.2021.625175

Article  CAS  PubMed  PubMed Central  Google Scholar 

Martínez-Cengotitabengoa, M., Carrascón, L., O’Brien, J. T., Díaz-Gutiérrez, M. J., Bermúdez-Ampudia, C., Sanada, K., & González-Pinto, A. (2016). Peripheral inflammatory parameters in late-life depression: A systematic review. International Journal of Molecular Sciences, 17 (12). https://doi.org/10.3390/ijms17122022

Naismith, S. L., Norrie, L. M., Mowszowski, L., & Hickie, I. B. (2012). The neurobiology of depression in later-life: Clinical, neuropsychological, neuroimaging and pathophysiological features. Progress in Neurobiology, 98 (1), 99–143. https://doi.org/10.1016/j.pneurobio.2012.05.009

Article  PubMed  Google Scholar 

Salo, K. I., Scharfen, J., Wilden, I. D., Schubotz, R. I., & Holling, H. (2019). Confining the Concept of Vascular Depression to Late-Onset Depression: A Meta-analysis of MRI-Defined hyperintensity burden in major depressive disorder and bipolar disorder. Frontiers in Psychology, 10, 1241. https://doi.org/10.3389/fpsyg.2019.01241

Article  PubMed  PubMed Central  Google Scholar 

Sheline, Y. I., Barch, D. M., Garcia, K., Gersing, K., Pieper, C., Welsh-Bohmer, K., & Doraiswamy, P. M. (2006). Cognitive function in late life depression: Relationships to depression severity, cerebrovascular risk factors and processing speed. Biological Psychiatry, 60 (1), 58–65. https://doi.org/10.1016/j.biopsych.2005.09.019

Article  PubMed  Google Scholar 

Shu, M., Feng, S., & Liu, J. (2022). Targeting disrupted rich-club network organization with neuroplasticity-based computerized cognitive remediation in major depressive disorder patients. Psychiatry Research, 316, 114742. https://doi.org/10.1016/j.psychres.2022.114742

Article  PubMed  Google Scholar 

van den Heuvel, M. P., & Sporns, O. (2011). Rich-club organization of the human connectome. Journal of Neuroscience, 31 (44), 15775–15786. https://doi.org/10.1523/jneurosci.3539-11.2011

Article  PubMed  Google Scholar 

van den Heuvel, M. P., Sporns, O., Collin, G., Scheewe, T., Mandl, R. C., Cahn, W., & Kahn, R. S. (2013). Abnormal rich club organization and functional brain dynamics in schizophrenia. JAMA Psychiatry, 70 (8), 783–792. https://doi.org/10.1001/jamapsychiatry.2013.1328

Article  PubMed  Google Scholar 

Wang, J., Wang, X., Xia, M., Liao, X., Evans, A., & He, Y. (2015). GRETNA: A graph theoretical network analysis toolbox for imaging connectomics. Frontiers in Human Neuroscience, 9, 386. https://doi.org/10.3389/fnhum.2015.00386

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wen, Z. L., Chang, L., Hau, K. T., & Liu, H. Y. (2004). Testing and application of the mediating effects. Acta Psychologica Sinica, 36 (5), 614–620.

Google Scholar 

Weyerer, S., Eifflaender-Gorfer, S., Wiese, B., Luppa, M., Pentzek, M., Bickel, H., & Riedel-Heller, S. G. (2013). Incidence and predictors of depression in non-demented primary care attenders aged 75 years and older: Results from a 3-year follow-up study. Age and Ageing, 42 (2), 173–180. https://doi.org/10.1093/ageing/afs184

Article  PubMed  Google Scholar 

Wu, Y., Zhong, X., Mai, N., Wen, Y., Shang, D., Hu, L., & Ning, Y. (2018). Kynurenine pathway changes in late-life depression. Journal of Affective Disorders, 235, 76–81. https://doi.org/10.1016/j.jad.2018.04.007

Article  CAS  PubMed  Google Scholar