Abstract
Sertraline is one of the most commonly prescribed antidepressants. Major depressive disorder (MDD) is characterized by spontaneous thoughts that are laden with negative affect—a “malignant sadness”. Prior neuroimaging studies have identified abnormal resting-state functional connectivity (rsFC) in the spontaneous brain networks of MDD patients. But how antidepressant medication acts to relieve the experience of depression as well as adjust its associated spontaneous networks and mood-regulation circuits remains an open question. In this study, we recruited 22 drug-naïve MDD patients along with 35 normal controls and investigated whether the functional integrity of cortical networks associated with spontaneous thoughts is modulated by sertraline treatment. We attempted to predict post-treatment effects based upon what we observed in the pre-treatment rsFC of drug-naïve MDD patients. In the result, we demonstrated that (1) after the sertraline treatment, the medial temporal lobe of default network (DNMTL) and mood regulation pathway—the fronto-parietal control network (FPCN), the thalamus, and the salience network (SN)—were restored to normal connectivity, relative to the pre-treatment condition; however, the altered connections of FPCN-core DN (DNCORE), FPCN-SN, and intra-FPCN among MDD patients remained impaired; (2) thalamo-prefrontal connectivity provides moderate predictive power (r2 = 0.63) for the effectiveness of sertraline treatment. In summary, our findings contribute to a body of evidence that suggests salubrious effects of sertraline treatment primarily involve the FPCN-thalamus-SN pathway. The pre-treatment rsFC in this pathway could serve as a predictor of sertraline treatment outcome.
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Aiello, M., Salvatore, E., Cachia, A., Pappatà, S., Cavaliere, C., Prinster, A., et al. (2015). Relationship between simultaneously acquired resting-state regional cerebral glucose metabolism and functional MRI: A PET/MR hybrid scanner study. NeuroImage. https://doi.org/10.1016/j.neuroimage.2015.03.017.
Akgören, N., Fabricius, M., & Lauritzen, M. (1994). Importance of nitric oxide for local increases of blood flow in rat cerebellar cortex during electrical stimulation. Proceedings of the National Academy of Sciences of the United States of America, 91(13), 5903–5907 http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=7517038.
Alexander, G. E., & Crutcher, M. D. (1990). Functional architecture of basal ganglia circuits: Neural substrates of parallel processing. Trends in Neurosciences. https://doi.org/10.1016/0166-2236(90)90107-L.
Alexopoulos, G. S., Hoptman, M. J., Kanellopoulos, D., Murphy, C. F., Lim, K. O., & Gunning, F. M. (2012). Functional connectivity in the cognitive control network and the default mode network in late-life depression. Journal of Affective Disorders, 139(1), 56–65. https://doi.org/10.1016/j.jad.2011.12.002.
Anand, A., Li, Y., Wang, Y., Wu, J., Gao, S., Bukhari, L., et al. (2005a). Activity and connectivity of brain mood regulating circuit in depression: A functional magnetic resonance study. Biological Psychiatry, 57(10), 1079–1088. https://doi.org/10.1016/j.biopsych.2005.02.021.
Anand, A., Li, Y., Wang, Y., Wu, J., Gao, S., Bukhari, L., et al. (2005b). Antidepressant effect on connectivity of the mood-regulating circuit: An fMRI study. Neuropsychopharmacology, 30(7), 1334–1344. https://doi.org/10.1038/sj.npp.1300725.
Andrew Kozel, F., Rao, U., Lu, H., Nakonezny, P. A., Grannemann, B., McGregor, T., et al. (2011). Functional connectivity of brain structures correlates with treatment outcome in major depressive disorder. Frontiers in Psychiatry, 2, 7. https://doi.org/10.3389/fpsyt.2011.00007.
Andrews-Hanna, J. R., Reidler, J. S., Sepulcre, J., Poulin, R., & Buckner, R. L. (2010). Functional-anatomic fractionation of the Brain’s default network. Neuron, 65(4), 550–562. https://doi.org/10.1016/j.neuron.2010.02.005.
Beck, A., Steer, R., & Brown, G. (1996). Beck depression inventory-II (pp. 12–15). San Antonio: Psychological Corporation. https://doi.org/10.1037/t00742-000.
Bousman, C. A., Forbes, M., Jayaram, M., Eyre, H., Reynolds, C. F., Berk, M., et al. (2017). Antidepressant prescribing in the precision medicine era: A prescriber’s primer on pharmacogenetic tools. BMC Psychiatry. https://doi.org/10.1186/s12888-017-1230-5.
Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The brain’s default network: Anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences. https://doi.org/10.1196/annals.1440.011.
Buckner, R. L., Krienen, F. M., & Yeo, B. T. T. (2013). Opportunities and limitations of intrinsic functional connectivity MRI. Nature Neuroscience. https://doi.org/10.1038/nn.3423.
Carneiro, A. M., Fernandes, F., & Moreno, R. A. (2015). Hamilton depression rating scale and montgomery-asberg depression rating scale in depressed and bipolar I patients: Psychometric properties in a Brazilian sample. Health and Quality of Life Outcomes. https://doi.org/10.1186/s12955-015-0235-3.
Chen, B., Xu, T., Zhou, C., Wang, L., Yang, N., Wang, Z., et al. (2015). Individual variability and test-retest reliability revealed by ten repeated resting-state brain scans over one month. PLoS One. https://doi.org/10.1371/journal.pone.0144963.
Cho, Y. T., Fromm, S., Guyer, A. E., Detloff, A., Pine, D. S., Fudge, J. L., & Ernst, M. (2013). Nucleus accumbens, thalamus and insula connectivity during incentive anticipation in typical adults and adolescents. NeuroImage, 66, 508–521. https://doi.org/10.1016/j.neuroimage.2012.10.013.
Christoff, K., Keramatian, K., Gordon, A. M., Smith, R., & Mädler, B. (2009). Prefrontal organization of cognitive control according to levels of abstraction. Brain Research. https://doi.org/10.1016/j.brainres.2009.05.096.
Christoff, K., Irving, Z. C., Fox, K. C. R., Spreng, R. N., & Andrews-hanna, J. R. (2016). Mind-wandering as spontaneous thought: A dynamic framework. Nature Reviews Neuroscience, 17(11), 718–731. https://doi.org/10.1038/nrn.2016.113.
Colloby, S. J., Firbank, M. J., He, J., Thomas, A. J., Vasudev, A., Parry, S. W., & O’Brien, J. T. (2012). Regional cerebral blood flow in late-life depression: Arterial spin labelling magnetic resonance study. The British journal of psychiatry : the journal of mental science, 200(2), 150–155. https://doi.org/10.1192/bjp.bp.111.092387.
Conio, B., Martino, M., Magioncalda, P., Escelsior, A., Inglese, M., Amore, M., & Northoff, G. (2019). Opposite effects of dopamine and serotonin on resting-state networks: Review and implications for psychiatric disorders. Molecular Psychiatry. https://doi.org/10.1038/s41380-019-0406-4.
Cox, R. W. (1996). AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages. Computers and Biomedical Research. https://doi.org/10.1006/cbmr.1996.0014.
Cummings, J. L. (1995). Anatomic and behavioral aspects of frontal-subcortical circuits. Annals of the New York Academy of Sciences. https://doi.org/10.1111/j.1749-6632.1995.tb38127.x.
Davidson, R. J., Irwin, W., Anderle, M. J., & Kalin, N. H. (2003). The neural substrates of affective processing in depressed patients treated with venlafaxine. American Journal of Psychiatry, 160(1), 64–75. https://doi.org/10.1176/appi.ajp.160.1.64.
Di, X., Kim, E. H., Huang, C. C., Tsai, S. J., Lin, C. P., & Biswal, B. B. (2013). The influence of the amplitude of low-frequency fluctuations on resting-state functional connectivity. Frontiers in Human Neuroscience. https://doi.org/10.3389/fnhum.2013.00118.
Dixon, M. L., Fox, K. C. R., & Christoff, K. (2014). A framework for understanding the relationship between externally and internally directed cognition. Neuropsychologia. https://doi.org/10.1016/j.neuropsychologia.2014.05.024.
Dixon, M. L., De La Vega, A., Mills, C., Andrews-Hanna, J., Spreng, R. N., Cole, M. W., & Christoff, K. (2018). Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks. Proceedings of the National Academy of Sciences of the United States of America. https://doi.org/10.1073/pnas.1715766115.
Drevets, W. C., Bogers, W., & Raichle, M. E. (2002). Functional anatomical correlates of antidepressant drug treatment assessed using PET measures of regional glucose metabolism. European Neuropsychopharmacology, 12(6), 527–544. https://doi.org/10.1016/S0924-977X(02)00102-5.
Duhameau, B., Ferré, J. C., Jannin, P., Gauvrit, J. Y., Vérin, M., Millet, B., & Drapier, D. (2010). Chronic and treatment-resistant depression: A study using arterial spin labeling perfusion MRI at 3Tesla. Psychiatry Research - Neuroimaging. https://doi.org/10.1016/j.pscychresns.2010.01.009.
Dupont, R. M., Jernigan, T. L., Heindel, W., Butters, N., Shafer, K., Wilson, T., et al. (1995). Magnetic resonance imaging and mood disorders. Localization of white matter and other subcortical abnormalities. Archives of General Psychiatry, 52(9), 747–755. https://doi.org/10.1001/archpsyc.1995.03950210041009.
Fales, C. L., Barch, D. M., Rundle, M. M., Mintun, M. A., Snyder, A. Z., Cohen, J. D., et al. (2008). Altered emotional interference processing in affective and cognitive-control brain circuitry in major depression. Biological Psychiatry, 63(4), 377–384. https://doi.org/10.1016/j.biopsych.2007.06.012.
Fox, M. D., & Greicius, M. (2010). Clinical applications of resting state functional connectivity. Frontiers in Systems Neuroscience, 4(19), 1–13. https://doi.org/10.3389/fnsys.2010.00019.
Fu, C. H. Y., Steiner, H., & Costafreda, S. G. (2013). Predictive neural biomarkers of clinical response in depression: A meta-analysis of functional and structural neuroimaging studies of pharmacological and psychological therapies. Neurobiology of Disease, 52, 75–83. https://doi.org/10.1016/j.nbd.2012.05.008.
Goodwin, G. M. (1997). Neuropsychological and neuroimaging evidence for the involvement of the frontal lobes in depression. Journal of Psychopharmacology, 11(2), 115–122. https://doi.org/10.1177/026988119701100204.
Greicius, M. D., Flores, B. H., Menon, V., Glover, G. H., Solvason, H. B., Kenna, H., et al. (2007). Resting-state functional connectivity in major depression: Abnormally increased contributions from Subgenual cingulate cortex and thalamus. Biological Psychiatry, 62(5), 429–437. https://doi.org/10.1016/j.biopsych.2006.09.020.
Guo, W. B., Liu, F., Xun, G. L., Hu, M. R., Guo, X. F., Xiao, C. Q., et al. (2013). Reversal alterations of amplitude of low-frequency fluctuations in early and late onset, first-episode, drug-naive depression. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 40(1), 153–159. https://doi.org/10.1016/j.pnpbp.2012.08.014.
Halassa, M. M., & Kastner, S. (2017). Thalamic functions in distributed cognitive control. Nature Neuroscience, 20(12), 1669–1679. https://doi.org/10.1038/s41593-017-0020-1.
Hale, A., Corral, R. M., Mencacci, C., Ruiz, J. S., Severo, C. A., & Gentil, V. (2010). Superior antidepressant efficacy results of agomelatine versus fluoxetine in severe MDD patients: A randomized, double-blind study. International Clinical Psychopharmacology, 25(6), 305–314. https://doi.org/10.1097/YIC.0b013e32833a86aa.
Hamilton, J. P., Farmer, M., Fogelman, P., & Gotlib, I. H. (2015). Depressive rumination, the default-mode network, and the dark matter of clinical neuroscience. Biological Psychiatry. https://doi.org/10.1016/j.biopsych.2015.02.020.
Ho, T. C., Wu, J., Shin, D. D., Liu, T. T., Tapert, S. F., Yang, G., et al. (2013). Altered cerebral perfusion in executive, affective, and motor networks during adolescent depression. Journal of the American Academy of Child and Adolescent Psychiatry, 52(10). https://doi.org/10.1016/j.jaac.2013.07.008.
Hoge, R. D., & Pike, G. B. (2001). Oxidative metabolism and the detection of neuronal activation via imaging. Journal of Chemical Neuroanatomy. https://doi.org/10.1016/S0891-0618(01)00114-4.
Järnum, H., Eskildsen, S. F., Steffensen, E. G., Lundbye-Christensen, S., Simonsen, C. W., Thomsen, I. S., et al. (2011). Longitudinal MRI study of cortical thickness, perfusion, and metabolite levels in major depressive disorder. Acta Psychiatrica Scandinavica, 124(6), 435–446. https://doi.org/10.1111/j.1600-0447.2011.01766.x.
Kaiser, R. H., Andrews-Hanna, J. R., Spielberg, J. M., Warren, S. L., Sutton, B. P., Miller, G. A., et al. (2015a). Distracted and down: Neural mechanisms of affective interference in subclinical depression. Social Cognitive and Affective Neuroscience, 10(5), 654–663. https://doi.org/10.1093/scan/nsu100.
Kaiser, R. H., Andrews-Hanna, J. R., Wager, T. D., & Pizzagalli, D. A. (2015b). Large-scale network dysfunction in major depressive disorder: A meta-analysis of resting-state functional connectivity. JAMA Psychiatry, 72(6), 603–611. https://doi.org/10.1001/jamapsychiatry.2015.0071.
Kong, L., Wu, F., Tang, Y., Ren, L., Kong, D., Liu, Y., et al. (2014). Frontal-subcortical volumetric deficits in single episode, medication-naïve depressed patients and the effects of 8 weeks fluoxetine treatment: A VBM-DARTEL study. PLoS One, 9(1), e79055. https://doi.org/10.1371/journal.pone.0079055.
Kranz, G. S., Kasper, S., & Lanzenberger, R. (2010). Reward and the serotonergic system. Neuroscience, 166(4), 1023–1035. https://doi.org/10.1016/j.neuroscience.2010.01.036.
Kugaya, A., Sanacora, G., Staley, J. K., Malison, R. T., Bozkurt, A., Khan, S., et al. (2004). Brain serotonin transporter availability predicts treatment response to selective serotonin reuptake inhibitors. Biological Psychiatry, 56(7), 497–502. https://doi.org/10.1016/j.biopsych.2004.07.001.
Lane, T., Duncan, N. W., Cheng, T., & Northoff, G. (2016). The trajectory of self. Trends in Cognitive Sciences. https://doi.org/10.1016/j.tics.2016.03.004.
Lane, T. J., Northoff, G. (2017). Is depressive rumination rational? In Hung, T. W. and Lane, T. Eds. Rationality: Constraints and Contexts.London: Academic Press. pp. 119–143. https://doi.org/10.1016/B978-0-12-804600-5.00007-6
Langenecker, S. A., Kennedy, S. E., Guidotti, L. M., Briceno, E. M., Own, L. S., Hooven, T., et al. (2007). Frontal and limbic activation during inhibitory control predicts treatment response in major depressive disorder. Biological Psychiatry, 62(11), 1272–1280. https://doi.org/10.1016/j.biopsych.2007.02.019.
LeDoux, J. E. (2000). Emotion circuits in the brain. Annual Review of Neuroscience. https://doi.org/10.1146/annurev.neuro.23.1.155.
Li, C. T., Chen, L. F., Tu, P. C., Wang, S. J., Chen, M. H., Su, T. P., & Hsieh, J. C. (2013). Impaired Prefronto-thalamic functional connectivity as a key feature of treatment-resistant depression: A combined MEG, PET and rTMS study. PLoS One, 8(8), e70089. https://doi.org/10.1371/journal.pone.0070089.
Liu, J., Ren, L., Womer, F. Y., Wang, J., Fan, G., Jiang, W., et al. (2014). Alterations in amplitude of low frequency fluctuation in treatment-naïve major depressive disorder measured with resting-state fMRI. Human Brain Mapping, 35(10), 4979–4988. https://doi.org/10.1002/hbm.22526.
Lui, S., Parkes, L. M., Huang, X., Zou, K., Chan, R. C. K., Yang, H., et al. (2009). Depressive disorders: Focally altered cerebral perfusion measured with arterial spin-labeling MR imaging. Radiology, 251(2), 476–484. https://doi.org/10.1148/radiol.2512081548.
Lui, S., Wu, Q., Qiu, L., Yang, X., Kuang, W., Chan, R. C. K., et al. (2011). Resting-state functional connectivity in treatment-resistant depression. American Journal of Psychiatry, 168(6), 642–648. https://doi.org/10.1176/appi.ajp.2010.10101419.
Matsumoto, N., Minamimoto, T., Graybiel, A. M., & Kimura, M. (2001). Neurons in the thalamic CM-pf complex supply striatal neurons with information about behaviorally significant sensory events. Journal of Neurophysiology, 85(2), 960–976 https://www.ncbi.nlm.nih.gov/pubmed/11160526.
Mayberg, H. S. (2003). Modulating dysfunctional limbic-cortical circuits in depression: Towards development of brain-based algorithms for diagnosis and optimised treatment. British Medical Bulletin. https://doi.org/10.1093/bmb/65.1.193.
Mayberg, H. S., Liotti, M., Brannan, S. K., McGinnis, S., Mahurin, R. K., Jerabek, P. A., et al. (1999). Reciprocal limbic-cortical function and negative mood: Converging PET findings in depression and normal sadness. American Journal of Psychiatry, 156(5), 675–682. https://doi.org/10.1176/ajp.156.5.675.
Menon, V. (2015). Salience network. In Brain mapping: an encyclopedic reference. https://doi.org/10.1016/B978-0-12-397025-1.00052-X.
Mitchell, A. S. (2015). The mediodorsal thalamus as a higher order thalamic relay nucleus important for learning and decision-making. Neuroscience and Biobehavioral Reviews. https://doi.org/10.1016/j.neubiorev.2015.03.001.
Montgomery, S. A., & Asberg, M. (1979). A new depression scale designed to be sensitive to change. British Journal of Psychiatry, 134(4), 382–389. https://doi.org/10.1192/bjp.134.4.382.
Muijsers, R. B., Plosker, G. L., & Noble, S. (2002). Sertraline: A review of its use in the management of major depressive disorder in elderly patients. Drugs & Aging, 19(5), 377–392.
Nakajima, M., & Halassa, M. M. (2017). Thalamic control of functional cortical connectivity. Current Opinion in Neurobiology. https://doi.org/10.1016/j.conb.2017.04.001.
Neumeister, A., Nugent, A. C., Waldeck, T., Geraci, M., Schwarz, M., Bonne, O., et al. (2004). Neural and behavioral responses to tryptophan depletion in unmedicated patients with remitted major depressive disorder and controls. Archives of General Psychiatry, 61(8), 765–773. https://doi.org/10.1001/archpsyc.61.8.765.
Nolen-Hoeksema, S., Wisco, B. E., & Lyubomirsky, S. (2008). Rethinking rumination. Perspectives on Psychological Science, 3(5), 400–424. https://doi.org/10.1111/j.1745-6924.2008.00088.x.
Parnaudeau, S., O’Neill, P. K., Bolkan, S. S., Ward, R. D., Abbas, A. I., Roth, B. L., et al. (2013). Inhibition of Mediodorsal thalamus disrupts Thalamofrontal connectivity and cognition. Neuron, 77(6), 1151–1162. https://doi.org/10.1016/j.neuron.2013.01.038.
Peng, D. H., Shen, T., Zhang, J., Huang, J., Liu, J., Liu, S. Y., et al. (2012). Abnormal functional connectivity with mood regulating circuit in unmedicated individual with major depression: A resting-state functional magnetic resonance study. Chinese Medical Journal, 125(20), 3701–3706. https://doi.org/10.3760/cma.j.issn.0366-6999.2012.20.019.
Phillips, M. L., Young, A. W., Senior, C., Brammer, M., Andrew, C., Calder, A. J., et al. (1997). A specific neural substrate for perceiving facial expressions of disgust. Nature. https://doi.org/10.1038/39051.
Phillips, M. L., Drevets, W. C., Rauch, S. L., & Lane, R. (2003). Neurobiology of emotion perception I: The neural basis of normal emotion perception. Biological Psychiatry. https://doi.org/10.1016/S0006-3223(03)00168-9.
Posner, J., Hellerstein, D. J., Gat, I., Mechling, A., Klahr, K., Wang, Z., et al. (2013). Antidepressants normalize the default mode network in patients with dysthymia. JAMA Psychiatry, 70(4), 373–382. https://doi.org/10.1001/jamapsychiatry.2013.455.
Power JD, Mitra A, Laumann TO, Snyder AZ, Schlaggar BL, Petersen SE. (2014). Methods to detect, characterize, and remove motion artifact in resting state fMRI. NeuroImage 84,320–341. https://doi.org/10.1016/j.neuroimage.2013.08.048
Power JD, Schlaggar BL, Petersen SE. (2015). Recent progress and outstanding issues in motion correction in resting state fMRI. Neuroimage 105: 536–551. https://doi.org/10.1016/j.neuroimage.2014.10.044
Qin, P., Grimm, S., Duncan, N. W., Fan, Y., Huang, Z., Lane, T., et al. (2016). Spontaneous activity in default-mode network predicts ascription of self-relatedness to stimuli. Social Cognitive and Affective Neuroscience. https://doi.org/10.1093/scan/nsw008.
Savitz, J., & Drevets, W. C. (2009). Bipolar and major depressive disorder: Neuroimaging the developmental-degenerative divide. Neuroscience and Biobehavioral Reviews. https://doi.org/10.1016/j.neubiorev.2009.01.004.
Schultz, W. (1997). Dopamine neurons and their role in reward mechanisms. Current Opinion in Neurobiology. https://doi.org/10.1016/S0959-4388(97)80007-4.
Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., et al. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. Journal of Neuroscience, 27(9), 2349–2356. https://doi.org/10.1523/JNEUROSCI.5587-06.2007.
Sheehan, D. V., & Kamijima, K. (2009). An evidence-based review of the clinical use of sertraline in mood and anxiety disorders. International Clinical Psychopharmacology. https://doi.org/10.1097/YIC.0b013e3282f4b616.
Sheline, Y. I., Barch, D. M., Price, J. L., Rundle, M. M., Vaishnavi, S. N., Snyder, A. Z., et al. (2009). The default mode network and self-referential processes in depression. Proceedings of the National Academy of Sciences, 106(6), 1942–1947. https://doi.org/10.1073/pnas.0812686106.
Smith, K. (2014). Mental health: A world of depression. Nature. https://doi.org/10.1038/515180a.
Smith, D. J., & Cavanagh, J. T. O. (2005). The use of single photon emission computed tomography in depressive disorders. Nuclear Medicine Communications, 26(3), 197–203. https://doi.org/10.1097/00006231-200503000-00004.
Snell, J., Birkes, D., & Dodge, Y. (1996). Alternative methods of regression. Journal of the Royal Statistical Society. Series A (Statistics in Society). https://doi.org/10.2307/2983483.
Snyder, H. R. (2013). Major depressive disorder is associated with broad impairments on neuropsychological measures of executive function: A meta-analysis and review. Psychological Bulletin, 139(1), 81–132. https://doi.org/10.1037/a0028727.
Spreng, R. N., Stevens, W. D., Chamberlain, J. P., Gilmore, A. W., & Schacter, D. L. (2010). Default network activity, coupled with the frontoparietal control network, supports goal-directed cognition. NeuroImage, 53(1), 303–317. https://doi.org/10.1016/j.neuroimage.2010.06.016.
Stange, J. P., Bessette, K. L., Jenkins, L. M., Peters, A. T., Feldhaus, C., Crane, N. A., et al. (2017). Attenuated intrinsic connectivity within cognitive control network among individuals with remitted depression: Temporal stability and association with negative cognitive styles. Human Brain Mapping. https://doi.org/10.1002/hbm.23564.
Veltman, D. J., Rombouts, S. A. R. B., & Dolan, R. J. (2003). Maintenance versus manipulation in verbal working memory revisited: An fMRI study. NeuroImage, 18(2), 247–256. https://doi.org/10.1016/S1053-8119(02)00049-6.
Vincent, J. L., Kahn, I., Snyder, A. Z., Raichle, M. E., & Buckner, R. L. (2008). Evidence for a Frontoparietal control system revealed by intrinsic functional connectivity. Journal of Neurophysiology, 100(6), 3328–3342. https://doi.org/10.1152/jn.90355.2008.
Wang, L., Dai, W., Su, Y., Wang, G., Tan, Y., Jin, Z., et al. (2012). Amplitude of low-frequency oscillations in first-episode, treatment-naive patients with major depressive disorder: A resting-state functional MRI study. PLoS One, 7(10), e48658. https://doi.org/10.1371/journal.pone.0048658.
Webb, C. A., Weber, M., Mundy, E. A., & Killgore, W. D. S. (2014). Reduced gray matter volume in the anterior cingulate, orbitofrontal cortex and thalamus as a function of mild depressive symptoms: A voxel-based morphometric analysis. Psychological Medicine, 44(13), 2833–2843. https://doi.org/10.1017/S0033291714000348.
Williams, J. B. (1988). A structured interview guide for the Hamilton depression rating scale. Archives of General Psychiatry, 45(8), 742–747. https://doi.org/10.1001/archpsyc.1988.01800320058007.
Yamamura, T., Okamoto, Y., Okada, G., Takaishi, Y., Takamura, M., Mantani, A., et al. (2016). Association of thalamic hyperactivity with treatment-resistant depression and poor response in early treatment for major depression: A resting-state fMRI study using fractional amplitude of low-frequency fluctuations. Translational Psychiatry, 6(3), e754. https://doi.org/10.1038/tp.2016.18.
Yang, R., Zhang, H., Wu, X., Yang, J., Ma, M., Gao, Y., et al. (2014). Hypothalamus-anchored resting brain network changes before and after sertraline treatment in major depression. BioMed Research International, 2014, 915026. https://doi.org/10.1155/2014/915026.
Yeh, Y. W., Ho, P. S., Kuo, S. C., Chen, C. Y., Liang, C. S., Yen, C. H., et al. (2015). Disproportionate reduction of serotonin transporter may predict the response and adherence to antidepressants in patients with major depressive disorder: A positron emission tomography study with 4-[18F]-ADAM. The International Journal of Neuropsychopharmacology, 18(7), 1–12. https://doi.org/10.1093/ijnp/pyu120.
Zang, Y., He, Y., Zhu, C., Cao, Q., Sui, M., Liang, M., et al. (2007). Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain Dev, 29(2), 83–91. https://doi.org/10.1016/j.braindev.2006.07.002.
Zigmond, A. S., & Snaith, R. P. (1983). The hospital anxiety and depression scale. Acta Psychiatrica Scandinavica, 67(6), 361–370. https://doi.org/10.1111/j.1600-0447.1983.tb09716.x.
Zuo, X. N., Kelly, C., Adelstein, J. S., Klein, D. F., Castellanos, F. X., & Milham, M. P. (2010). Reliable intrinsic connectivity networks: Test-retest evaluation using ICA and dual regression approach. NeuroImage. https://doi.org/10.1016/j.neuroimage.2009.10.080.
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This research was supported by National Science Council, Taiwan (NSC 102-2314-B-016-057) and Ministry of Science and Technology, Taiwan (MOST 108-2321-B-038-005-MY2, MOST 106-2420-H-038-005-MY2, MOST 106-2410-H-038-003, MOST 106-2632-H-038-001-MY3, MOST 104-2420-H-038-001-MY3, MOST 105-2632-H-038-001-MY3).
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Li-Ming Hsu declares that he has no conflict of interest. Timothy J. Lane declares that he has no conflict of interest. Changwei W. Wu declares that he has no conflict of interest. Chien-Yuan Lin declares that he has no conflict of interest. Chi-Bin Yeh declares that he has no conflict of interest. Hung-Wen Kao declares that he has no conflict of interest. Ching-Po Lin declares that he has no conflict of interest.
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Hsu, LM., Lane, T.J., Wu, C.W. et al. Spontaneous thought-related network connectivity predicts sertraline effect on major depressive disorder. Brain Imaging and Behavior 15, 1705–1717 (2021). https://doi.org/10.1007/s11682-020-00364-w
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DOI: https://doi.org/10.1007/s11682-020-00364-w