Functional connectivity of the subcallosal cingulate cortex and differential outcomes to treatment with cognitive- behavioral therapy or antidepressant medication for major depressive disorder
Open accessAbstract
OBJECTIVE: The purpose of this article was to inform the first-line treatment choice between cognitive-behavioral therapy (CBT) or an antidepressant medication for treatment-naive adults with major depressive disorder by defining a neuroimaging biomarker that differentially identifies the outcomes of remission and treatment failure to these interventions. METHOD: Functional MRI resting-state functional connectivity analyses using a bilateral subcallosal cingulate cortex (SCC) seed was applied to 122 patients from the Prediction of Remission to Individual and Combined Treatments (PReDICT) study who completed 12 weeks of randomized treatment with CBT or antidepressant medication. Of the 122 participants, 58 achieved remission (Hamilton Depression Rating Scale [HAM-D] score ≤7 at weeks 10 and 12), and 24 had treatment failure (<30% decrease from baseline in HAM-D score). A 2×2 analysis of variance using voxel-wise subsampling permutation tests compared the interaction of treatment and outcome. Receiver operating characteristic curves constructed using brain connectivity measures were used to determine possible classification rates for differential treatment outcomes. RESULTS: The resting-state functional connectivity of the following three regions with the SCC was differentially associated with outcomes of remission and treatment failure to CBT and antidepressant medication and survived application of the subsample permutation tests: the left anterior ventrolateral prefrontal cortex/insula, the dorsal midbrain, and the left ventromedial prefrontal cortex. Using the summed SCC functional connectivity scores for these three regions, overall classification rates of 72%-78% for remission and 75%-89% for treatment failure was demonstrated. Positive summed functional connectivity was associated with remission with CBT and treatment failure with medication, whereas negative summed functional connectivity scores were associated with remission to medication and treatment failure with CBT. CONCLUSIONS: Imaging-based depression subtypes defined using resting-state functional connectivity differentially identified an individual's probability of remission or treatment failure with first-line treatment options for major depression. This biomarker should be explored in future research through prospective testing and as a component of multivariate treatment prediction models.
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Incorporation of gene-environment interactions improves the prediction of depression over the polygenic risk score approach.
“Incorporation of gene-environment interactions improves the prediction of depression over the polygenic risk score approach. 302”
From Time for united action on depression: a Lancet–World Psychiatric Association Commission (2022) · cites this paper as [302]
A study of 122 treatment-resistant depression cases revealed two subtypes: one with negative subcallosal cingulate cortex to left insula connectivity responded to medication but not CBT; the other with positive connectivity responded to therapy but not medication.
“For example, a study of 122 treatment-resistant depression cases revealed two subtypes (53). One had negative sub- callosal cingulate cortex to left insula connectivity and responded to medication but not cognitive behavioral therapy. The other had positive connectivity and responded to therapy but not medication.”
From Methods and challenges for assessing heterogeneity (2020) · cites this paper as [53]
Subcallosal cingulate stimulation affects pathways that connect with the orbitofrontal cortex.
“it is possible that the subcallosal cingulate stimulation affects pathways that connect with the OFC (Johansen-Berg et al., 2008; Lujan et al., 2013; Dunlop et al., 2017; Riva-Posse et al., 2018).”
From The orbitofrontal cortex: reward, emotion and depression (2020) · cites this paper as Dunlop et al., 2017
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Cites
Statistical Power Analysis for the Behavioral Sciences
Muller, K. E., & Cohen, J. (1989) · Technometrics · doi:10.2307/1270020 · Cited by 99,588 · see citing works
An inventory for measuring depression
BECK, A. T. (1961) · Archives of General Psychiatry · doi:10.1001/archpsyc.1961.01710120031004 · Cited by 38,032 · cited 1× · see citing works
“Symptom severity using the HDRS, Hamilton Anxiety Rating Scale (43), and Beck Depression Inventory (44) was assessed weekly by blinded raters for the first 6 weeks after randomization and then every other week until week 12.”
Hamilton, M. (1960) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.23.1.56 · Cited by 32,817 · cited 1× · see citing works
“Patients Adults aged 18–65 years were eligible to participate if they met DSM-IV criteria for a primary current diagnosis of nonpsychotic major depression as assessed by the Structured Clinical Interview for DSM-IV (40) and a psychiatrist’s evaluation, and if they scored $18 on the 17-item Hamilton DepressionRatingSca…”
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324 · cited 1× · see citing works
“The SCC volume was defined using the Harvard-Oxford atlas (49), and the SCC was thresholded at 50% probability centered on MNI coordinates ±6, 24, −11 consistent with seeds used in our other studies of SCC (38,50).”
The assessment of anxiety states by rating
HAMILTON, M. (1959) · British Journal of Medical Psychology · doi:10.1111/j.2044-8341.1959.tb00467.x · Cited by 11,455 · cited 1× · see citing works
“Symptom severity using the HAM-D, Hamilton Anxiety Rating Scale (43), and Beck Depression Inventory (44) was assessed weekly by blinded raters for the first 6 weeks after randomization and then every other week until week 12.”
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553 · cited 1× · see citing works
“The ventromedial portion of BA 10 in the prefrontal cortex is an important component of the default mode network (80) and is extensively connected to the SCC (via the fronto-medial extent of the uncinate fasciculus) (38), FIGURE 3.”
Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.018 · Cited by 7,429 · cited 1× · see citing works
“Mean head motion of included subjects, assessed by framewise displacement (47), did not significantly differ between the treatment outcome groups.”
Selective Cortical Undercutting As a Means of Modifying and Studying Frontal Lobe Function in Man
Scoville, W. B. (1949) · Journal of neurosurgery · doi:10.3171/jns.1949.6.1.0065 · Cited by 7,373 · see citing works
A New Initiative on Precision Medicine
Collins, F. S., & Varmus, H. (2015) · New England Journal of Medicine · doi:10.1056/nejmp1500523 · Cited by 5,202 · see citing works
Cognitive Therapy of Depression
HOLLON, S. D., & BECK, A. T. (1979) · Cognitive-Behavioral Interventions · doi:10.1016/b978-0-12-404480-7.50012-5 · Cited by 4,685 · see citing works
Deep Brain Stimulation for Treatment-Resistant Depression
Mayberg, H. S., Lozano, A. M., Voon, V., McNeely, H. E., Seminowicz, D., Hamani, C., Schwalb, J. M., & Kennedy, S. H. (2005) · Neuron · doi:10.1016/j.neuron.2005.02.014 · Cited by 4,059 · cited 1× · see citing works
“Finally, deep brain stimulation to the SCC and its cortical and subcortical connections may be efficacious in patients with highly treatment-resistant depression (37, 38).”
Self-citationOngur, D. (2000) · Cerebral Cortex · doi:10.1093/cercor/10.3.206 · Cited by 2,627 · cited 1× · see citing works
“as well as the periaqueductal gray and hypothalamus (81, 82).”
Mayberg, H. S., Liotti, M., Brannan, S. K., McGinnis, S., Mahurin, R. K., Jerabek, P. A., Silva, J. A., Tekell, J. L., Martin, C. C., Lancaster, J. L., et al. (1999) · American Journal of Psychiatry · doi:10.1176/ajp.156.5.675 · Cited by 2,416 · cited 1× · see citing works
“The SCC is an extensively connected component of the limbic system that modulates emotional behavior and is particularly involved in feelings of sadness (30,31).”
Self-citationGreicius, M. D., Flores, B. H., Menon, V., Glover, G. H., Solvason, H. B., Kenna, H., Reiss, A. L., & Schatzberg, A. F. (2007) · Biological Psychiatry · doi:10.1016/j.biopsych.2006.09.020 · Cited by 2,214 · cited 1× · see citing works
“Greater functional connectivity between the SCCand the defaultmodenetwork is present in patientswith treatment-resistant depression (32).”
Drevets, W. C., Price, J. L., & Furey, M. L. (2008) · Brain Structure and Function · doi:10.1007/s00429-008-0189-x · Cited by 2,209 · cited 1× · see citing works
“Several prior studies have implicated dysregulation in themedial portion of BA 10 in patientswithmajor depression (77, 78), and thepolar components ofVMPF10maybe smaller in patients with major depression compared with healthy controls (79).”
Prefrontal-Subcortical Pathways Mediating Successful Emotion Regulation
Wager, T. D., Davidson, M. L., Hughes, B. L., Lindquist, M. A., & Ochsner, K. N. (2008) · Neuron · doi:10.1016/j.neuron.2008.09.006 · Cited by 1,761 · cited 1× · see citing works
“The VLPFC activity in healthy controls has been linked repeatedly to emotion regulation (58, 59) and sustained attention (60).”
Gut feelings: the emerging biology of gut-brain communication
Mayer, E. A. (2011) · Nature Reviews Neuroscience · doi:10.1038/nrn3071 · Cited by 1,726 · cited 1× · see citing works
“From a clinical perspective, cases of major depression more associated with signals from the body (“gut feelings”) may be more resistant to pure psychotherapy approaches, whereas major depression that does not involve strong interoceptive experiences may be particularly responsive to CBT (68).”
Neural mechanisms of the cognitive model of depression.
Disner, S. G., Beevers, C. G., Haigh, E. A. P., & Beck, A. T. (2011) · Nature Reviews Neuroscience · doi:10.1038/nrn3027 · Cited by 1,718 · cited 1× · see citing works
“TheVLPFCis involved in stimulus selection, and reducedVLPFCactivation in response to stimuli is associated with inability to disengage from negative stimuli (61).”
Mayberg, H. S. (2003) · British Medical Bulletin · doi:10.1093/bmb/65.1.193 · Cited by 1,166 · cited 1× · see citing works
“Several prior studies have implicated dysregulation in the medial portion of BA 10 in patients with major depression (77,78), and the polar components of VMPF10 may be smaller in patients with major depression than healthy controls (79).”
Self-citationDiscovering Endophenotypes for Major Depression
Hasler, G., Drevets, W. C., Manji, H. K., & Charney, D. S. (2004) · Neuropsychopharmacology · doi:10.1038/sj.npp.1300506 · Cited by 1,123 · cited 1× · see citing works
“The syndrome of major depressive disorder, a highly heterogeneous clinical condition, has largely defied meaningful subtyping (1).”
Goldapple, K., Segal, Z., Garson, C., Lau, M., Bieling, P., Kennedy, S., & Mayberg, H. (2004) · Archives of General Psychiatry · doi:10.1001/archpsyc.61.1.34 · Cited by 1,068 · cited 1× · see citing works
“, increasedmetabolism in the dorsolateral prefrontal cortex) (14).”
Self-citationTargeting abnormal neural circuits in mood and anxiety disorders: from the laboratory to the clinic
Ressler, K. J., & Mayberg, H. S. (2007) · Nature Neuroscience · doi:10.1038/nn1944 · Cited by 1,007 · cited 1× · see citing works
“Among patients with major depression compared with healthy control subjects, relative hyperactivity of limbic brain regions, including the amygdala, insula, and subcallosal cingulate cortex (SCC), is consistently reported; hypoactivity in the dorsolateral prefrontal cortex is another replicated finding (12).”
Self-citationCognitive Emotion Regulation: Insights From Social Cognitive and Affective Neuroscience
Ochsner, K. N., & Gross, J. J. (2008) · Current Directions in Psychological Science · doi:10.1111/j.1467-8721.2008.00566.x · Cited by 988 · see citing works
Dissecting the uncinate fasciculus: disorders, controversies and a hypothesis.
Von Der Heide, R. J., Skipper, L. M., Klobusicky, E., & Olson, I. R. (2013) · Brain · doi:10.1093/brain/awt094 · Cited by 829 · cited 1× · see citing works
“Moreover, VMPF10 and VLPF47 are bidirectionally connected by lateral branches of the uncinate fasciculus, disruptions of which are associated with impairments in use of memory to guide decision making and socio-emotional difficulties (83).”
Prefrontal cortical contributions to working memory: evidence from event-related fMRI studies
D’Esposito, M., Postle, B. R., & Rypma, B. (2000) · Experimental Brain Research · doi:10.1007/s002210000395 · Cited by 796 · cited 1× · see citing works
“VLPFC activity in healthy controls has been linked repeatedly to emotion regulation (58,59) and sustained attention (60).”
A prefrontal cortex–brainstem neuronal projection that controls response to behavioural challenge
Warden, M. R., Selimbeyoglu, A., Mirzabekov, J. J., Lo, M., Thompson, K. R., Kim, S.-Y., Adhikari, A., Tye, K. M., Frank, L. M., & Deisseroth, K. (2012) · Nature · doi:10.1038/nature11617 · Cited by 645 · cited 2× · see citing works
“Sufficient connectivity between the SCCand themidbrain may also reflect the importance of the structural connections between the ventromedial prefrontal cortex and the dorsal raphe (73).”
Precision psychiatry: a neural circuit taxonomy for depression and anxiety
Williams, L. M. (2016) · The Lancet Psychiatry · doi:10.1016/s2215-0366(15)00579-9 · Cited by 641 · cited 1× · see citing works
“However, average differences between groups may mask important heterogeneitybetween individuals (13),withsomepatientsnot showing these changes, or even demonstrating opposite patterns (e.”
Mechanisms of placebo analgesia: rACC recruitment of a subcortical antinociceptive network
Bingel, U., Lorenz, J., Schoell, E., Weiller, C., & Büchel, C. (2006) · Pain · doi:10.1016/j.pain.2005.08.027 · Cited by 567 · cited 1× · see citing works
“In healthy controls, periaqueductal gray activity can be modulated by placebo-induced expectation of pain relief, and functional connectivity between SCC and periaqueductal gray is increasedduringa coldpressor task (72).”
Toward a Neuroimaging Treatment Selection Biomarker for Major Depressive Disorder
McGrath, C. L., Kelley, M. E., Holtzheimer, P. E., Dunlop, B. W., Craighead, W. E., Franco, A. R., Craddock, R. C., & Mayberg, H. S. (2013) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2013.143 · Cited by 561 · cited 7× · see citing works
“Metabolic activity in the right anterior insula emerged as the best candidate for use as a treatment selection biomarker (26), with support provided by the finding that, among nonremitters to monotherapy, the same biomarker predicted eventual remission after addition of the alternative treatment (27).”
InfluentialSelf-citationAutoregulation of Serotonin Neurons: Role in Antidepressant Drug Action
Piñeyro, G., & Blier, P. (1999) · Pharmacological Reviews · doi:10.1016/s0031-6997(24)01417-0 · Cited by 537 · cited 1× · see citing works
“Weak or absent connectivity between the SCC and dorsal raphe may reflect a biological inability of a patient to achieve effortful control over stress responses, and thus indicate the need for a direct effect on the serotonergic transporters and autoreceptors of the raphe by antidepressant medication (76).”
Rive, M. M., van Rooijen, G., Veltman, D. J., .Phillips, M. L., Schene, A. H., & Ruhé, H. G. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.07.018 · Cited by 481 · cited 1× · see citing works
“Impaired emotion regulation is linked to activity in the VLPFC among patients with major depression (62), and rumination is associated with VLPFC activity (63, 64) and volume (65).”
Overlapping activity in anterior insula during interoception and emotional experience
Zaki, J., Davis, J. I., & Ochsner, K. N. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.05.012 · Cited by 462 · cited 1× · see citing works
“The operculo-insular cortex (VLPF47/INS region) is important for interoceptive and emotional processing (66,67).”
Riva-Posse, P., Choi, K. S., Holtzheimer, P. E., McIntyre, C. C., Gross, R. E., Chaturvedi, A., Crowell, A. L., Garlow, S. J., Rajendra, J. K., & Mayberg, H. S. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.03.029 · Cited by 460 · cited 3× · see citing works
“The SCC volume was defined using the Harvard-Oxford atlas (49), and the SCC was thresholded at 50% probability centered on MNI coordinates ±6, 24, −11 consistent with seeds used in our other studies of SCC (38,50).”
Self-citationFu, C. H. Y., Steiner, H., & Costafreda, S. G. (2013) · Neurobiology of Disease · doi:10.1016/j.nbd.2012.05.008 · Cited by 399 · cited 2× · see citing works
“Recent reviews have found inconsistent results for potential neuroimaging predictors of treatment outcomes in major depression (15, 16).”
Dichter, G. S., Gibbs, D., & Smoski, M. J. (2015) · Journal of Affective Disorders · doi:10.1016/j.jad.2014.09.028 · Cited by 375 · see citing works
Connolly, C. G., Wu, J., Ho, T. C., Hoeft, F., Wolkowitz, O., Eisendrath, S., Frank, G., Hendren, R., Max, J. E., Paulus, M. P., et al. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.05.036 · Cited by 356 · cited 1× · see citing works
“Impaired emotion regulation is linked to activity in the VLPFC among patients with major depression (62), and rumination is associated with VLPFC activity (63, 64) and volume (65).”
Fu, C. H. Y., Williams, S. C. R., Cleare, A. J., Scott, J., Mitterschiffthaler, M. T., Walsh, N. D., Donaldson, C., Suckling, J., Andrew, C., Steiner, H., et al. (2008) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.04.033 · Cited by 349 · cited 1× · see citing works
“Others have found better response to CBT among major depressivedisorderpatientswhowereclosest tohealthycontrols in terms of reactivity to emotional stimuli in the ventromedial prefrontal cortex (56), VLPFC, dorsolateral prefrontal cortex, and dorsal anterior cingulate cortex (57).”
A systematic review of resting-state functional-MRI studies in major depression
Wang, L., Hermens, D. F., Hickie, I. B., & Lagopoulos, J. (2012) · Journal of Affective Disorders · doi:10.1016/j.jad.2012.04.013 · Cited by 333 · cited 2× · see citing works
“In our previous report using PET, resting state metabolic activity in the right anterior insula (with the cluster extending into the frontal operculum) differentially predicted remission and treatment failure with CBT and escitalopram (27,28).”
Liotti, M., Mayberg, H. S., McGinnis, S., Brannan, S. L., & Jerabek, P. (2002) · American Journal of Psychiatry · doi:10.1176/appi.ajp.159.11.1830 · Cited by 331 · cited 1× · see citing works
“Impaired emotion regulation is linked to activity in the VLPFC among patients with major depression (62), and rumination is associated with VLPFC activity (63,64) and volume (65).”
Self-citationRitchey, M., Dolcos, F., Eddington, K. M., Strauman, T. J., & Cabeza, R. (2011) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2010.09.007 · Cited by 320 · cited 1× · see citing works
“Others have found better response to CBT among major depressivedisorderpatientswhowereclosest tohealthycontrols in terms of reactivity to emotional stimuli in the ventromedial prefrontal cortex (56), VLPFC, dorsolateral prefrontal cortex, and dorsal anterior cingulate cortex (57).”
Brain metabolic changes in major depressive disorder from pre- to post-treatment with paroxetine
Brody, A. L., Saxena, S., Silverman, D. H. S., Fairbanks, L. A., Phelps, M. E., Huang, S., Wu, H.-M., Maidment, K. M., Baxter, L. R., & Alborzian, S. (1999) · Psychiatry Research Neuroimaging · doi:10.1016/s0925-4927(99)00034-7 · Cited by 292 · see citing works
Delaveau, P., Jabourian, M., Lemogne, C., Guionnet, S., Bergouignan, L., & Fossati, P. (2011) · Journal of Affective Disorders · doi:10.1016/j.jad.2010.09.032 · Cited by 281 · cited 1× · see citing works
“Prior studies have shown that antidepressant medication treatment alters reactivity of the SCC, VLPFC, and insula (85), as well as the functional connectivity between cortical and limbic regions in major depression patients (86).”
Amat, J., Paul, E., Zarza, C., Watkins, L. R., & Maier, S. F. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.3630-06.2006 · Cited by 249 · cited 1× · see citing works
“The ventromedial prefrontal cortex (incorporating the SCC) is crucial for regulating an organism’s response to both controllable and uncontrollable stressors, mediated in part by its regulation of dorsal raphe activity in response to stress (73, 74).”
Chen, G., Adleman, N. E., Saad, Z. S., Leibenluft, E., & Cox, R. W. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.027 · Cited by 248 · cited 1× · see citing works
“Contrasts were performed using a whole-brain voxel-wise 232 analysis of variance (ANOVA) (3dMVM) (53) with treatment (medication or CBT) and 12-week outcomes (remission or treatment failure).”
A tractography analysis of two deep brain stimulation white matter targets for depression
Gutman, D. A., Holtzheimer, P. E., Behrens, T. E. J., Johansen-Berg, H., & Mayberg, H. S. (2009) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.09.021 · Cited by 220 · cited 1× · see citing works
“TheSCCvolumewas defined using the Harvard-Oxford Atlas (49), and the SCC was thresholded at 50% probability centered on MNI coordinates66, 24, –11, consistent with seeds used in our other studies of SCC (38, 50).”
Self-citationCannon, D. M., Ichise, M., Rollis, D., Klaver, J. M., Gandhi, S. K., Charney, D. S., Manji, H. K., & Drevets, W. C. (2007) · Biological Psychiatry · doi:10.1016/j.biopsych.2007.03.016 · Cited by 219 · cited 1× · see citing works
“Further, serotonin transporter concentrations may be elevated in the periaqueductal grey of major depression patients versus healthy controls (71).”
Anand, A., Li, Y., Wang, Y., Gardner, K., & Lowe, M. J. (2007) · The Journal of Neuropsychiatry and Clinical Neurosciences · doi:10.1176/appi.neuropsych.19.3.274 · Cited by 215 · cited 1× · see citing works
“Prior studies have shown that antidepressant medication treatment alters reactivity of the SCC, VLPFC, and insula (85), as well as the functional connectivity between cortical and limbic regions in major depression patients (86).”
FATCAT: (An Efficient) Functional And Tractographic Connectivity Analysis Toolbox
Taylor, P. A., & Saad, Z. S. (2013) · Brain Connectivity · doi:10.1089/brain.2013.0154 · Cited by 211 · cited 1× · see citing works
“Utilizing 3dNetCorr (51), the mean time course of the bilateral seed was correlated voxel-wise with the rest of the brain.”
Toward Clinically Useful Neuroimaging in Depression Treatment
Siegle, G. J., Thompson, W. K., Collier, A. B., Berman, S., Feldmiller, J., Thase, M. E., & Friedman, E. S. (2012) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2012.65 · Cited by 206 · see citing works
Williams, L. M., Korgaonkar, M. S., Song, Y. C., Paton, R., Eagles, S., Goldstein-Piekarski, A., Grieve, S. M., Harris, A. W. F., Usherwood, T., & Etkin, A. (2015) · Neuropsychopharmacology · doi:10.1038/npp.2015.89 · Cited by 195 · see citing works
Weitz, E. S., Hollon, S. D., Twisk, J., van Straten, A., Huibers, M. J. H., David, D., DeRubeis, R. J., Dimidjian, S., Dunlop, B. W., Cristea, I. A., et al. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.1516 · Cited by 187 · see citing works
Self-citationKonarski, J. Z., Kennedy, S. H., Segal, Z. V., Lau, M. A., Bieling, P., McIntyre, R. S., & Mayberg, H. S. (2009) · Journal of Psychiatry and Neuroscience · doi:10.1139/jpn.0923 · Cited by 155 · see citing works
Self-citationSchatzberg, A. F., Rush, A. J., Arnow, B. A., Banks, P. L. C., Blalock, J. A., Borian, F. E., Howland, R., Klein, D. N., Kocsis, J. H., Kornstein, S. G., et al. (2005) · Archives of General Psychiatry · doi:10.1001/archpsyc.62.5.513 · Cited by 147 · cited 1× · see citing works
“Importantly, some patients who do not respond to one treatment intervention exhibit an excellent response when switched to the alternative (4, 5).”
Dunlop, B. W., Kelley, M. E., Aponte‐Rivera, V., Mletzko, T., Kinkead, B. L., Ritchie, J., Nemeroff, C. B., Craighead, W. E., Mayberg, H. S., & for the PReDICT Team (2017) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2016.16050517 · Cited by 140 · cited 3× · see citing works
“Studies The design of the Emory Predictors of Remission in Depression to Individual andCombinedTreatments (PReDICT) study has been published previously (39), and the clinical results of the trial are presented elsewhere (10).”
Self-citationPretreatment Brain States Identify Likely Nonresponse to Standard Treatments for Depression
McGrath, C. L., Kelley, M. E., Dunlop, B. W., Holtzheimer III, P. E., Craighead, W. E., & Mayberg, H. S. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.12.005 · Cited by 139 · cited 2× · see citing works
“Based on prior work (26, 27, 36),wehypothesized that pretreatment levels of SCC resting-state functional connectivity to other cortical and limbic regions would differentially predict the clinical outcomes of the CBT and antidepressant medication treatments.”
Self-citationDunlop, B. W., Binder, E. B., Cubells, J. F., Goodman, M. M., Kelley, M. E., Kinkead, B., Kutner, M., Nemeroff, C. B., Newport, D. J., Owens, M. J., et al. (2012) · Trials · doi:10.1186/1745-6215-13-106 · Cited by 136 · cited 2× · see citing works
“Studies The design of the Emory Predictors of Remission in Depression to Individual andCombinedTreatments (PReDICT) study has been published previously (39), and the clinical results of the trial are presented elsewhere (10).”
Self-citationCraighead, W. E., & Dunlop, B. W. (2011) · Annual Review of Psychology · doi:10.1146/annurev.psych.121208.131653 · Cited by 129 · cited 1× · see citing works
“Combination treatment with psychotherapy and antidepressant medication improves remission rates, but barriers such as cost, time, andpatientpreferencepreclude this option formany patients (3).”
Self-citationNeuroimaging-based biomarkers for treatment selection in major depressive disorder
Dunlop, B. W., & Mayberg, H. S. (2014) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2014.16.4/bdunlop · Cited by 127 · cited 2× · see citing works
“We have previously proposed that psychotherapy-responsive depression may represent a brain state with sufficiently adequate connectivity in mood-regulating systems such that engagement of these systems via psychotherapy can reduce negative emotional states (25).”
Self-citationVeerakumar, A., Challis, C., Gupta, P., Da, J., Upadhyay, A., Beck, S. G., & Berton, O. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.12.009 · Cited by 102 · cited 1× · see citing works
“Furthermore, in a chronic social defeat model of depression inmice, deep brain stimulation to the ventromedial prefrontal cortex induces neuroplastic changes in the serotonergic neurons in the dorsal raphe (75).”
Intergenerational neural mediators of early-life anxious temperament
Fox, A. S., Oler, J. A., Shackman, A. J., Shelton, S. E., Raveendran, M., McKay, D., Converse, A. K., Alexander, A. L., Davidson, R. J., Blangero, J., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1508593112 · Cited by 98 · cited 1× · see citing works
“Intriguingly, metabolic activity in the anterior insula and periaqueductal gray of rhesus monkeys correlates positively with anxious temperament behaviors in animals exposed to threat (84).”
zu Eulenburg, P., Baumgärtner, U., Treede, R.-D., & Dieterich, M. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.06.057 · Cited by 82 · cited 1× · see citing works
“The operculo-insular cortex (VLPF47/INS region) is important for interoceptive and emotional processing (66,67).”
Brain activation predicts treatment improvement in patients with major depressive disorder
Samson, A. C., Meisenzahl, E., Scheuerecker, J., Rose, E., Schoepf, V., Wiesmann, M., & Frodl, T. (2011) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2011.03.009 · Cited by 78 · see citing works
Pragmatism Instead of Mechanism
Paulus, M. P. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.0497 · Cited by 67 · see citing works
Bludau, S., Bzdok, D., Gruber, O., Kohn, N., Riedl, V., Sorg, C., Palomero-Gallagher, N., Müller, V. I., Hoffstaedter, F., Amunts, K., et al. (2016) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2015.15030349 · Cited by 67 · cited 1× · see citing works
“Several prior studies have implicated dysregulation in themedial portion of BA 10 in patientswithmajor depression (77, 78), and thepolar components ofVMPF10maybe smaller in patients with major depression compared with healthy controls (79).”
Simultaneous acquisition of gradient‐echo and asymmetric spin‐echo for single‐shot z‐shim: Z‐SAGA
Heberlein, K., & Hu, X. P. (2003) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10680 · Cited by 60 · cited 1× · see citing works
“Resting-state fMRI datawere acquired using a Z-SAGA sequence (46) to recover areas affected by susceptibility artifact, with the following parameters: 150 measurements; 30 axial slices; voxel resolution=3.”
Milak, M. S., Parsey, R. V., Lee, L., Oquendo, M. A., Olvet, D. M., Eipper, F., Malone, K. M., & Mann, J. J. (2009) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2008.09.004 · Cited by 58 · cited 1× · see citing works
“pre-treatment resting state metabolism in the midbrain did predict remission to standard antidepressant medications (69).”
Evidence-Based Applications of Combination Psychotherapy and Pharmacotherapy for Depression
Dunlop, B. W. (2016) · FOCUS The Journal of Lifelong Learning in Psychiatry · doi:10.1176/appi.focus.20150042 · Cited by 53 · cited 2× · see citing works
“Furthermore, because combination treatment with both psychotherapy and medication formajor depression is often not required or not feasible, selectionof the initial treatment is typically a forced choice between psychotherapy and medication (5).”
Self-citationLittle, J. T., Ketter, T. A., Kimbrell, T. A., Danielson, A., Benson, B., Willis, M. W., & Post, R. M. (1996) · PubMed · Cited by 45 · see citing works
Dunlop, B. W., Kelley, M. E., McGrath, C. L., Craighead, W. E., & Mayberg, H. S. (2015) · The Journal of Neuropsychiatry and Clinical Neurosciences · doi:10.1176/appi.neuropsych.14030048 · Cited by 43 · cited 4× · see citing works
“The present results, in conjunction with our prior CBT compared with antidepressant medication study using FDGPET (26, 27), argue strongly that brain state subtypes of heterogeneous major depressive disorder patients may reflect their biological capacity to benefit differentially from treatments with differingmechanis…”
InfluentialSelf-citationImaging predictors of remission to anti-depressant medications in major depressive disorder
Kee, F., Korgaonkar, M. S., & Grieve, S. M. (2015) · Journal of Affective Disorders · doi:10.1016/j.jad.2015.07.002 · Cited by 43 · cited 1× · see citing works
“Recent reviews have found inconsistent results for potential neuroimaging predictors of treatment outcomes in major depression, (15,16).”
Cuijpers, P. J., Weitz, E. S., Lamers, F., Penninx, B. W. J. H., Twisk, J. W. R., DeRubeis, R. J., Dimidjian, S., Dunlop, B. W., Jarrett, R. B., Segal, Z. V., et al. (2016) · Depression and Anxiety · doi:10.1002/da.22580 · Cited by 41 · cited 2× · see citing works
“found no difference in outcome among patients treated with CBT or antidepressant medication based on severity (7) or depressive clinical subtype (8).”
Self-citationSmith, R. S., Fadok, R. A., Purcell, M. J., Liu, S., Stonnington, C. M., Spetzler, R. F., & Baxter, L. C. (2011) · Brain Imaging and Behavior · doi:10.1007/s11682-011-9127-2 · Cited by 30 · cited 1× · see citing works
“The SCC is an extensively connected component of the limbic system that modulates emotional behavior and is particularly involved in feelings of sadness (30,31).”
Qiao, L., Wei, D.-T., Li, W.-F., Chen, Q.-L., Che, X.-W., Li, B.-B., Li, Y.-M., Qiu, J., Zhang, Q.-L., & Liu, Y.-J. (2013) · Neuroscience · doi:10.1016/j.neuroscience.2013.09.053 · Cited by 27 · cited 1× · see citing works
“Impaired emotion regulation is linked to activity in the VLPFC among patients with major depression (62), and rumination is associated with VLPFC activity (63, 64) and volume (65).”
Prediction of treatment outcomes in major depressive disorder
Dunlop, B. W. (2015) · Expert Review of Clinical Pharmacology · doi:10.1586/17512433.2015.1075390 · Cited by 22 · cited 2× · see citing works
“Unfortunately, genetic testing, neuroimaging, and psychophysiological approaches, though promising, have not yet proven sufficiently accurate or replicable to warrant clinical application to individual patients (11).”
Self-citationSalerian, A. J., & Altar, C. A. (2012) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2012.04.019 · Cited by 22 · cited 2× · see citing works
“Several studies support the conclusion that, on average, patients with major depression have reduced prefrontal control over emotion-generating limbic structures (29).”
Narrowing the Gaps Between What We Know and What We Do in Psychiatry
Rush, A. J. (2015) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.15ac10309 · Cited by 11 · cited 1× · see citing works
“However, avoiding treatment failure is also a vitally important outcome (24).”
Connectional networks within the orbital and medial prefrontal cortex of macaque monkeys
Carmichael, S. T., & Price, J. L. (1996) · Journal of Comparative Neurology · doi:10.1002/(sici)1096-9861(19960722)371:2
An, X., Bandler, R., �ng�r, D., & Price, J. L. (1998) · The Journal of Comparative Neurology · doi:10.1002/(sici)1096-9861(19981130)401:4
Biswal (1997) · doi:10.1002/(sici)1099-1492(199706/08)10:4/5
Flagged first, then by citations
Research works printed but not linked: 5
- [7]Weitz E Hollon SD Twisk J van Straten A David D DeRubeis RJ Dimidjian S Dunlop BW Faramarzi M Hegerl U Jarrett RB Kheirkhah F Kennedy SJ Mergl R Miranda J Mohr DC Rush AJ Segal ZV Siddique J Simmons AD Vittengl JR Cuijpers P Does baseline depression severity moderate outcomes between CBT and pharmacotherapy? An individual participant data meta-analysis JAMA Psychiatry 2015 72 1102 1109 26397232
- [40]First MB Spitzer RL Gibbon M Williams JB Structured Clinical Interview for DSM-IV Axis I Disorders-Patient Edition (SCID-I/P, Version 2.0) Biometrics Research Department, New York State Psychiatric Institute New York 1995
- [56]Ritchey M Dolcos F Eddington KM Strauman TJ Cabeza R Neural correlates of emotional processing in depression: changes with cognitive behavioral therapy and predictors of treatment response J Psychiatr Res 2011 45 577 587 20934190 PMC3042483
- [57]Fu CH Williams SC Cleare AJ Scott J Mitterschiffthaler MT Walsh ND Donaldson C Suckling J Andrew C Steiner H Murray RM Neural responses to sad facial expressions in major depression following cognitive behavioral therapy Biol Psychiatry 2008 154 505 512 18550030
- [69]Milak MS Parsey RV Lee L Oquendo MA Olvet DM Eipper F Malone K Mann JJ Pretreatment regional brain glucose uptake in the midbrain on PET may predict remission from a major depressive episode after three months of treatment Psychiatry Res 2009 173 63 70 19446443 PMC3804908
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Time for united action on depression: a Lancet–World Psychiatric Association Commission
Herrman, H., Patel, V., Kieling, C., Berk, M., Buchweitz, C., Cuijpers, P., Furukawa, T. A., Kessler, R. C., Kohrt, B. A., Maj, M., et al. (2022) · The Lancet · doi:10.1016/s0140-6736(21)02141-3 · Cited by 1,104 · see citing works
Self-citationThe Heterogeneity Problem: Approaches to Identify Psychiatric Subtypes
Feczko, E., Miranda-Dominguez, O., Marr, M., Graham, A. M., Nigg, J. T., & Fair, D. A. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.03.009 · Cited by 443 · see citing works
“as in [38], see also [47]) may not generalize to independent datasets across different sites[48], and therefore require additional independent validation (see Box: 3).”
BackgroundMethodInfluentialThe orbitofrontal cortex: reward, emotion and depression
Rolls, E. T., Cheng, W., & Feng, J. (2020) · Brain Communications · doi:10.1093/braincomms/fcaa196 · Cited by 474 · see citing works
“stimulation affects pathways that connect with the OFC (Johansen-Berg et al., 2008; Lujan et al., 2013; Dunlop et al., 2017; Riva-Posse et al., 2018).”
BackgroundTreatment resistant depression: A multi-scale, systems biology approach
Akil, H., Gordon, J. A., Hen, R., Javitch, J. A., Mayberg, H. S., McEwen, B. S., Meaney, M. J., & Nestler, E. J. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.08.019 · Cited by 443 · see citing works
“Variability in baseline patterns can be further evaluated against known clinical phenotypes (Mayberg, 2003; McGrath et al., 2014; Williams, 2016; Dunlop et al., 2017).”
BackgroundResultInfluentialSelf-citationPrognosis and improved outcomes in major depression: a review
Kraus, C., Kadriu, B., Lanzenberger, R., Zarate, C. A., & Kasper, S. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0460-3 · Cited by 482 · see citing works
The orbitofrontal cortex and emotion in health and disease, including depression
Rolls, E. T. (2017) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2017.09.021 · Cited by 326 · see citing works
“pression, and stimulation in the subcallosal cingulate cortex has been used to treat depression (Drevets et al., 2004; Drevets et al., 1997; Drysdale et al., 2017; Dunlop et al., 2017; Hamani et al., 2009, 2011; Johansen-Berg et al., 2008; Kang et al., 2016; Laxton et al., 2013; Lujan et al., 2013; Mayberg, 2003; Mayb…”
Cingulate dynamics track depression recovery with deep brain stimulation
Alagapan, S., Choi, K. S., Heisig, S., Riva‐Posse, P., Crowell, A. L., Tiruvadi, V., Obatusin, M., Veerakumar, A., Waters, A. C., Gross, R. E., et al. (2023) · Nature · doi:10.1038/s41586-023-06541-3 · Cited by 277 · see citing works
Self-citationDissecting diagnostic heterogeneity in depression by integrating neuroimaging and genetics
Buch, A. M., & Liston, C. M. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-00789-3 · Cited by 271 · see citing works
Syed, S. A., Beurel, E., Loewenstein, D., Lowell, J. A., Craighead, W. E., Dunlop, B. W., Mayberg, H. S., Dhabhar, F. S., Dietrich, W. D., Keane, R. W., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.08.001 · Cited by 212 · see citing works
Self-citationBrain-wide Electrical Spatiotemporal Dynamics Encode Depression Vulnerability
Hultman, R., Ulrich, K., Sachs, B. D., Blount, C., Carlson, D. E., Ndubuizu, N., Bagot, R. C., Parise, E. M., Vu, M.-A. T., Gallagher, N. M., et al. (2018) · Cell · doi:10.1016/j.cell.2018.02.012 · Cited by 183 · see citing works
“, pharmacology, psychotherapy, and transcranial magnetic stimulation) (Drysdale et al., 2017; Dunlop et al., 2017).”
BackgroundRapid Precision Functional Mapping of Individuals Using Multi-Echo fMRI
Lynch, C. J., Power, J. D., Scult, M. A., Dubin, M. J., Gunning, F. M., & Liston, C. M. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108540 · Cited by 192 · see citing works
Machine learning and big data in psychiatry: toward clinical applications
Rutledge, R. B., Chekroud, A. M., & Huys, Q. J. M. (2019) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2019.02.006 · Cited by 195 · see citing works
Lynch, C. J., Gunning, F. M., & Liston, C. M. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.01.012 · Cited by 181 · see citing works
Intrinsic connectomes are a predictive biomarker of remission in major depressive disorder
Korgaonkar, M. S., Goldstein-Piekarski, A. N., Fornito, A., & Williams, L. M. (2020) · Molecular Psychiatry · doi:10.1038/s41380-019-0574-2 · Cited by 163 · see citing works
“Few studies have examined whether pre-treatment intrinsic neural characteristics may pre-dispose an individual to respond to antidepressant medications [19, 20].”
BackgroundToward Circuit Mechanisms of Pathophysiology in Depression
Spellman, T., & Liston, C. M. (2020) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2020.20030280 · Cited by 169 · see citing works
“Multiple multisite collaborations have begun to investigate how abnormalities in specific circuits and functional networks predict individual differences in the antidepressant response to SSRIs (43, 44) and repetitive TMS (rTMS) (45) or differential response to antidepressant medications compared with cognitive-behavi…”
BackgroundNemeroff, C. B. (2020) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2020.20060845 · Cited by 153 · see citing works
Self-citationGe, R., Downar, J. H., Blumberger, D. M., Daskalakis, Z. J., & Vila‐Rodriguez, F. (2019) · Brain stimulation · doi:10.1016/j.brs.2019.10.012 · Cited by 149 · see citing works
“Thus, FC and morphology of sgACC have been investigated as potential predictive biomarkers of treatment response in depression across diverse treatment modalities, including antidepressant medications [8,9], evidence-based psychotherapy [9,10], repetitive transcranial magnetic stimulation (rTMS) [11e14], and electroco…”
BackgroundResultAndrewes, D., & Jenkins, L. (2019) · Neuropsychology Review · doi:10.1007/s11065-019-09398-4 · Cited by 138 · see citing works
New and emerging approaches to treat psychiatric disorders
Scangos, K. W., State, M. W., Miller, A. H., Baker, J. T., & Williams, L. M. (2023) · Nature Medicine · doi:10.1038/s41591-022-02197-0 · Cited by 147 · see citing works
Dunlop, B. W., Kelley, M. E., Aponte‐Rivera, V., Mletzko, T., Kinkead, B. L., Ritchie, J., Nemeroff, C. B., Craighead, W. E., Mayberg, H. S., & for the PReDICT Team (2017) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2016.16050517 · Cited by 140 · see citing works
“In the companion study to this article, we report that resting-state functional connectivity predicted remission and nonresponse rates with roughly 80% accuracy (45).”
BackgroundSelf-citationGaspersz, R., Nawijn, L., Lamers, F., & Penninx, B. W. J. H. (2018) · Current Opinion in Psychiatry · doi:10.1097/yco.0000000000000376 · Cited by 139 · see citing works
Chin Fatt, C. R., Jha, M. K., Cooper, C. M., Fonzo, G., South, C., Grannemann, B., Carmody, T., Greer, T. L., Kurian, B., Fava, M., et al. (2020) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2019.18070870 · Cited by 125 · see citing works
“(20) found that lower summed resting-state functional connectivity of the subcallosal anterior cingulate cortex to the left anterior ventrolateral prefrontal cortex, dorsal midbrain, and left ventromedial prefrontal cortex was associated with remission in patients treated with escitalopram or duloxetine, while the opp…”
BackgroundFunctional Connectivity of the Anterior Cingulate Cortex in Depression and in Health
Rolls, E. T., Cheng, W., Gong, W., Qiu, J., Zhou, C., Zhang, J., Lv, W., Ruan, H., Wei, D., Cheng, K., et al. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy236 · Cited by 131 · see citing works
“Indeed, the subcallosal cingulate cortex is thought to be a key area involved in depression, and is a target for brain stimulation aimed to reduce depression (Lujan et al. 2013; Kang et al. 2016; Mayberg et al. 2016; Drysdale et al. 2017; Dunlop et al. 2017; Ramirez-Mahaluf et al. 2017; Riva-Posse et al. 2018).”
BackgroundGoldstein-Piekarski, A. N., Staveland, B. R., Ball, T. M., Yesavage, J., Korgaonkar, M. S., & Williams, L. M. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0100-3 · Cited by 108 · see citing works
Alexander, L., Wood, C. M., Gaskin, P. L. R., Sawiak, S. J., Fryer, T. D., Hong, Y. T., McIver, L., Clarke, H. F., & Roberts, A. C. (2020) · Nature Communications · doi:10.1038/s41467-020-19167-0 · Cited by 100 · see citing works
Functional connectomics in depression: insights into therapies
Chai, Y., Sheline, Y. I., Oathes, D. J., Balderston, N. L., Rao, H., & Yu, M. (2023) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2023.05.006 · Cited by 108 · see citing works
Methods and challenges for assessing heterogeneity
Feczko, E., & Fair, D. A. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.02.015 · Cited by 96 · see citing works
“For example, a study of 122 treatment-resistant depression cases revealed two subtypes (53).”
BackgroundBrydges, C. R., Fiehn, O., Mayberg, H. S., Schreiber, H. L., Dehkordi, S. M., Bhattacharyya, S., Cha, J., Choi, K. S., Craighead, W. E., Krishnan, R. R., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-99845-1 · Cited by 100 · see citing works
“MATERIALS AND METHODS Study Design The PReDICT study protocol (30), clinical results (31) and initial neuroimaging analyses (32) have been published previously.”
BackgroundMethodInfluentialSelf-citationPredicting Treatment Response in Depression: The Role of Anterior Cingulate Cortex
Godlewska, B. R., Browning, M. D., Norbury, R., Igoumenou, A., Cowen, P. J., & Harmer, C. J. (2018) · The International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyy069 · Cited by 97 · see citing works
Toward personalized medicine in connectomic deep brain stimulation
Hollunder, B., Rajamani, N., Siddiqi, S., Finke, C., Kühn, A. A., Mayberg, H. S., Fox, M., Neudorfer, C., & Horn, A. (2021) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2021.102211 · Cited by 89 · see citing works
Self-citationIntrinsic Brain Network Biomarkers of Antidepressant Response: a Review
Dunlop, K., Talishinsky, A., & Liston, C. (2019) · Current Psychiatry Reports · doi:10.1007/s11920-019-1072-6 · Cited by 80 · see citing works
The anterior cingulate cortex as a key locus of ketamine’s antidepressant action
Alexander, L., Jelen, L. A., Mehta, M. A., & Young, A. H. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.05.003 · Cited by 83 · see citing works
Rakofsky, J. J., & Rapaport, M. H. (2018) · CONTINUUM Lifelong Learning in Neurology · doi:10.1212/con.0000000000000604 · Cited by 80 · see citing works
MahmoudianDehkordi, S., Bhattacharyya, S., Brydges, C. R., Jia, W., Fiehn, O., Rush, A. J., Dunlop, B. W., & Kaddurah-Daouk, R. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.937906 · Cited by 75 · see citing works
Deep Brain Stimulation for Obsessive-Compulsive Disorder and Depression
Sheth, S. A., & Mayberg, H. S. (2023) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-110122-110434 · Cited by 76 · see citing works
Self-citationThe future of personalized brain stimulation
Figee, M., & Mayberg, H. S. (2021) · Nature Medicine · doi:10.1038/s41591-021-01243-7 · Cited by 68 · see citing works
Self-citationDunlop, B. W., LoParo, D., Kinkead, B. L., Mletzko, T., Cole, S. P., Nemeroff, C. B., Mayberg, H. S., & Craighead, W. E. (2019) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2018.18091075 · Cited by 65 · see citing works
“Taken together, the existing data support the rationale for combining treatmentswithdifferingmechanismsofaction, and differing efficacy as indicated by patients’ brain activity patterns (21, 60, 61), to optimize treatment outcomes.”
Self-citationThe neuroscience of emotional disorders
Rolls, E. T. (2021) · Handbook of clinical neurology · doi:10.1016/b978-0-12-822290-4.00002-5 · Cited by 62 · see citing works
Prognosis and Improved Outcomes in Major Depression: A Review
Kraus, C., Kadriu, B., Lanzenberger, R. R., Zarate, C. A., & Kasper, S. F. (2020) · FOCUS The Journal of Lifelong Learning in Psychiatry · doi:10.1176/appi.focus.18205 · Cited by 62 · see citing works
Insular subdivisions functional connectivity dysfunction within major depressive disorder
Peng, X., Lin, P., Wu, X., Gong, R., Yang, R., & Wang, J. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.11.018 · Cited by 60 · see citing works
Device-Based Modulation of Neurocircuits as a Therapeutic for Psychiatric Disorders
Deng, Z., Luber, B. M., Balderston, N. L., Afanador, M. V., Noh, M. M., Thomas, J., Altekruse, W. C., Exley, S. L., Awasthi, S., & Lisanby, S. H. (2020) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010919-023253 · Cited by 58 · see citing works
“This pre/post design has been used to show evidence of CBT-induced plasticity in brain regions that are critical for mood regulation (44), fear conditioning (41), inhibition (39), and cognitive reappraisal (45).”
MethodThe heterogeneity of late-life depression and its pathobiology: a brain network dysfunction disorder
Jellinger, K. A. (2023) · Journal of Neural Transmission · doi:10.1007/s00702-023-02648-z · Cited by 59 · see citing works
Vahid-Ansari, F., Zhang, M., Zahrai, A., & Albert, P. R. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00404 · Cited by 59 · see citing works
Progress in psychoradiology, the clinical application of psychiatric neuroimaging
Huang, X., Gong, Q., Sweeney, J. A., & Biswal, B. B. (2019) · British Journal of Radiology · doi:10.1259/bjr.20181000 · Cited by 57 · see citing works
MRI predictors of pharmacotherapy response in major depressive disorder
Gerlach, A. R., Karim, H. T., Peciña, M., Ajilore, O., Taylor, W. D., Butters, M. A., & Andreescu, C. (2022) · NeuroImage: Clinical · doi:10.1016/j.nicl.2022.103157 · Cited by 57 · see citing works
“Successful treatment has been associated with lower baseline connectivity between the subgenual ACC and the dorsal ACC (small study) (Kozel et al., 2011), ventromedial PFC (large study) (Dunlop, 2017), and PCC (Goldstein-Piekarski et al., 2018).”
BackgroundDunlop, B. W., Cha, J., Choi, K. S., Rajendra, J. K., Nemeroff, C. B., Craighead, W. E., & Mayberg, H. S. (2023) · American Journal of Psychiatry · doi:10.1176/appi.ajp.21070727 · Cited by 56 · see citing works
Self-citationTalishinsky, A., Downar, J. H., Vértes, P. E., Seidlitz, J., Dunlop, K., Lynch, C. J., Whalley, H. C., McIntosh, A. M., Vila‐Rodriguez, F., Daskalakis, Z. J., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32617-1 · Cited by 55 · see citing works
Meyer, B. M., Rabl, U., Huemer, J., Bartova, L., Kalcher, K., Provenzano, J., Brandner, C., Sezen, P., Kasper, S., Schatzberg, A. F., et al. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0395-8 · Cited by 52 · see citing works
Predicting individual clinical trajectories of depression with generative embedding
Frässle, S., Marquand, A. F., Schmaal, L., Dinga, R., Veltman, D. J., van der Wee, N. J. A., van Tol, M., Schöbi, D., Penninx, B. W. J. H., & Stephan, K. E. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102213 · Cited by 51 · see citing works
Connectome-based models can predict early symptom improvement in major depressive disorder
Ju, Y., Horien, C. L., Chen, W., Guo, W., Lu, X., Sun, J., Dong, Q., Liu, B., Liu, J., Yan, D., et al. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.04.028 · Cited by 51 · see citing works
Brain connectivity in major depressive disorder: a precision component of treatment modalities?
Tura, A., & Goya‐Maldonado, R. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02499-y · Cited by 56 · see citing works
“, (2017), in which MDD patients were randomized to either CBT, Escitalopram, or Duloxetine, found that positive FC of sgACC with left ventrolateral prefrontal cortex (vlPFC), left ventromedial prefrontal cortex (vmPFC) and dorsal midbrain was associated with remission with CBT [38].”
BackgroundHilbert, K., Kunas, S. L., Lueken, U., Kathmann, N., Fydrich, T., & Fehm, L. (2019) · Behaviour Research and Therapy · doi:10.1016/j.brat.2019.103530 · Cited by 54 · see citing works
Zhou, Z., Gao, Y., Bao, W., Liang, K., Cao, L., Tang, M., Li, H., Hu, X., Zhang, L., Sun, H., et al. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2024.105583 · Cited by 53 · see citing works
Arena, R. A., Ozemek, C., Laddu, D., Campbell, T. S., Rouleau, C. R., Standley, R. A., Bond, S., Abril, E. P., Hills, A. P., & Lavie, C. J. (2018) · Current Problems in Cardiology · doi:10.1016/j.cpcardiol.2018.06.001 · Cited by 51 · see citing works
Brown, E. C., Clark, D., Forkert, N. D., Molnar, C., Kiss, Z. H. T., & Ramasubbu, R. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-0745-5 · Cited by 51 · see citing works
Shu, Y., Kuang, L., Huang, Q., & He, L. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.07.038 · Cited by 50 · see citing works
Siegel, J. S., Palanca, B. J. A., Ances, B. M., Kharasch, E. D., Schweiger, J. A., Yingling, M. D., Snyder, A. Z., Nicol, G. E., Lenze, E. J., & Farber, N. B. (2021) · Psychopharmacology · doi:10.1007/s00213-021-05762-6 · Cited by 50 · see citing works
“FC between the sgACC and other DMN regions correlates with depression severity (Greicius et al. 2007; Connolly et al. 2013), and normalization of FC is linkedwith antidepressant response across diverse treatment modalities (Dunlop et al. 2017), including ketamine (Gärtner et al. 2019).”
BackgroundResultMa, X., Liu, J., Liu, T., Ma, L., Wang, W., Shi, S., Wang, Y., Gong, Q., & Wang, M. (2019) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2019.00089 · Cited by 50 · see citing works
“, PET revealed increased metabolism in the dorsolateral prefrontal cortex) (Goldapple et al., 2004; Dunlop et al., 2017).”
BackgroundChen, C., & Shan, W. (2019) · Psychiatry Research · doi:10.1016/j.psychres.2019.112595 · Cited by 51 · see citing works
Predicting escitalopram monotherapy response in depression: The role of anterior cingulate cortex
Tian, S., Sun, Y., Shao, J., Zhang, S., Mo, Z., Liu, X., Wang, Q., Wang, L., Zhao, P., Chattun, M. R., et al. (2019) · Human Brain Mapping · doi:10.1002/hbm.24872 · Cited by 49 · see citing works
“FC of subcallosal cingulate cortex could identify individuals' treatment outcome to cognitive behavioral therapy (CBT) and antidepressant medicine (Dunlop et al., 2017).”
BackgroundTherapeutic potential of ketamine for alcohol use disorder
Worrell, S. D., & Gould, T. J. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.05.006 · Cited by 47 · see citing works
Kappelmann, N., Rein, M., Fietz, J., Mayberg, H. S., Craighead, W. E., Dunlop, B. W., Nemeroff, C. B., Keller, M. B., Klein, D. N., Arnow, B. A., et al. (2020) · BMC Medicine · doi:10.1186/s12916-020-01623-9 · Cited by 49 · see citing works
“These cover a wide range of different approaches such as using big data sets and machine learning models to predict the MDD course from baseline self-reports [19, 20], explorative data-mining strategies in order to define decision trees for the treatment of depression [21], algorithmbased treatments associated with sh…”
BackgroundSelf-citationUnpacking Major Depressive Disorder: From Classification to Treatment Selection
Kennedy, S. H., & Ceniti, A. K. (2017) · The Canadian Journal of Psychiatry · doi:10.1177/0706743717748883 · Cited by 47 · see citing works
“In a separate example, using both positron emission tomography and fMRI, baseline moderators of response to either escitalopram or cognitive behavioural therapy (CBT) were identified: levels of glucose metabolism in the right anterior insula and functional connectivity of the subcallosal cingulate cortex were strong p…”
ResultResting State Functional Connectivity Biomarkers of Treatment Response in Mood Disorders: A Review
Taylor, J. J., Kurt, H. G., & Anand, A. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.565136 · Cited by 46 · see citing works
“By contrast, remission was negatively correlated with rostral/subgenual ACC RSFC to right precentral gyrus and right posterior putamen (71).”
BackgroundBrain-based mechanisms of late-life depression: Implications for novel interventions
Gunning, F. M., Oberlin, L. E., Schier, M. M., & Victoria, L. W. (2021) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2021.05.002 · Cited by 47 · see citing works
The ventromedial prefrontal cortex and emotion regulation: lost in translation?
Alexander, L., Wood, C. M., & Roberts, A. (2022) · The Journal of Physiology · doi:10.1113/jp282627 · Cited by 46 · see citing works
“…and activity change within it (Downar et al., 2014; Fox et al., 2012; Hiser & Koenigs, 2018; Salomons et al., 2014) as well as its inter-regional functional connectivity (Dunlop et al., 2017; Weigand et al., 2018) has been identified as a good predictor of response to a variety of treatments.”
BackgroundDudek, E. M., & Dodell‐Feder, D. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.12.020 · Cited by 44 · see citing works
Ahmed, A. T., Frye, M. A., Rush, A. J., Biernacka, J. M., Craighead, W. E., McDonald, W. M., Bobo, W. V., Riva‐Posse, P., Tye, S. J., Mayberg, H. S., et al. (2018) · Journal of Affective Disorders · doi:10.1016/j.jad.2018.05.005 · Cited by 44 · see citing works
Self-citationKelley, M. E., Dunlop, B. W., Nemeroff, C. B., Lori, A., Carrillo‐Roa, T., Binder, E. B., Kutner, M., Aponte‐Rivera, V., Craighead, W. E., & Mayberg, H. S. (2018) · Depression and Anxiety · doi:10.1002/da.22832 · Cited by 44 · see citing works
Self-citationWilliams, L. M., Carpenter, W. T., Carretta, C. M., Papanastasiou, E., & Vaidyanathan, U. (2023) · CNS Spectrums · doi:10.1017/s1092852923002420 · Cited by 43 · see citing works
Katayama, N., Nakagawa, A., Umeda, S., Terasawa, Y., Kurata, C., Tabuchi, H., Kikuchi, T., & Mimura, M. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101877 · Cited by 45 · see citing works
“These findings are consistent with the hypothesis that frontopolar cortical dysfunction plays a key role in the hopelessness that manifests in patients with MDD. Non-standard abbreviations MDD Major depressive disorder BA10 Brodmann area [BA] 10 GRID-HAMD GRID-Hamilton Depression Rating Scale BDI-II Beck Depression In…”
BackgroundInfluentialDang, W., Gao, Z., Sun, X., Li, R., Cai, Q., & Grebogi, C. (2020) · Nonlinear Dynamics · doi:10.1007/s11071-020-05665-9 · Cited by 43 · see citing works
Jamieson, A. J., Harrison, B. J., Razi, A., & Davey, C. G. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-021-01214-z · Cited by 41 · see citing works
“The rACC has also been shown to predict treatment response and remission [29, 35].”
ResultKlok, M., van Eijndhoven, P., Árgyelán, M., Schene, A. H., & Tendolkar, I. (2019) · BJPsych Open · doi:10.1192/bjo.2019.58 · Cited by 40 · see citing works
Identifying CBT non-response among OCD outpatients: A machine-learning approach
Hilbert, K., Jacobi, T., Kunas, S., Elsner, B., Reuter, B., Lueken, U., & Kathmann, N. (2020) · Psychotherapy Research · doi:10.1080/10503307.2020.1839140 · Cited by 40 · see citing works
Fu, C. H. Y., Antoniades, M., Erus, G., García, J., Yong Fan, A., Arnone, D., Arnott, S. R., Chen, T., Choi, K. S., Fatt, C. C., et al. (2024) · Nature Mental Health · doi:10.1038/s44220-023-00187-w · Cited by 37 · see citing works
“On the basis of functional connectivity measures, two to four MDD subtypes have been reported 11–15 .”
Self-citationNeuroimaging for precision medicine in psychiatry
Williams, L. M., & Whitfield, S. (2024) · Neuropsychopharmacology · doi:10.1038/s41386-024-01917-z · Cited by 39 · see citing works
Riva‐Posse, P., Inman, C. S., Choi, K. S., Crowell, A. L., Gross, R. E., Hamann, S. B., & Mayberg, H. S. (2019) · Brain stimulation · doi:10.1016/j.brs.2019.01.015 · Cited by 36 · see citing works
Self-citationBrain–computer interfaces for neuropsychiatric disorders
Oganesian, L. L., & Shanechi, M. M. (2024) · Nature Reviews Bioengineering · doi:10.1038/s44222-024-00177-2 · Cited by 39 · see citing works
“Besides, the biomarker might change over time owing to variations in the disorder stage and other stimulation-induced eff ects 31,35,41,42,95–97 .”
Trivedi, M. H., Fatt, C. C., Jha, M. K., Cooper, C. M., Trombello, J. M., Mason, B. L., Hughes, J. L., Gadad, B. S., Czysz, A. H., Toll, R. T., et al. (2019) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2019.12.004 · Cited by 37 · see citing works
Dynamic Resting-State Network Biomarkers of Antidepressant Treatment Response
Kaiser, R. H., Chase, H. W., Phillips, M. L., Deckersbach, T., Parsey, R. V., D, M. F. M., McGrath, P. J., Weissman, M. M., Oquendo, M. A., McInnis, M. G., et al. (2022) · Biological Psychiatry · doi:10.1016/j.biopsych.2022.03.020 · Cited by 37 · see citing works
Godlewska, B. R. (2018) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2018.12.010 · Cited by 36 · see citing works
Seeberg, I., Kjærstad, H. L., & Miskowiak, K. W. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00337 · Cited by 36 · see citing works
“In keeping with this, one study of patients undergoing either pharmacotherapy with fluoxetine or CBT found that clinical remission to pharmacotherapy was predicted by greater GM volume density in the right rostral ACC, left PCC, whereas no prediction was found for CBT (68).”
BackgroundMethodInfluentialCristea, I. A., Karyotaki, E., Hollon, S. D., Cuijpers, P., & Gentili, C. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.03.022 · Cited by 34 · see citing works
Dunlop, K., Grosenick, L., Downar, J. H., Vila‐Rodriguez, F., Gunning, F. M., Daskalakis, Z. J., Blumberger, D. M., & Liston, C. M. (2024) · Biological Psychiatry · doi:10.1016/j.biopsych.2024.01.012 · Cited by 35 · see citing works
Ranasinghe, P. H. K. I. S., & Mapa, M. S. T. (2024) · Exploration of Medicine · doi:10.37349/emed.2024.00256 · Cited by 37 · see citing works
Hahn, A., Lanzenberger, R. R., & Kasper, S. F. (2018) · The International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyy100 · Cited by 37 · see citing works
Tymofiyeva, O., Yuan, J. P., Huang, C., Connolly, C. G., Blom, E. H., Xu, D., & Yang, T. T. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101914 · Cited by 34 · see citing works
Fulong, X., Spruyt, K., Lu, C., Dianjiang, Z., Jun, Z., & Fang, H. (2020) · SLEEP · doi:10.1093/sleep/zsaa018 · Cited by 35 · see citing works
Chang, K.-Y., Tik, M., Mizutani-Tiebel, Y., Schuler, A., Taylor, P. C. J., Campana, M., Vogelmann, U., Huber, B., Dechantsreiter, E., Thielscher, A., et al. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120596 · Cited by 34 · see citing works
“To analyze the change of BOLD activation over the course of an iTBS session, we conducted an investigation wherein the complete 20 iTBS trains were divided into four blocks, each consisting of 5 trains of iTBS (equivalent to 150 stimuli).”
Wang, Y., Wang, C., Zhou, J., Chen, X., Liu, R., Zhang, Z., Feng, Y., Feng, L., Liu, J., Zhou, Y., et al. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-03117-1 · Cited by 35 · see citing works
“In a study using fMRI, Dunlop et al. [18] discovered that the rsFC of the sgACC was differentially associated with treatment outcomes for cognitive behavior therapy and antidepressant medication [18].”
Resting State Functional Connectivity and Outcomes of Psychotherapies for Late-Life Depression
Solomonov, N., Victoria, L. W., Dunlop, K., Respino, M., Hoptman, M. J., Zilcha‐Mano, S., Oberlin, L. E., Liston, C. M., Areán, P. A., Gunning, F. M., et al. (2020) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2020.04.008 · Cited by 34 · see citing works
Hilland, E., Landrø, N. I., Harmer, C. J., Browning, M. D., Maglanoc, L. A., & Jonassen, R. (2019) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.180118 · Cited by 34 · see citing works
Engelmann, J. B., Berns, G. S., & Dunlop, B. W. (2017) · Psychological Medicine · doi:10.1017/s0033291717001428 · Cited by 33 · see citing works
“Furthermore, resting state metabolism of the AI (McGrath et al. 2013; Dunlop et al. 2015), and its functional connectivity with the subcallosal cingulate cortex (Dunlop et al. 2017), has been identified as a potential biomarker for treatment selection in patients with MDD.”
BackgroundSelf-citationJaeckle, T., Williams, S., Barker, G. J., Basilio, R., Carr, E., Goldsmith, K., Colasanti, A., Giampietro, V., Cleare, A. J., Young, A. H., et al. (2021) · Psychological Medicine · doi:10.1017/s0033291721004797 · Cited by 36 · see citing works
“This work builds on extensive evidence for the pathophysiological importance of SC networks in MDD (Drevets & Savitz, 2008; Dunlop et al., 2017; Price & Drevets, 2010; Ressler & Mayberg, 2007; Siegle, Carter, & Thase, 2006).”
Paolini, M., Harrington, Y. A., Colombo, F., Bettonagli, V., Poletti, S., Carminati, M., Colombo, C., Benedetti, F., & Zanardi, R. (2023) · Journal of Psychopharmacology · doi:10.1177/02698811231190859 · Cited by 31 · see citing works
“…regions: lower rs-FC between ACC, ventro-medial prefrontal cortex and posterior cingulate cortex has been associated with better treatment response (Dunlop et al., 2017; Goldstein-Piekarski et al., 2018), as well as higher connectivity with right dorsolateral prefrontal cortex (Straub et al.,…”
BackgroundWu, H., Liu, R., Zhou, J., Feng, L., Wang, Y., Chen, X., Zhang, Z., Cui, J., Zhou, Y., & Wang, G. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02152-0 · Cited by 30 · see citing works
“An accuracy of 70–89% was achieved by using fMRI to predict whether MDD patients were in remission after 12 weeks of antidepressant treatment [14, 15, 18].”
Circuit based anti-correlation, attention orienting, and major depression
Fossati, P. (2019) · CNS Spectrums · doi:10.1017/s1092852918001402 · Cited by 29 · see citing works
Blame-rebalance fMRI neurofeedback in major depressive disorder: A randomised proof-of-concept trial
Zahn, R., Weingartner, J. H., Basílio, R., Bado, P., Mattos, P., Sato, J. R., de Oliveira‐Souza, R., Fontenelle, L. F., Young, A. H., & Moll, J. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101992 · Cited by 29 · see citing works
Zou, L.-W., Wu, X.-Y., Tao, S.-M., Yang, Y.-J., Zhang, Q., Hong, X., Xie, Y., Li, T.-T., Zheng, S.-S., & Tao, F. (2021) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsab016 · Cited by 27 · see citing works
“In addition, ACC was regarded as a promising predictor for antidepression response from several studies (Dunlop et al., 2017; Godlewska et al., 2018; Wolke et al., 2019).”
Result
- Authors
- Dunlop, B. W., Rajendra, J. K., Craighead, W. E., Kelley, M. E., McGrath, C. L., Choi, K. S., Kinkead, B., Nemeroff, C. B., & Mayberg, H. S.
- Affiliations
- Harvard University (US)
- ORCID
- Venue
- American Journal of Psychiatry
- Published
- 2017-06-01
- Volume
- 174
- Issue
- 6
- Pages
- 533-545
- ISSN
- 0002-953X (ISSN-L)
- 1535-7228
- PMC
- PMC5453828
- OpenAlex
- W2600118519
- Cited by
- 342
- References
- 80
- Citations by year
- 2026: 20 · 2025: 32 · 2024: 30 · 2023: 30 · 2022: 31 · 2021: 47 · 2020: 55 · 2019: 50 · 2018: 28 · 2017: 19
- FWCI
- 23.85
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5r01mh080880-05, UL1TR000454)
- National Institute of Mental Health (K23MH086690, R01-MH080880, P50MH077083)
- National Center for Research Resources (UL1RR025008, M01RR000039)
- National Center for Advancing Translational Sciences
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- major depressive disorder, resting-state functional connectivity, cognitive behavioral therapy, antidepressants, treatment response prediction, remission, treatment failure, neuroimaging biomarkers, ventromedial prefrontal cortex, dorsal midbrain, anterior insula, ventrolateral prefrontal cortex, individualized treatment selection
- MeSH terms
- Duloxetine Hydrochloride, Adolescent, Adult, Aged, Antidepressive Agents, Depressive Disorder, Major, Major Depressive Disorder, Dominance, Cerebral, Female, Gyrus Cinguli, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Nerve Net, Psychiatric Status Rating Scales, Citalopram, Cognitive Behavioral Therapy, Outcome Assessment, Health Care, Prefrontal Cortex, Young Adult
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