Skip to main content Accessibility help
×
Hostname: page-component-848d4c4894-nr4z6 Total loading time: 0 Render date: 2024-05-08T04:27:24.630Z Has data issue: false hasContentIssue false

Chapter 19 - Brain Imaging and the Mechanisms of Antidepressant Action

from Section 5 - Therapeutic Applications of Neuroimaging in Mood Disorders

Published online by Cambridge University Press:  12 January 2021

Sudhakar Selvaraj
Affiliation:
UTHealth School of Medicine, USA
Paolo Brambilla
Affiliation:
Università degli Studi di Milano
Jair C. Soares
Affiliation:
UT Harris County Psychiatric Center, USA
Get access

Summary

The history of pharmacological treatments for depression began in the 1950s, with the serendipitous discovery of the antidepressant potential of drugs like the tricyclic antidepressant, imipramine. Since then, many new, safer, and better tolerated, antidepressant drugs have appeared on the market (1), and now depression can be treated widely in primary care. However, finding a treatment effective for an individual patient is not a trivial task, with only around 30% of patients responding to their first antidepressant (AD) medication, most requiring multiple changes, and about one-third not responding at all (2).

Type
Chapter
Information
Mood Disorders
Brain Imaging and Therapeutic Implications
, pp. 248 - 260
Publisher: Cambridge University Press
Print publication year: 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Cipriani, A, Furukawa, TA, Salanti, G, et al. Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. Lancet 2018; 391: 13571366.CrossRefGoogle ScholarPubMed
Warden, D, Rush, AJ, Trivedi, MH, et al. The STAR*D Project results: a comprehensive review of findings. Curr Psychiatry Rep 2007; 9: 449459.Google Scholar
Ferrari, AJ, Charlson, FJ, Norman, RE, et al. Burden of depressive disorders by country, sex, age,and year: findings from the global burden of disease study. PLoS Med 2013; 10: e1001547.CrossRefGoogle ScholarPubMed
Mayberg, HS. Limbic-cortical dysregulation: a proposed model of depression. Journal of Neuropsychiatry & Clinical Neurosciences 1997; 9: 471481.Google ScholarPubMed
Drevets, WC. Neuroimaging and neuropathological studies of depression: implications for the cognitive–emotional features of mood disorders. Current Opinion in Neurobiology 2001; 11: 240249.Google Scholar
Mayberg, HS. Modulating dysfunctional limbic-cortical circuits in depression: towards development of brain-based algorithms for diagnosis and optimised treatment. British Medical Bulletin 2003; 65: 193207.Google Scholar
Roiser, JP, Elliott, R, Sahakian, BJ. Cognitive mechanisms of treatment in depression. Neuropsychopharmacology 2012; 37: 117136.Google Scholar
Peters, SK, Dunlop, K, Downar, J. Cortico-striatal-thalamic loop circuits of the salience network: a central pathway in psychiatric disease and treatment. Front Syst Neurosci 2016; 27: 104.Google Scholar
Fettes, P, Schulze, L, Downar, J. Cortico-striatal-thalamic loop circuits of the orbitofrontal cortex: promising therapeutic targets in psychiatric illness. Front Syst Neurosci 2017; 27: 25.Google Scholar
Brakowski, J, Spinelli, S, Dörig, N, et al. Resting state brain network function in major depression – Depression symptomatology, antidepressant treatment effects, future research. J Psychiatr Res 2017; 92: 147159.CrossRefGoogle ScholarPubMed
Whitfield-Gabrieli, S, Ford, JM. Default mode network activity and connectivity in psychopathology. Annu Rev Clin Psychol 2015; 8: 4976.Google Scholar
Wang, X, Öngür, D, Auerbach, RP, et al. Cognitive vulnerability to major depression: view from the intrinsic network and cross-network Interactions. Harv Rev Psychiatry 2016; 24: 188201.Google Scholar
Graham, J, Salimi-Khorshidi, G, Hagan, C, et al. Meta-analytic evidence for neuroimaging models of depression: state or trait? J Affect Disord 2013; 151: 423431.CrossRefGoogle ScholarPubMed
Sheline, YI, Barch, DM, Donnelly, JM, et al. Increased amygdala response to masked emotional faces in depressed subjects resolves with antidepressant treatment: an fMRI study. Biol Psychiatry 2001; 50: 651658.Google Scholar
Anand, A, Li, Y, Wang, Y, et al. Antidepressant effect on connectivity of the mood-regulating circuit: an fMRI study. Neuropsychopharmacology 2005; 30: 13341344.Google Scholar
Anand, A, Li, Y, Wang, Y, et al. Reciprocal effects of antidepressant treatment on activity and connectivity of the mood regulating circuit: an fMRI study. J Neuropsychiatry Clin Neurosci 2007; 19: 274282.Google Scholar
Fales, CL, Barch, DM, Rundle, MM, et al. Antidepressant treatment normalizes hypoactivity in dorsolateral prefrontal cortex during emotional interference processing in major depression. J Affect Disord 2009; 112: 206211.CrossRefGoogle ScholarPubMed
Victor, TA, Furey, ML, Fromm, SJ, et al. Changes in the neural correlates of implicit emotional face processing during antidepressant treatment in major depressive disorder. Int J Neuropsychopharmacol 2013; 16: 21952208.CrossRefGoogle ScholarPubMed
Williams, LM, Korgaonkar, MS, Song, YC, et al. Amygdala reactivity to emotional faces in the prediction of general and medication-specific responses to antidepressant treatment in the randomized iSPOT-D trial. Neuropsychopharmacology 2015; 40: 23982408.CrossRefGoogle ScholarPubMed
Fu, CH, Williams, SC, Cleare, AJ, et al. Attenuation of the neural response to sad faces in major depression by antidepressant treatment: a prospective, event-related functional magnetic resonance imaging study. Arch Gen Psychiatry 2004; 61: 877889.CrossRefGoogle ScholarPubMed
Fu, CH, Williams, SC, Brammer, MJ, et al. Neural responses to happy facial expressions in major depression following antidepressant treatment. Am J Psychiatry 2007; 164: 599607.CrossRefGoogle ScholarPubMed
Walsh, ND, Williams, SC, Brammer, MJ, et al. A longitudinal functional magnetic resonance imaging study of verbal working memory in depression after antidepressant therapy. Biol Psychiatry 2007; 62: 12361243.Google Scholar
Chen, CH, Suckling, J, Ooi, C, et al. Functional coupling of the amygdala in depressed patients treated with antidepressant medication. Neuropsychopharmacology 2008; 33: 19091918.Google Scholar
Wang, Y, Xu, C, Cao, X, et al. Effects of an antidepressant on neural correlates of emotional processing in patients with major depression. Neurosci Lett 2012; 527: 5559.Google Scholar
Tao, R, Calley, CS, Hart, J, et al. Brain activity in adolescent major depressive disorder before and after fluoxetine treatment. Am J Psychiatr 2012; 169: 381388.CrossRefGoogle ScholarPubMed
Heller, AS, Johnstone, T, Light, SN, et al. Relationships between changes in sustained fronto-striatal connectivity and positive affect in major depression resulting from antidepressant treatment. Am J Psychiatr 2013; 170: 197206.Google Scholar
Wagner, G, Koch, K, Schachtzabel, C, et al. Differential effects of serotonergic and noradrenergic antidepressants on brain activity during a cognitive control task and neurofunctional prediction of treatment outcome in patients with depression. J Psychiat Neurosci 2010; 35: 247257.Google Scholar
Arnone, D, McKie, S, Elliott, R, et al. Increased amygdala responses to sad but not fearful faces in major depression: relation to mood state and pharmacological treatment. Am J Psychiatr 2012, 169: 841850.CrossRefGoogle Scholar
Jiang, W, Yin, Z, Pang, Y, et al. Brain functional changes in facial expression recognition in patients with major depressive disorder before and after antidepressant treatment: A functional magnetic resonance imaging study. Neural Regen Res 2012; 7: 11511157.Google ScholarPubMed
Stoy, M, Schlagenhauf, F, Sterzer, P, et al. Hyporeactivity of ventral striatum towards incentive stimuli in unmedicated depressed patients normalizes after treatment with escitalopram. J Psychopharmacol 2012; 26: 677688.CrossRefGoogle ScholarPubMed
Godlewska, BR, Norbury, R, Cowen, PJ, et al. Short-term SSRI treatment normalizes amygdala hyperactivity in depressed patients. Psych Medicine 2012; 42: 26092617.CrossRefGoogle ScholarPubMed
Rosenblau, G, Sterzer, P, Stoy, M, et al. Functional neuroanatomy of emotion processing in major depressive disorder is altered after successful antidepressant therapy. J Psychopharmacol 2012; 26: 14241433.CrossRefGoogle ScholarPubMed
Miller, JM, Schneck, N, Siegle, GJ, et al. fMRI response to negative words and SSRI treatment outcome in major depressive disorder: a preliminary study. Psychiat Res 2013, 214: 296305.Google Scholar
Wang, L, Li, K, Zhang, Q, et al. Short-term effects of escitalopram on regional brain function in first-episode drug-naive patients with major depressive disorder assessed by resting-state functional magnetic resonance imaging. Psychol Med 2014; 44: 14171426.CrossRefGoogle ScholarPubMed
Ruhe, HG, Booij, J, Veltman, DJ, et al. Successful pharmacologic treatment of major depressive disorder attenuates amygdala activation to negative facial expressions: a functional magnetic resonance imaging study. J Clin Psychiat 2012; 73: 451459.Google Scholar
Davidson, RJ, Irwin, W, Anderle, MJ, et al. The neural substrates of affective processing in depressed patients treated with venlafaxine. Am J Psychiatr 2003, 160: 6475.Google Scholar
Schaefer, KM Putnam, HS, Benca, RM, et al. Event related functional magnetic resonance imaging measures of neural activity to positive social stimuli in pre- and post-treatment depression. Biol Psychiat 2006, 60: 974986.CrossRefGoogle ScholarPubMed
Benedetti, F, Radaelli, D, Bernasconi, A, et al. Changes in medial prefrontal cortex neural responses parallel successful antidepressant combination of venlafaxine and light therapy. Arch Ital Biol 2009; 147: 8393.Google Scholar
Lisiecka, D, Meisenzahl, E, Scheuerecker, J, et al. Neural correlates of treatment outcome in major depression. Int J Neuropsychoph 2011; 14: 521534.Google Scholar
Samson, AC, Meisenzahl, E, Scheuerecker, J, et al. Brain activation predicts treatment improvement in patients with major depressive disorder. J Psychiat Res 2011; 45: 12141222.Google ScholarPubMed
Gyurak, A, Patenaude, B, Korgaonkar, MS, et al. Frontoparietal activation during response inhibition predicts remission to antidepressants in patients with major depression. Biol Psychiatry 2016; 79: 274281.Google Scholar
Rzepa, E, McCabe, C. Anhedonia and depression severity dissociated by dmPFC resting-state functional connectivity in adolescents. J Psychopharmacol 2018; 32: 10671074.CrossRefGoogle ScholarPubMed
Harmer, CJ, Bhagwagar, Z, Perrett, DI, et al. Acute SSRI administration affects the processing of social cues in healthy volunteers. Neuropsychopharmacology 2003; 28: 148152.Google Scholar
Scheidegger, M, Henning, A, Walter, M, et al. Effects of ketamine on cognition-emotion interaction in the brain. Neuroimage 2016; 124: 815.CrossRefGoogle ScholarPubMed
Selvaraj, S, Walker, C, Arnone, D, et al. Effect of citalopram on emotion processing in humans: a combined 5-HT1A [11 C]CUMI-101 PET and functional MRI study. Neuropsychopharmacology 2018; 43: 655664.Google Scholar
Ma, Y. Neuropsychological mechanism underlying antidepressant effect: a systematic metaanalysis. Mol Psychiatry 2015; 20: 311–19.CrossRefGoogle Scholar
Wessa, M, Lois, G. Brain functional effects of psychopharmacological treatment in major depression: a focus on neural circuitry of affective processing. Curr Neuropharmacol 2015; 13: 466479.Google Scholar
Fu, CH, Steiner, H, Costafreda, SG. Predictive neural biomarkers of clinical response in depression: a meta-analysis of functional and structural neuroimaging studies of pharmacological and psychological therapies. Neurobiol Dis 2013; 52: 7583.Google Scholar
Etkin, A, Egner, T,. Kalisch, R. Emotional processing in anterior cingulate and medial prefrontal cortex. Trends Cogn Sci 2011; 15: 8593.CrossRefGoogle ScholarPubMed
Pizzagalli, DA. Frontocingulate dysfunction in depression: toward biomarkers of treatment response. Neuropsychopharmacology 2011; 36: 183206.Google Scholar
Arnone, D. Functional MRI findings, pharmacological treatment in major depression and clinical response. Prog Neuropsychopharmacol Biol Psychiatry 2019; 91: 2837.Google Scholar
Downey, D, Dutta, A, McKie, S, et al. Comparing the actions of lanicemine and ketamine in depression: key role of the anterior cingulate. Eur Neuropsychopharmacol. 2016; 26: 9941003.Google Scholar
McGrath, CL, Kelley, ME, Holtzheimer, PE III, et al. Toward a neuroimaging treatment selection biomarker for major depressive disorder. JAMA Psychiatry 2013; 70: 821829.Google Scholar
Keedwell, P, Drapier, D, Surguladze, S, et al. Neural markers of symptomatic improvement during antidepressant therapy in severe depression: subgenual cingulate and visual cortical responses to sad, but not happy, facial stimuli are correlated with changes in symptom score. J Psychopharmacol 2009; 23: 775788.Google Scholar
Boku, S, Nakagawa, S, Toda, H, et al. Neural basis of major depressive disorder: Beyond monoamine hypothesis. Psychiatry Clin Neurosci 2018; 72: 312.Google Scholar
Dusi, N, Barlati, S, Vita, A, et al. Brain structural effects of antidepressant treatment in major depression. Curr Neuropharmacol 2015; 13: 458465.CrossRefGoogle ScholarPubMed
Gunning, FM, Cheng, J, Murphy, CF, et al. Anterior cingulate cortical volumes and treatment remission of geriatric depression. Int J Geriatr Psychiatry 2009; 24: 829836.Google Scholar
Korgaonkar, MS, Williams, LM, Song, YJ, et al. Diffusion tensor imaging predictors of treatment outcomes in major depressive disorder. Br J Psychiatry 2014; 205: 321328.Google Scholar
Korgaonkar, MS, Rekshan, W, Gordon, E, et al. Magnetic resonance imaging measures of brain structure to predict antidepressant treatment outcome in major depressive disorder. E Bio Medicine 2014; 2: 3745.Google Scholar
Dichter, GS, Gibbs, D, Smoski, MJ. A systematic review of relations between resting-state functional-MRI and treatment response in major depressive disorder. J Affect Disord 2015; 172: 817.Google Scholar
Yang, R, Zhang, H, Wu, X, et al. Hypothalamus-anchored resting brain network changes before and after sertraline treatment in major depression. Biomed Res Int 2014; 2014: 915026.Google ScholarPubMed
Posner, J, Hellerstein, DJ, Gat, I, et al. Antidepressants normalize the default mode network in patients with dysthymia. JAMA Psychiatry 2013; 70: 373382.Google Scholar
Li, B, Liu, L, Friston, KJ, et al. A treatment-resistant default mode subnetwork in major depression. Biol Psychiatry 2013; 74: 4854.Google Scholar
Wagner, G, de la Cruz, F, Köhler, S, et al. Treatment associated changes of functional connectivity of midbrain/brainstem nuclei in major depressive disorder. Sci Rep 2017; 7: 8675.Google Scholar
de Kwaasteniet, B, Ruhe, E, Caan, M, et al. Relation between structural and functional connectivity in major depressive disorder. Biol Psychiatry 2013; 74: 4047.Google Scholar
Guo, WB, Liu, F, Chen, JD, et al. Abnormal neural activity of brain regions in treatment-resistant and treatment-sensitive major depressive disorder: a resting-state fMRI study. J Psychiatr Res 2012; 46: 13661373.Google Scholar
Guo, W, Liu, F, Xue, Z, et al. Abnormal resting-state cerebellar-cerebral functional connectivity in treatment-resistant depression and treatment sensitive depression. Prog Neuropsychopharmacol Biol Psychiatry 2013; 44: 5157.Google Scholar
Maltbie, EA, Kaundinya, GS, Howell, LL. Ketamine and pharmacological imaging: use of functional magnetic resonance imaging to evaluate mechanisms of action. Behav Pharmacol 2017; 28: 610622.CrossRefGoogle ScholarPubMed
Abdallah, CG, Averill, LA, Collins, KA, et al. Ketamine treatment and global brain connectivity in major depression. Neuropsychopharmacology 2017; 42:12101219.CrossRefGoogle ScholarPubMed
Gopinath, K, Maltbie, E, Urushino, N, et al. Ketamine-induced changes in connectivity of functional brain networks in awake female nonhuman primates: a translational functional imaging model. Psychopharmacology (Berl) 2016; 233: 36733684.CrossRefGoogle ScholarPubMed
da Cunha-Bang, S, Ettrup, A, Mc Mahon, B, et al. Measuring endogenous changes in serotonergic neurotransmission with [11 C]Cimbi-36 positron emission tomography in humans. Transl Psychiatry 2019; 9: 134.Google Scholar
Miller, JM, Hesselgrave, N, Ogden, RT, et al. Brain serotonin 1 A receptor binding as a predictor of treatment outcome in major depressive disorder. Biol Psychiatry 2013, 15; 74: 760767.Google Scholar
Gray, NA, Milak, MS, DeLorenzo, C, et al. Antidepressant treatment reduces serotonin-1A autoreceptor binding in major depressive disorder. Biol Psychiatry 2013; 74: 2631.Google Scholar
Spies, M, Knudsen, GM, Lanzenberger, R, et al. The serotonin transporter in psychiatric disorders: insights from PET imaging. Lancet Psychiatry 2015; 2: 743755.CrossRefGoogle ScholarPubMed
Miller, JM, Oquendo, MA, Ogden, RT, et al. Serotonin transporter binding as a possible predictor of one-year remission in major depressive disorder. J Psychiatr Res 2008; 42: 11371144.Google Scholar
Lanzenberger, R, Kranz, GS, Haeusler, D, et al. Prediction of SSRI treatment response in major depression based on serotonin transporter interplay between median raphe nucleus and projection areas. Neuroimage 2012; 63: 874–871.CrossRefGoogle ScholarPubMed
Yeh, YW, Ho, PS, Kuo, SC, et al. 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-[18 F]-ADAM. Int J Neuropsychopharmacol. 2015 Jan 7;18(7):pyu120.Google Scholar
James, GM, Baldinger-Melich, P, Philippe, C, et al. Effects of selective serotonin reuptake inhibitors on interregional relation of serotonin transporter availability in major depression. Front Hum Neurosci 2017; 11: 48.Google Scholar
Arakawa, R, Stenkrona, P, Takano, A, et al. Venlafaxine ER blocks the norepinephrine transporter in the brain of patients with major depressive disorder: a PET study using [18 F]FMeNER-D2. Int J Neuropsychopharmacol 2019; 22: 278285.Google Scholar
Moriguchi, S, Takano, H, Kimura, Y, et al. Occupancy of norepinephrine transporter by duloxetine in human brains measured by positron emission tomography with (S,S)-[18 F]FMeNER-D2. Int J Neuropsychopharmacol 2017; 20: 957962.Google Scholar
Pringle, A, Harmer, CJ. The effects of drugs on human models of emotional processing: an account of antidepressant drug treatment. Dialogues Clin Neurosci 2015; 17: 477487.Google Scholar
Godlewska, BR. Cognitive neuropsychological theory: reconciliation of psychological and biological approaches for depression. Pharmacol Ther 2018; pii: S0163–7258(18)3023230238.Google Scholar
Komulainen, E, Heikkilä, R, Nummenmaa, L, et al. Short-term escitalopram treatment normalizes aberrant self-referential processing in major depressive disorder. J Affect Disord 2018; 236: 222229.Google Scholar
Godlewska, BR, Browning, M, Norbury, R, et al. Early changes in emotional processing as a marker of clinical response to SSRI treatment in depression. Transl Psych 2016; 6: e957.Google Scholar
Shiroma, PR, Thuras, P, Johns, B, et al. Emotion recognition processing as early predictor of response to 8-week citalopram treatment in late-life depression. Int J Geriatr Psychiatry 2014; 29: 11321139.Google Scholar
MacLeod, C, Rutherford, E, Campbell, L, et al. Selective attention and emotional vulnerability: assessing the causal basis of their association through the experimental manipulation of attentional bias. J Abnorm Psychol 2002; 111: 107123.Google Scholar
Miller, S, McTeague, LM, Gyurak, A, et al. Cognition-childhood maltreatment interactions in the prediction of antidepressant outcomes in major depressive disorder patients: results from the iSPOT-D trial. Depress Anxiety 2015; 32: 594604.CrossRefGoogle ScholarPubMed
Holmes, EA, Ghaderi, A, Harmer, CJ, et al. Commission on psychological treatments research in tomorrow’s science. The Lancet Psychiatry 2018; 5: 237286.Google Scholar
Browning, M, Reid, C, Cowen, PJ, Goodwin, GM, Harmer, CJ. A single dose of citalopram increases fear recognition in healthy subjects. J Psychopharmacol 2007; 21: 684690.Google Scholar
Jonassen, R, Chelnokova, O, Harmer, C, et al. A single dose of antidepressant alters eye-gaze patterns across face stimuli in healthy women. Psychopharmacology 2014; 232: 953958.Google Scholar
Di Simplicio, M, Norbury, R, Reinecke, A, et al. Paradoxical effects of short-term antidepressant treatment in fMRI emotional processing models in volunteers with high neuroticism. Psychol Med 2014; 44: 241252.Google Scholar
McArthur, RA. Aligning physiology with psychology: translational neuroscience in neuropsychiatric drug discovery. Neuroscience & Biobehavioral Reviews 2017; 76: 421.CrossRefGoogle ScholarPubMed
Insel, TR. The NIMH Research Domain Criteria (RDoC) Project: precision medicine for psychiatry. Am J Psychiatry 2014; 171: 395397.Google Scholar
Drysdale, AT, Grosenick, L, Downar, J, et al. Resting-state Connectivity Biomarkers Define Neurophysiological Subtypes of Depression Nat Med. 2017 Jan;23(1):28–38.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×