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Prediction of the Therapeutic Response in Depression Based on Neuro-computational Modeling Assessment of Motivation (STRATIDEP)

Primary Purpose

Major Depressive Disorder

Status
Not yet recruiting
Phase
Not Applicable
Locations
France
Study Type
Interventional
Intervention
escitalopram
vortioxetine
Sponsored by
Centre Hospitalier St Anne
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional treatment trial for Major Depressive Disorder

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesAccepts Healthy Volunteers

Patients with major depressive disorder Inclusion Criteria: Meeting DSM-5 criteria for major depressive disorder (single or recurrent episodes) With a MADRS score >= 24 For which a new line of treatment is needed No previous line of antidepressant for this episode or wash-out long-enough to avoid carry-over effects Valid health care insurance Exclusion Criteria: Treatment-resistant depression (defined as insufficient response despite at least 2 trials of antidepressant prescribed at adequate dose and duration) Subjects with a trial of escitalopram and/or vortioxetine for the current episode, or with contra-indication to one of these two drugs Subjects with a diagnostic of persistent depressive disorder, bipolar disorder or schizophrenia, neurodeveloppemental disorder, unremitted substance abuse disorder other than tobacco, personality disorder severe enough to compromise the follow-up (based on investigator's appreciation). Subject with a history of neurological disorder: parkinson's disease, dementia Contraindications to MRI scanning: pregnancy, claustrophobia, metallic implants Pregnant or breastfeeding women involuntary hospitalisation and legal protection measures Healthy volunteers Inclusion Criteria: - Valid health care insurance Exclusion Criteria: Subjects with a diagnostic of persistent depressive disorder, bipolar disorder or schizophrenia, neurodeveloppemental disorder, unremitted substance abuse disorder other than tobacco, personality disorder severe enough to compromise the follow-up (based on investigator's appreciation). Subject with a history of neurological disorder: parkinson's disease, dementia Contraindications to MRI scanning: pregnancy, claustrophobia, metallic implants Pregnant or breastfeeding women

Sites / Locations

  • Groupe hospitalo-universitaire de Grenoble Alpes
  • Centre hospitalier Universitaire de Saint-Etienne
  • Centre hospitalier Universitaire de Lille
  • Groupe hospitalo-universitaire Assistance Publique, hôpital Pitié Salpêtrière - Hôpitaux de Paris Sorbonne Université
  • - Groupe hospitalo-universitaire Paris Psychiatrie et Neurosciences

Arms of the Study

Arm 1

Arm 2

Arm Type

Other

Other

Arm Label

escitalopram strategy

vortioxetine strategy

Arm Description

The strategy will not be modified for a period of 4 weeks. Dosage adjustment and co-prescriptions will be at the discretion of the refeering psychiatrist.

The strategy will not be modified for a period of 4 weeks. Dosage adjustment and co-prescriptions will be at the discretion of the refeering psychiatrist.

Outcomes

Primary Outcome Measures

Prediction of the therapeutic response (MADRS score) 28 days after the introduction of the antidepressant strategy (V3) based on the early changes (differences between V1 and V2) of the computational phenotype of depressed patients.
The therapeutic response will be measured with the Montgomery-Asberg Depression Rating Scale (MADRS). The MADRS is a 10- item scale widely used in depression research to assess the severity of depression. Response will be defined by a score divided by 2 compared to baseline MADRS score, while remission will be defined by a score < 7 (symptom absent) 28 days after the initiation of the antidepressant strategy. The "computational phenotype" is the outcome of the computationnal analysis of behavior. It is expressed in abstract unit. The change in computationnal phenotype between V1 and V2 will be entered in logistic regression aiming to predict clinical response at 28 days, measured with the MADRS score.

Secondary Outcome Measures

Prediction of the therapeutic response (MADRS score) 28 days after the introduction of the antidepressant strategy (V3) based on the early changes (differences between V1 and V2) of the neuro-computational phenotype of depressed patients
Same than outcome 1 but using brain imaging on top of behavior (neurocomputational modeling) to predict clinical response.
Prediction of the therapeutic response (MADRS score) 28 days after the introduction of the antidepressant strategy (V3) based on the initial (baseline state- V1) neuro-computational phenotype of depressed patients
Same than Outcome 2 but using only V1 instead of the change between V1 and V2 to predict clinical response.
Prediction of long-term remission (V4) based on the early changes (differences between V1 and V2) of the neuro-computationnal phenotype of depressed patients
Same than Outcome 2 but to predict clinical remission at V4 instead of clinical response at V3.
Prediction functional remission (V5) based on the early changes (differences between V1 and V2) of the neuro-computationnal phenotype of depressed patients
Same than Outcome 2 but to predict functional remission at V5 instead of clinical response at V3.
Prediction of relapse at one year (V5) based on the computationnal phenotype of remitted patients at 6 months (V4).
Same than Outcome 1 but using computational phenotype at V4 to predict predict functional remission at V5.
Description of the motivational deficit of depressed patients at baseline (V1).
Comparison of the computational phenotype of patients with depression and healthy volunteers at V1.
Description of the neural correlates of motivation deficits of depressed patients at baseline (V1).
Comparison of the brain functional statistical maps of patient with depression and healthy volunteers at V1.
Description of the evolution of motivation deficit of depressed patients after one week of antidepressant treatment
Comparison of the computational phenotype of patients with depression at V1 and V2.
Description of the evolution of the neural correlates of motivation deficits after one week of antidepressant treatment
Comparison of the brain functional statistical maps of patient with depression at V1 and V2.
Description of the evolution of motivation deficit of depressed patients at 6 months
Comparison of the computational phenotype of patients with depression at V1 and V4.
Description of the evolution of the structural neural correlates of depression after 6 months of treatment
Comparison of the structural brain imaging of patients with depression at V1 and V4.
Description of the evolution of the functional neural correlates of depression after 6 months of treatment
Comparison of the function brain imaging (ASL) of patients with depression at V1 and V4.
Construction of a bio-bank
Serum tubes will be drowned along the study (V1, V2, V3 and V4 for patients - V1 for healthy volunteers) prepared and stored.

Full Information

First Posted
November 15, 2022
Last Updated
May 10, 2023
Sponsor
Centre Hospitalier St Anne
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1. Study Identification

Unique Protocol Identification Number
NCT05866575
Brief Title
Prediction of the Therapeutic Response in Depression Based on Neuro-computational Modeling Assessment of Motivation
Acronym
STRATIDEP
Official Title
Prediction of the Therapeutic Response in Depression Based on an Early Neuro-computational Modeling Assessment of Motivation
Study Type
Interventional

2. Study Status

Record Verification Date
May 2022
Overall Recruitment Status
Not yet recruiting
Study Start Date
June 1, 2023 (Anticipated)
Primary Completion Date
November 1, 2025 (Anticipated)
Study Completion Date
December 31, 2026 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Centre Hospitalier St Anne

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No

5. Study Description

Brief Summary
This study aims to better understand the mechanisms of action of antidepressants, but also the neural correlates of motivation deficits. One hundred patients with a moderate to severe major depressive episode will be enrolled in this prospective multicenter study. The objective will be to predict the therapeutic response to two first-line antidepressants on the basis of an early neurocomputational assessment of motivation. Antidepressant treatment will be administered as monotherapy after randomization between two drugs: escitalopram and vortioxetine. Patients will undergo six visits and follow-up for one year. The investigators will combine computer modeling and functional MRI to identify motivational deficits and elucidate their brain correlates before initiation, after 7 days and after 6 months of treatment. 36 healthy volunteers will also be included to allow comparison with patients with depression. They will not receive any treatment.
Detailed Description
One hundred patients with a moderate to severe major depressive episode will be enrolled in this prospective multicenter study. Six visits will be scheduled within a year: V0 (inclusion visit): verification of inclusion and exclusion criteria, information, and consent. V1 (before randomization - baseline state): Clinical evaluation using validated questionnaires for the severity of depression, quality of life, anhedonia, apathy, and cognitive dysfunction. Neuro-cognitive evaluation using a battery of tests to explore motivation, emotion processing, belief construction, and their updating. Part of the tests will be performed during the functional MRI session. Structural (anatomical) and functional MRI, ASL. Blood samples. Randomization and introduction of the new antidepressant will occur immediately after V1. To maximize acceptability by referring psychiatrists, dosage and co-prescriptions will be at the discretion of the psychiatrist in charge, but the assigned treatment will not be changed for 4 weeks (until V3). V2 (7 days after the beginning of the new antidepressant - 'early response visit'): o Similar to V1. V3 (28 days after the beginning of the new antidepressant - 'conventional response visit'): Clinical evaluation using validated questionnaires for the severity of depression, quality of life, anhedonia, apathy, and cognitive dysfunction. Blood samples V4 (6 months after the beginning of the new antidepressant - 'remission visit'): Clinical evaluation using validated questionnaires for the severity of depression, quality of life, anhedonia, apathy, and cognitive dysfunction. Cognitive evaluation using a battery of tests to explore motivation, emotion processing, belief construction, and their updating. Structural (anatomical) MRI, ASL Blood samples V5 (one year after the beginning of the new antidepressant - 'functional remission visit'): Clinical evaluation using validated questionnaires for the severity of depression, quality of life, anhedonia, apathy, and cognitive dysfunction. 36 healthy volunteers without a history of neurologic or psychiatric disorder, matched for age, gender, and education will be included. They will perform V0-V2 (without MRI and blood sample at V2). Healthy volunteers will not receive any treatment as part of the research.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Major Depressive Disorder

7. Study Design

Primary Purpose
Treatment
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Model Description
Randomization and introduction of the new antidepressant will occur immediately after V1. Patients will receive an antidepressant as monotherapy after randomization between two strategies: escitalopram and vortioxetine. To maximize acceptability by referring psychiatrists, dosage and co-prescriptions will be at the discretion of the psychiatrist in charge, but the allocated treatment will not be changed for 4 weeks (until V3). After 4 weeks, the treatment can be adapted by the refeering psychiatrist exactly as if the patient had not been included in the trial.
Masking
None (Open Label)
Allocation
Randomized
Enrollment
136 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title
escitalopram strategy
Arm Type
Other
Arm Description
The strategy will not be modified for a period of 4 weeks. Dosage adjustment and co-prescriptions will be at the discretion of the refeering psychiatrist.
Arm Title
vortioxetine strategy
Arm Type
Other
Arm Description
The strategy will not be modified for a period of 4 weeks. Dosage adjustment and co-prescriptions will be at the discretion of the refeering psychiatrist.
Intervention Type
Other
Intervention Name(s)
escitalopram
Intervention Description
Patients will receive an antidepressant strategy : escitalopram. The strategy will not be modified for a period of 4 weeks. Dosage adjustment and co-prescriptions will be at the discretion of the refeering psychiatrist. After 4 weeks, the strategy can be adapted by the refeering psychiatrist exactly as if the patient had not been included in the trial.
Intervention Type
Other
Intervention Name(s)
vortioxetine
Intervention Description
Patients will receive an antidepressant strategy : vortioxetine. The strategy will not be modified for a period of 4 weeks. Dosage adjustment and co-prescriptions will be at the discretion of the refeering psychiatrist. After 4 weeks, the treatment strategy can be adapted by the refeering psychiatrist exactly as if the patient had not been included in the trial.
Primary Outcome Measure Information:
Title
Prediction of the therapeutic response (MADRS score) 28 days after the introduction of the antidepressant strategy (V3) based on the early changes (differences between V1 and V2) of the computational phenotype of depressed patients.
Description
The therapeutic response will be measured with the Montgomery-Asberg Depression Rating Scale (MADRS). The MADRS is a 10- item scale widely used in depression research to assess the severity of depression. Response will be defined by a score divided by 2 compared to baseline MADRS score, while remission will be defined by a score < 7 (symptom absent) 28 days after the initiation of the antidepressant strategy. The "computational phenotype" is the outcome of the computationnal analysis of behavior. It is expressed in abstract unit. The change in computationnal phenotype between V1 and V2 will be entered in logistic regression aiming to predict clinical response at 28 days, measured with the MADRS score.
Time Frame
Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant) and V3 (after 28 days of antidepressant)
Secondary Outcome Measure Information:
Title
Prediction of the therapeutic response (MADRS score) 28 days after the introduction of the antidepressant strategy (V3) based on the early changes (differences between V1 and V2) of the neuro-computational phenotype of depressed patients
Description
Same than outcome 1 but using brain imaging on top of behavior (neurocomputational modeling) to predict clinical response.
Time Frame
Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant) and V3 (after 28 days of antidepressant)
Title
Prediction of the therapeutic response (MADRS score) 28 days after the introduction of the antidepressant strategy (V3) based on the initial (baseline state- V1) neuro-computational phenotype of depressed patients
Description
Same than Outcome 2 but using only V1 instead of the change between V1 and V2 to predict clinical response.
Time Frame
Baseline state (before the start of antidepressant strategy), and V3 (after 28 days of antidepressant)
Title
Prediction of long-term remission (V4) based on the early changes (differences between V1 and V2) of the neuro-computationnal phenotype of depressed patients
Description
Same than Outcome 2 but to predict clinical remission at V4 instead of clinical response at V3.
Time Frame
Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant), V4 (6 months after the start of antidepressant)
Title
Prediction functional remission (V5) based on the early changes (differences between V1 and V2) of the neuro-computationnal phenotype of depressed patients
Description
Same than Outcome 2 but to predict functional remission at V5 instead of clinical response at V3.
Time Frame
Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant), V5 (1 year after the start of antidepressant)
Title
Prediction of relapse at one year (V5) based on the computationnal phenotype of remitted patients at 6 months (V4).
Description
Same than Outcome 1 but using computational phenotype at V4 to predict predict functional remission at V5.
Time Frame
V4 (6 months after the start of antidepressant), V5 (1 year after the start of antidepressant)
Title
Description of the motivational deficit of depressed patients at baseline (V1).
Description
Comparison of the computational phenotype of patients with depression and healthy volunteers at V1.
Time Frame
Baseline state (before the start of antidepressant strategy)
Title
Description of the neural correlates of motivation deficits of depressed patients at baseline (V1).
Description
Comparison of the brain functional statistical maps of patient with depression and healthy volunteers at V1.
Time Frame
Baseline state (before the start of antidepressant strategy)
Title
Description of the evolution of motivation deficit of depressed patients after one week of antidepressant treatment
Description
Comparison of the computational phenotype of patients with depression at V1 and V2.
Time Frame
Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant)
Title
Description of the evolution of the neural correlates of motivation deficits after one week of antidepressant treatment
Description
Comparison of the brain functional statistical maps of patient with depression at V1 and V2.
Time Frame
Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant)
Title
Description of the evolution of motivation deficit of depressed patients at 6 months
Description
Comparison of the computational phenotype of patients with depression at V1 and V4.
Time Frame
Baseline state (before the start of antidepressant strategy), V4 (6 months after the start of antidepressant)
Title
Description of the evolution of the structural neural correlates of depression after 6 months of treatment
Description
Comparison of the structural brain imaging of patients with depression at V1 and V4.
Time Frame
Baseline state (before the start of antidepressant strategy), V4 (6 months after the start of antidepressant)
Title
Description of the evolution of the functional neural correlates of depression after 6 months of treatment
Description
Comparison of the function brain imaging (ASL) of patients with depression at V1 and V4.
Time Frame
Baseline state (before the start of antidepressant strategy) V4 (6 months after the start of antidepressant)
Title
Construction of a bio-bank
Description
Serum tubes will be drowned along the study (V1, V2, V3 and V4 for patients - V1 for healthy volunteers) prepared and stored.
Time Frame
Baseline state (before the start of antidepressant strategy), V2 (after 7 days of antidepressant) and V3 (after 28 days of antidepressant), V4 (6 months after the start of antidepressant)

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
Accepts Healthy Volunteers
Eligibility Criteria
Patients with major depressive disorder Inclusion Criteria: Meeting DSM-5 criteria for major depressive disorder (single or recurrent episodes) With a MADRS score >= 24 For which a new line of treatment is needed No previous line of antidepressant for this episode or wash-out long-enough to avoid carry-over effects Valid health care insurance Exclusion Criteria: Treatment-resistant depression (defined as insufficient response despite at least 2 trials of antidepressant prescribed at adequate dose and duration) Subjects with a trial of escitalopram and/or vortioxetine for the current episode, or with contra-indication to one of these two drugs Subjects with a diagnostic of persistent depressive disorder, bipolar disorder or schizophrenia, neurodeveloppemental disorder, unremitted substance abuse disorder other than tobacco, personality disorder severe enough to compromise the follow-up (based on investigator's appreciation). Subject with a history of neurological disorder: parkinson's disease, dementia Contraindications to MRI scanning: pregnancy, claustrophobia, metallic implants Pregnant or breastfeeding women involuntary hospitalisation and legal protection measures Healthy volunteers Inclusion Criteria: - Valid health care insurance Exclusion Criteria: Subjects with a diagnostic of persistent depressive disorder, bipolar disorder or schizophrenia, neurodeveloppemental disorder, unremitted substance abuse disorder other than tobacco, personality disorder severe enough to compromise the follow-up (based on investigator's appreciation). Subject with a history of neurological disorder: parkinson's disease, dementia Contraindications to MRI scanning: pregnancy, claustrophobia, metallic implants Pregnant or breastfeeding women
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Fabien Vinckier
Phone
0033683714083
Email
f.vinckier@ghu-paris.fr
First Name & Middle Initial & Last Name or Official Title & Degree
Claire Jaffré
Phone
0033650557373
Email
claire.jaffre@yahoo.fr
Facility Information:
Facility Name
Groupe hospitalo-universitaire de Grenoble Alpes
City
La Tronche
State/Province
Isère
ZIP/Postal Code
38700
Country
France
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Mircea Polosan
Facility Name
Centre hospitalier Universitaire de Saint-Etienne
City
Saint-Priest-en-Jarez
State/Province
Loire
ZIP/Postal Code
42270
Country
France
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Eric Fakra
Facility Name
Centre hospitalier Universitaire de Lille
City
Lille
State/Province
Nord
ZIP/Postal Code
59000
Country
France
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Renaud Jardri
Facility Name
Groupe hospitalo-universitaire Assistance Publique, hôpital Pitié Salpêtrière - Hôpitaux de Paris Sorbonne Université
City
Paris
ZIP/Postal Code
75013
Country
France
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Philippe Fossati
Facility Name
- Groupe hospitalo-universitaire Paris Psychiatrie et Neurosciences
City
Paris
ZIP/Postal Code
75014
Country
France
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Fabien Vinckier

12. IPD Sharing Statement

Plan to Share IPD
Yes
IPD Sharing Plan Description
The data obtained from medical visits (clinical informations, biological assessments, cognitive data) and brain MRIs will be kept, coded and archived for a period of two years after the last publication of the research results or until the final research report is signed. These can be used later for collaborative research (academic and/or industrial partners) in the European Union (EU) and/or abroad exclusively for scientific purposes. In case of transfer of the anonymized database resulting from this research abroad (outside the EU), the sponsor undertakes to ensure a level of security equivalent to French or European Union law.
IPD Sharing Time Frame
The data obtained from medical visits (clinical informations, biological assessments, neurocognitive data)and brain MRIs will be kept, coded and archived for a period of two years after the last publication of the research results or until the final research report is signed.
IPD Sharing Access Criteria
The data can be used for collaborative research (academic and/or industrial partners) in the European Union (EU) and/or abroad exclusively for scientific purposes. In case of transfer of the anonymized database resulting from this research abroad (outside the EU), the sponsor undertakes to ensure a level of security equivalent to French or European Union law.
Citations:
PubMed Identifier
23879318
Citation
Bauer M, Pfennig A, Severus E, Whybrow PC, Angst J, Moller HJ; World Federation of Societies of Biological Psychiatry. Task Force on Unipolar Depressive Disorders. World Federation of Societies of Biological Psychiatry (WFSBP) guidelines for biological treatment of unipolar depressive disorders, part 1: update 2013 on the acute and continuation treatment of unipolar depressive disorders. World J Biol Psychiatry. 2013 Jul;14(5):334-85. doi: 10.3109/15622975.2013.804195. Epub 2013 Jul 3.
Results Reference
background
PubMed Identifier
19674794
Citation
Lam RW, Kennedy SH, Grigoriadis S, McIntyre RS, Milev R, Ramasubbu R, Parikh SV, Patten SB, Ravindran AV; Canadian Network for Mood and Anxiety Treatments (CANMAT). Canadian Network for Mood and Anxiety Treatments (CANMAT) clinical guidelines for the management of major depressive disorder in adults. III. Pharmacotherapy. J Affect Disord. 2009 Oct;117 Suppl 1:S26-43. doi: 10.1016/j.jad.2009.06.041. Epub 2009 Aug 11.
Results Reference
background
PubMed Identifier
21929846
Citation
Uher R, Perlis RH, Henigsberg N, Zobel A, Rietschel M, Mors O, Hauser J, Dernovsek MZ, Souery D, Bajs M, Maier W, Aitchison KJ, Farmer A, McGuffin P. Depression symptom dimensions as predictors of antidepressant treatment outcome: replicable evidence for interest-activity symptoms. Psychol Med. 2012 May;42(5):967-80. doi: 10.1017/S0033291711001905. Epub 2011 Sep 20.
Results Reference
background
PubMed Identifier
29194534
Citation
Pessiglione M, Vinckier F, Bouret S, Daunizeau J, Le Bouc R. Why not try harder? Computational approach to motivation deficits in neuro-psychiatric diseases. Brain. 2018 Mar 1;141(3):629-650. doi: 10.1093/brain/awx278.
Results Reference
background
PubMed Identifier
21853083
Citation
Clery-Melin ML, Schmidt L, Lafargue G, Baup N, Fossati P, Pessiglione M. Why don't you try harder? An investigation of effort production in major depression. PLoS One. 2011;6(8):e23178. doi: 10.1371/journal.pone.0023178. Epub 2011 Aug 10.
Results Reference
background
PubMed Identifier
27337420
Citation
Mauras T, Masson M, Fossati P, Pessiglione M. Incentive Sensitivity as a Behavioral Marker of Clinical Remission From Major Depressive Episode. J Clin Psychiatry. 2016 Jun;77(6):e697-703. doi: 10.4088/JCP.15m09995.
Results Reference
background
PubMed Identifier
29672668
Citation
Le Heron C, Plant O, Manohar S, Ang YS, Jackson M, Lennox G, Hu MT, Husain M. Distinct effects of apathy and dopamine on effort-based decision-making in Parkinson's disease. Brain. 2018 May 1;141(5):1455-1469. doi: 10.1093/brain/awy110.
Results Reference
background
PubMed Identifier
22090487
Citation
Wardle MC, Treadway MT, Mayo LM, Zald DH, de Wit H. Amping up effort: effects of d-amphetamine on human effort-based decision-making. J Neurosci. 2011 Nov 16;31(46):16597-602. doi: 10.1523/JNEUROSCI.4387-11.2011.
Results Reference
background
PubMed Identifier
22553023
Citation
Treadway MT, Buckholtz JW, Cowan RL, Woodward ND, Li R, Ansari MS, Baldwin RM, Schwartzman AN, Kessler RM, Zald DH. Dopaminergic mechanisms of individual differences in human effort-based decision-making. J Neurosci. 2012 May 2;32(18):6170-6. doi: 10.1523/JNEUROSCI.6459-11.2012.
Results Reference
background
PubMed Identifier
17050654
Citation
Nutt D, Demyttenaere K, Janka Z, Aarre T, Bourin M, Canonico PL, Carrasco JL, Stahl S. The other face of depression, reduced positive affect: the role of catecholamines in causation and cure. J Psychopharmacol. 2007 Jul;21(5):461-71. doi: 10.1177/0269881106069938. Epub 2006 Oct 18.
Results Reference
background
PubMed Identifier
15014711
Citation
Culpepper L. Escitalopram: A New SSRI for the Treatment of Depression in Primary Care. Prim Care Companion J Clin Psychiatry. 2002 Dec;4(6):209-214. doi: 10.4088/pcc.v04n0601.
Results Reference
background
PubMed Identifier
25016186
Citation
Sanchez C, Asin KE, Artigas F. Vortioxetine, a novel antidepressant with multimodal activity: review of preclinical and clinical data. Pharmacol Ther. 2015 Jan;145:43-57. doi: 10.1016/j.pharmthera.2014.07.001. Epub 2014 Jul 9.
Results Reference
background
PubMed Identifier
24850369
Citation
Fervaha G, Foussias G, Agid O, Remington G. Motivational and neurocognitive deficits are central to the prediction of longitudinal functional outcome in schizophrenia. Acta Psychiatr Scand. 2014 Oct;130(4):290-9. doi: 10.1111/acps.12289. Epub 2014 May 22.
Results Reference
background
PubMed Identifier
26995233
Citation
Fervaha G, Foussias G, Takeuchi H, Agid O, Remington G. Motivational deficits in major depressive disorder: Cross-sectional and longitudinal relationships with functional impairment and subjective well-being. Compr Psychiatry. 2016 Apr;66:31-8. doi: 10.1016/j.comppsych.2015.12.004. Epub 2015 Dec 18.
Results Reference
background
PubMed Identifier
32074255
Citation
Berwian IM, Wenzel JG, Collins AGE, Seifritz E, Stephan KE, Walter H, Huys QJM. Computational Mechanisms of Effort and Reward Decisions in Patients With Depression and Their Association With Relapse After Antidepressant Discontinuation. JAMA Psychiatry. 2020 May 1;77(5):513-522. doi: 10.1001/jamapsychiatry.2019.4971.
Results Reference
background
PubMed Identifier
22363208
Citation
Schmidt L, Lebreton M, Clery-Melin ML, Daunizeau J, Pessiglione M. Neural mechanisms underlying motivation of mental versus physical effort. PLoS Biol. 2012 Feb;10(2):e1001266. doi: 10.1371/journal.pbio.1001266. Epub 2012 Feb 21.
Results Reference
background
PubMed Identifier
25411490
Citation
Skvortsova V, Palminteri S, Pessiglione M. Learning to minimize efforts versus maximizing rewards: computational principles and neural correlates. J Neurosci. 2014 Nov 19;34(47):15621-30. doi: 10.1523/JNEUROSCI.1350-14.2014.
Results Reference
background
PubMed Identifier
17431137
Citation
Pessiglione M, Schmidt L, Draganski B, Kalisch R, Lau H, Dolan RJ, Frith CD. How the brain translates money into force: a neuroimaging study of subliminal motivation. Science. 2007 May 11;316(5826):904-6. doi: 10.1126/science.1140459. Epub 2007 Apr 12.
Results Reference
background
PubMed Identifier
31179377
Citation
Pessiglione M, Delgado MR. The good, the bad and the brain: Neural correlates of appetitive and aversive values underlying decision making. Curr Opin Behav Sci. 2015 Oct;5:78-84. doi: 10.1016/j.cobeha.2015.08.006. Epub 2015 Aug 24.
Results Reference
background
PubMed Identifier
23217747
Citation
Palminteri S, Justo D, Jauffret C, Pavlicek B, Dauta A, Delmaire C, Czernecki V, Karachi C, Capelle L, Durr A, Pessiglione M. Critical roles for anterior insula and dorsal striatum in punishment-based avoidance learning. Neuron. 2012 Dec 6;76(5):998-1009. doi: 10.1016/j.neuron.2012.10.017.
Results Reference
background
PubMed Identifier
19914190
Citation
Lebreton M, Jorge S, Michel V, Thirion B, Pessiglione M. An automatic valuation system in the human brain: evidence from functional neuroimaging. Neuron. 2009 Nov 12;64(3):431-9. doi: 10.1016/j.neuron.2009.09.040.
Results Reference
background
PubMed Identifier
29700303
Citation
Vinckier F, Rigoux L, Oudiette D, Pessiglione M. Neuro-computational account of how mood fluctuations arise and affect decision making. Nat Commun. 2018 Apr 26;9(1):1708. doi: 10.1038/s41467-018-03774-z.
Results Reference
background
PubMed Identifier
26573970
Citation
Stephan KE, Bach DR, Fletcher PC, Flint J, Frank MJ, Friston KJ, Heinz A, Huys QJM, Owen MJ, Binder EB, Dayan P, Johnstone EC, Meyer-Lindenberg A, Montague PR, Schnyder U, Wang XJ, Breakspear M. Charting the landscape of priority problems in psychiatry, part 1: classification and diagnosis. Lancet Psychiatry. 2016 Jan;3(1):77-83. doi: 10.1016/S2215-0366(15)00361-2. Epub 2015 Nov 11.
Results Reference
background
PubMed Identifier
26573969
Citation
Stephan KE, Binder EB, Breakspear M, Dayan P, Johnstone EC, Meyer-Lindenberg A, Schnyder U, Wang XJ, Bach DR, Fletcher PC, Flint J, Frank MJ, Heinz A, Huys QJM, Montague PR, Owen MJ, Friston KJ. Charting the landscape of priority problems in psychiatry, part 2: pathogenesis and aetiology. Lancet Psychiatry. 2016 Jan;3(1):84-90. doi: 10.1016/S2215-0366(15)00360-0. Epub 2015 Nov 11.
Results Reference
background
PubMed Identifier
27346545
Citation
Stephan KE, Schlagenhauf F, Huys QJM, Raman S, Aponte EA, Brodersen KH, Rigoux L, Moran RJ, Daunizeau J, Dolan RJ, Friston KJ, Heinz A. Computational neuroimaging strategies for single patient predictions. Neuroimage. 2017 Jan 15;145(Pt B):180-199. doi: 10.1016/j.neuroimage.2016.06.038. Epub 2016 Jun 22.
Results Reference
background
PubMed Identifier
26361002
Citation
Corlett PR, Fletcher PC. Computational psychiatry: a Rosetta Stone linking the brain to mental illness. Lancet Psychiatry. 2014 Oct;1(5):399-402. doi: 10.1016/S2215-0366(14)70298-6. Epub 2014 Aug 12. No abstract available.
Results Reference
background
PubMed Identifier
21550365
Citation
Hasler G. Can the neuroeconomics revolution revolutionize psychiatry? Neurosci Biobehav Rev. 2012 Jan;36(1):64-78. doi: 10.1016/j.neubiorev.2011.04.011. Epub 2011 Apr 29.
Results Reference
background
PubMed Identifier
26906507
Citation
Huys QJ, Maia TV, Frank MJ. Computational psychiatry as a bridge from neuroscience to clinical applications. Nat Neurosci. 2016 Mar;19(3):404-13. doi: 10.1038/nn.4238.
Results Reference
background
PubMed Identifier
22177032
Citation
Montague PR, Dolan RJ, Friston KJ, Dayan P. Computational psychiatry. Trends Cogn Sci. 2012 Jan;16(1):72-80. doi: 10.1016/j.tics.2011.11.018. Epub 2011 Dec 14. Erratum In: Trends Cogn Sci. 2012 May;16(5):306.
Results Reference
background
PubMed Identifier
27346915
Citation
Keks N, Hope J, Keogh S. Switching and stopping antidepressants. Aust Prescr. 2016 Jun;39(3):76-83. doi: 10.18773/austprescr.2016.039. Epub 2016 Jun 1.
Results Reference
background
PubMed Identifier
29477251
Citation
Cipriani A, Furukawa TA, Salanti G, Chaimani A, Atkinson LZ, Ogawa Y, Leucht S, Ruhe HG, Turner EH, Higgins JPT, Egger M, Takeshima N, Hayasaka Y, Imai H, Shinohara K, Tajika A, Ioannidis JPA, Geddes JR. 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 Apr 7;391(10128):1357-1366. doi: 10.1016/S0140-6736(17)32802-7. Epub 2018 Feb 21.
Results Reference
background
PubMed Identifier
28677828
Citation
Koesters M, Ostuzzi G, Guaiana G, Breilmann J, Barbui C. Vortioxetine for depression in adults. Cochrane Database Syst Rev. 2017 Jul 5;7(7):CD011520. doi: 10.1002/14651858.CD011520.pub2.
Results Reference
background
PubMed Identifier
19578460
Citation
Hartwig V, Giovannetti G, Vanello N, Lombardi M, Landini L, Simi S. Biological effects and safety in magnetic resonance imaging: a review. Int J Environ Res Public Health. 2009 Jun;6(6):1778-98. doi: 10.3390/ijerph6061778. Epub 2009 Jun 10.
Results Reference
background
PubMed Identifier
29593535
Citation
Felice D, Guilloux JP, Pehrson A, Li Y, Mendez-David I, Gardier AM, Sanchez C, David DJ. Vortioxetine Improves Context Discrimination in Mice Through a Neurogenesis Independent Mechanism. Front Pharmacol. 2018 Mar 12;9:204. doi: 10.3389/fphar.2018.00204. eCollection 2018.
Results Reference
background
PubMed Identifier
24818074
Citation
Hayakawa YK, Sasaki H, Takao H, Hayashi N, Kunimatsu A, Ohtomo K, Aoki S. Depressive symptoms and neuroanatomical structures in community-dwelling women: A combined voxel-based morphometry and diffusion tensor imaging study with tract-based spatial statistics. Neuroimage Clin. 2014 Mar 12;4:481-7. doi: 10.1016/j.nicl.2014.03.002. eCollection 2014.
Results Reference
background
PubMed Identifier
27376473
Citation
Colle R, Dupong I, Colliot O, Deflesselle E, Hardy P, Falissard B, Ducreux D, Chupin M, Corruble E. Smaller hippocampal volumes predict lower antidepressant response/remission rates in depressed patients: A meta-analysis. World J Biol Psychiatry. 2018 Aug;19(5):360-367. doi: 10.1080/15622975.2016.1208840. Epub 2016 Aug 15.
Results Reference
background
PubMed Identifier
32113908
Citation
Osimo EF, Pillinger T, Rodriguez IM, Khandaker GM, Pariante CM, Howes OD. Inflammatory markers in depression: A meta-analysis of mean differences and variability in 5,166 patients and 5,083 controls. Brain Behav Immun. 2020 Jul;87:901-909. doi: 10.1016/j.bbi.2020.02.010. Epub 2020 Feb 27.
Results Reference
background
PubMed Identifier
31076872
Citation
Kojima M, Matsui K, Mizui T. BDNF pro-peptide: physiological mechanisms and implications for depression. Cell Tissue Res. 2019 Jul;377(1):73-79. doi: 10.1007/s00441-019-03034-6. Epub 2019 May 10.
Results Reference
background
PubMed Identifier
29608993
Citation
Ogyu K, Kubo K, Noda Y, Iwata Y, Tsugawa S, Omura Y, Wada M, Tarumi R, Plitman E, Moriguchi S, Miyazaki T, Uchida H, Graff-Guerrero A, Mimura M, Nakajima S. Kynurenine pathway in depression: A systematic review and meta-analysis. Neurosci Biobehav Rev. 2018 Jul;90:16-25. doi: 10.1016/j.neubiorev.2018.03.023. Epub 2018 Mar 30.
Results Reference
background
PubMed Identifier
31255681
Citation
Verdonk F, Petit AC, Abdel-Ahad P, Vinckier F, Jouvion G, de Maricourt P, De Medeiros GF, Danckaert A, Van Steenwinckel J, Blatzer M, Maignan A, Langeron O, Sharshar T, Callebert J, Launay JM, Chretien F, Gaillard R. Microglial production of quinolinic acid as a target and a biomarker of the antidepressant effect of ketamine. Brain Behav Immun. 2019 Oct;81:361-373. doi: 10.1016/j.bbi.2019.06.033. Epub 2019 Jun 28.
Results Reference
background
PubMed Identifier
26359113
Citation
Harrison NA, Voon V, Cercignani M, Cooper EA, Pessiglione M, Critchley HD. A Neurocomputational Account of How Inflammation Enhances Sensitivity to Punishments Versus Rewards. Biol Psychiatry. 2016 Jul 1;80(1):73-81. doi: 10.1016/j.biopsych.2015.07.018. Epub 2015 Aug 1.
Results Reference
background
PubMed Identifier
28101340
Citation
Chen G, Bian H, Jiang D, Cui M, Ji S, Liu M, Lang X, Zhuo C. Pseudo-continuous arterial spin labeling imaging of cerebral blood perfusion asymmetry in drug-naive patients with first-episode major depression. Biomed Rep. 2016 Dec;5(6):675-680. doi: 10.3892/br.2016.796. Epub 2016 Oct 31.
Results Reference
background
PubMed Identifier
24882178
Citation
Ota M, Noda T, Sato N, Hattori K, Teraishi T, Hori H, Nagashima A, Shimoji K, Higuchi T, Kunugi H. Characteristic distributions of regional cerebral blood flow changes in major depressive disorder patients: a pseudo-continuous arterial spin labeling (pCASL) study. J Affect Disord. 2014 Aug;165:59-63. doi: 10.1016/j.jad.2014.04.032. Epub 2014 Apr 21.
Results Reference
background
PubMed Identifier
31388104
Citation
Cooper CM, Chin Fatt CR, Liu P, Grannemann BD, Carmody T, Almeida JRC, Deckersbach T, Fava M, Kurian BT, Malchow AL, McGrath PJ, McInnis M, Oquendo MA, Parsey RV, Bartlett E, Weissman M, Phillips ML, Lu H, Trivedi MH. Discovery and replication of cerebral blood flow differences in major depressive disorder. Mol Psychiatry. 2020 Jul;25(7):1500-1510. doi: 10.1038/s41380-019-0464-7. Epub 2019 Aug 6.
Results Reference
background
PubMed Identifier
26826533
Citation
Kaichi Y, Okada G, Takamura M, Toki S, Akiyama Y, Higaki T, Matsubara Y, Okamoto Y, Yamawaki S, Awai K. Changes in the regional cerebral blood flow detected by arterial spin labeling after 6-week escitalopram treatment for major depressive disorder. J Affect Disord. 2016 Apr;194:135-43. doi: 10.1016/j.jad.2015.12.062. Epub 2016 Jan 21.
Results Reference
background
PubMed Identifier
31158260
Citation
Ruckbeil MV, Hilgers RD, Heussen N. Randomization in survival studies: An evaluation method that takes into account selection and chronological bias. PLoS One. 2019 Jun 3;14(6):e0217946. doi: 10.1371/journal.pone.0217946. eCollection 2019.
Results Reference
background
PubMed Identifier
444788
Citation
Montgomery SA, Asberg M. A new depression scale designed to be sensitive to change. Br J Psychiatry. 1979 Apr;134:382-9. doi: 10.1192/bjp.134.4.382.
Results Reference
background
PubMed Identifier
12946886
Citation
Rush AJ, Trivedi MH, Ibrahim HM, Carmody TJ, Arnow B, Klein DN, Markowitz JC, Ninan PT, Kornstein S, Manber R, Thase ME, Kocsis JH, Keller MB. The 16-Item Quick Inventory of Depressive Symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression. Biol Psychiatry. 2003 Sep 1;54(5):573-83. doi: 10.1016/s0006-3223(02)01866-8. Erratum In: Biol Psychiatry. 2003 Sep 1;54(5):585.
Results Reference
background
PubMed Identifier
9626712
Citation
Development of the World Health Organization WHOQOL-BREF quality of life assessment. The WHOQOL Group. Psychol Med. 1998 May;28(3):551-8. doi: 10.1017/s0033291798006667.
Results Reference
background
PubMed Identifier
21102344
Citation
Sheehan DV, Harnett-Sheehan K, Spann ME, Thompson HF, Prakash A. Assessing remission in major depressive disorder and generalized anxiety disorder clinical trials with the discan metric of the Sheehan disability scale. Int Clin Psychopharmacol. 2011 Mar;26(2):75-83. doi: 10.1097/YIC.0b013e328341bb5f.
Results Reference
background
PubMed Identifier
7551619
Citation
Snaith RP, Hamilton M, Morley S, Humayan A, Hargreaves D, Trigwell P. A scale for the assessment of hedonic tone the Snaith-Hamilton Pleasure Scale. Br J Psychiatry. 1995 Jul;167(1):99-103. doi: 10.1192/bjp.167.1.99.
Results Reference
background
PubMed Identifier
1627973
Citation
Starkstein SE, Mayberg HS, Preziosi TJ, Andrezejewski P, Leiguarda R, Robinson RG. Reliability, validity, and clinical correlates of apathy in Parkinson's disease. J Neuropsychiatry Clin Neurosci. 1992 Spring;4(2):134-9. doi: 10.1176/jnp.4.2.134.
Results Reference
background
PubMed Identifier
30763119
Citation
Brown S, Rittenbach K, Cheung S, McKean G, MacMaster FP, Clement F. Current and Common Definitions of Treatment-Resistant Depression: Findings from a Systematic Review and Qualitative Interviews. Can J Psychiatry. 2019 Jun;64(6):380-387. doi: 10.1177/0706743719828965. Epub 2019 Feb 14.
Results Reference
background
PubMed Identifier
17055746
Citation
Friston K, Mattout J, Trujillo-Barreto N, Ashburner J, Penny W. Variational free energy and the Laplace approximation. Neuroimage. 2007 Jan 1;34(1):220-34. doi: 10.1016/j.neuroimage.2006.08.035. Epub 2006 Oct 20.
Results Reference
background
PubMed Identifier
24465198
Citation
Daunizeau J, Adam V, Rigoux L. VBA: a probabilistic treatment of nonlinear models for neurobiological and behavioural data. PLoS Comput Biol. 2014 Jan;10(1):e1003441. doi: 10.1371/journal.pcbi.1003441. Epub 2014 Jan 23.
Results Reference
background
PubMed Identifier
17416921
Citation
O'Doherty JP, Hampton A, Kim H. Model-based fMRI and its application to reward learning and decision making. Ann N Y Acad Sci. 2007 May;1104:35-53. doi: 10.1196/annals.1390.022. Epub 2007 Apr 7.
Results Reference
background
PubMed Identifier
27824554
Citation
Meyniel F, Goodwin GM, Deakin JW, Klinge C, MacFadyen C, Milligan H, Mullings E, Pessiglione M, Gaillard R. A specific role for serotonin in overcoming effort cost. Elife. 2016 Nov 8;5:e17282. doi: 10.7554/eLife.17282.
Results Reference
background

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Prediction of the Therapeutic Response in Depression Based on Neuro-computational Modeling Assessment of Motivation

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