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| Name | Class |
|---|---|
| Sheba Medical Center | OTHER_GOV |
| Hebrew University of Jerusalem | OTHER |
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This project will combine the data collected from EEG, Eye tracking, structural and functional MRI scans and neuropsychological performance from patients with major depression receiving SSRI treatment. The purpose of this research is to predict the success of the SSRI treatment and to categorize patients into sub-groups according to similar patterns of brain activation to personalize treatment.
Major depression is a mood disorder affecting 350 million people worldwide. The disorder is characterized by depressed mood, anhedonia, decreased quality of life, deficits in cognitive functions and even suicide thoughts. Treatment of depression is often a long process and includes taking different types and quantities of medications. Therefore, there is a need to predict the success of the SSRI treatment. Our research will examine the outcomes of the combined technologies: BNA (EEG), Eye-tracker, structural and functional MRI scans and neuropsychology tasks in patients with depression while receiving SSRI treatment. The purpose of the research is to track biomarkers and other measures, which will allow predicting the SSRI treatment's success within 4 weeks instead of 8 weeks. In addition, the investigators will attempt to categorize patients into different subgroups according to their brain activation and eye movements. This division into subgroups may contribute to the understanding of the mechanisms that account for the responsiveness to SSRI treatment and to the possibility of targeting patients with depression towards a particular treatment. From this research, the investigators aim to personalize the treatment of depression, make it more efficient and reduce the amount of time for the patient to reach an optimal responsiveness.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Healthy subjects | 50 healthy subjects for a control group |
| |
| Patients with Major Depression | 50 patients with major depression for a research group |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| SIEMENS PRISMA MRI | Device | Collect data on brain activation from different methods |
|
| Measure | Description | Time Frame |
|---|---|---|
| EEG responses to cognitive tasks in combination with the Eye-tracker Device. | Categorize patients into subgroups according to combined measures of EEG and Eye | 2 years |
| Measure | Description | Time Frame |
|---|---|---|
| Resting state connectivity analysis | Examine the difference in resting state connectivity between the groups. | 2 years |
| Examine correlations between the different methods | Examine correlations between the different methods EEG, Eye-tracking and fMRI |
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Inclusion Criteria:
Inclusion Criteria for patients with depression:
Exclusion Criteria:
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Study population will include 2 groups of subjects: healthy subjects and patients with major depression
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Revital Amiaz | Contact | +972505250590 | Revital.Amiaz@sheba.health.gov.il | |
| Liran Korine | Contact | +972507453300 | liran@elminda.com |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Sheba Medical CENTER | Recruiting | Ramat Gan | 52621 | Israel |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 27918562 | Background | Drysdale AT, Grosenick L, Downar J, Dunlop K, Mansouri F, Meng Y, Fetcho RN, Zebley B, Oathes DJ, Etkin A, Schatzberg AF, Sudheimer K, Keller J, Mayberg HS, Gunning FM, Alexopoulos GS, Fox MD, Pascual-Leone A, Voss HU, Casey BJ, Dubin MJ, Liston C. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med. 2017 Jan;23(1):28-38. doi: 10.1038/nm.4246. Epub 2016 Dec 5. | |
| 1414552 |
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| ID | Term |
|---|---|
| D003865 | Depressive Disorder, Major |
| ID | Term |
|---|---|
| D003866 | Depressive Disorder |
| D019964 | Mood Disorders |
| D001523 | Mental Disorders |
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| ID | Term |
|---|---|
| D004569 | Electroencephalography |
| ID | Term |
|---|---|
| D003943 | Diagnostic Techniques, Neurological |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
| D004568 | Electrodiagnosis |
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| 2 years |
| EEG brain activation to cognitive tasks | Categorize patients into subgroups according to similar brain activity | 2 years |
| Eye-tracking tasks | Categorize patients into subgroups according to similar patterns of eye movements. | 2 years |
| Examine MRI structural changes | Compare structural changes between the groups (patients with depression, healthy subjects). | 2 years |
| Cognitive scores on CANTAB (computerized cognitive assessments) | Examine the difference in responses to different cognitive exams between the groups | 2 years |
| Background |
| Ogawa T, Sekino H, Uzura M, Sakamoto T, Taguchi Y, Yamaguchi Y, Hayashi T, Yamanaka I, Oohama N, Imaki S. Comparative study of magnetic resonance and CT scan imaging in cases of severe head injury. Acta Neurochir Suppl (Wien). 1992;55:8-10. doi: 10.1007/978-3-7091-9233-7_3. |
| 17719799 | Background | Raichle ME, Snyder AZ. A default mode of brain function: a brief history of an evolving idea. Neuroimage. 2007 Oct 1;37(4):1083-90; discussion 1097-9. doi: 10.1016/j.neuroimage.2007.02.041. Epub 2007 Mar 6. |
| 28476404 | Background | Rohden AI, Benchaya MC, Camargo RS, Moreira TC, Barros HMT, Ferigolo M. Dropout Prevalence and Associated Factors in Randomized Clinical Trials of Adolescents Treated for Depression: Systematic Review and Meta-analysis. Clin Ther. 2017 May;39(5):971-992.e4. doi: 10.1016/j.clinthera.2017.03.017. Epub 2017 May 2. |