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Prediction of SSRI Treatment in Major Depression.

A Combination of Innovative Technologies: EEG, Eye Tracking Device and fMRI in Order to Predict the Success of SSRI Treatment in Patients With Major Depression.

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT03670823
Enrollment
100
Registered
2018-09-14
Start date
2019-03-01
Completion date
2020-10-01
Last updated
2019-06-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Major Depression

Keywords

Major Depression, EEG, Eye Tracker, fMRI, MRI, Resting State Connectivity, Cognition

Brief summary

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.

Detailed description

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.

Interventions

DEVICESIEMENS PRISMA MRI

Collect data on brain activation from different methods

Sponsors

Sheba Medical Center
CollaboratorOTHER_GOV
Hebrew University of Jerusalem
CollaboratorOTHER
ElMindA Ltd
Lead SponsorINDUSTRY

Study design

Observational model
CASE_CONTROL
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 65 Years
Healthy volunteers
Yes

Inclusion criteria

1. Patients 18-65 years old 2. Male and female 3. Ability to comprehend and sign informed consent 4. DSM-5 diagnosis with MINI 7.0.2 (healthy subjects need to be ruled out) Inclusion Criteria for patients with depression: 1. DSM-5 diagnosis 2. 0-2 failed treatments 3. Patients which will start SSRI treatment

Exclusion criteria

1. unconsciousness 2. Pregnancy or nursing 3. Cardiovascular instability 4. Metabolic instability (water, electrolytes, sugar) 5. Fever or evidence of microbiological pollutant 6. Deafness or blindness 7. Schizophrenia 8. Addiction disorders 9. Eating disorders 10. Bi-polar disorder 11. Cognitive deficits 12. Start a new psychotherapy during the research 13. Unable to enter the MRI scanner

Design outcomes

Primary

MeasureTime frameDescription
EEG responses to cognitive tasks in combination with the Eye-tracker Device.2 yearsCategorize patients into subgroups according to combined measures of EEG and Eye

Secondary

MeasureTime frameDescription
Examine correlations between the different methods2 yearsExamine correlations between the different methods EEG, Eye-tracking and fMRI
EEG brain activation to cognitive tasks2 yearsCategorize patients into subgroups according to similar brain activity
Resting state connectivity analysis2 yearsExamine the difference in resting state connectivity between the groups.
Examine MRI structural changes2 yearsCompare structural changes between the groups (patients with depression, healthy subjects).
Cognitive scores on CANTAB (computerized cognitive assessments)2 yearsExamine the difference in responses to different cognitive exams between the groups
Eye-tracking tasks2 yearsCategorize patients into subgroups according to similar patterns of eye movements.

Countries

Israel

Contacts

Primary ContactRevital Amiaz
Revital.Amiaz@sheba.health.gov.il+972505250590
Backup ContactLiran Korine
liran@elminda.com+972507453300

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026