Computational Psychiatric Approach to Depression

NCT ID: NCT04189939

Last Updated: 2024-08-06

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

128 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-03-09

Study Completion Date

2023-07-10

Brief Summary

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The purpose of this research is to investigate how the brain changes in patients undergoing electroconvulsive (ECT) treatment for depression. Subjects will be invited to be in this study because (1) they are a patient about to receive ECT treatment for depression, or (2) they are a patient diagnosed with depression and do not qualify for ECT treatment, or (3) they are a healthy adult volunteer with no history of depression.

All volunteers must be between the ages of 18-85. Participation in this research will involve three visits. Each visit will last about 3-4 hours. If the subject is a patient receiving ECT for depression the study team will schedule study visits to go along with patient treatment visits. If the subject is diagnosed with depression (not treatment-resistant depression) or are a healthy volunteer, their first visit will be scheduled at their convenience, followed by a second visit 1-3 months post visit one and a third visit 1-2 months post visit two, for a total of three research visits.

Participation in this research will involve playing simple computer games while the subject's brain is scanned with magnetic resonance imaging (MRI). Additionally, the study team will assess symptoms of depression using questionnaires. Patients receiving ECT will not experience any changes to their standard of care ECT treatment plan. Healthy and non-treatment resistant depressed volunteers will not undergo ECT treatment.

Detailed Description

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The goal for this study will be to test the following overall hypotheses: (1) that adaptive decision-making processes are disrupted in patients with treatment-resistant depression, and (2) the neural and behavioral changes associated with treatment-resistant depression can be assessed using functional magnetic resonance imaging paired with computationally constrained adaptive decision-making games.

The investigators will use computational modeling of incentivized decision-making tasks, brain imaging (functional magnetic resonance imaging, fMRI), and standard clinical assessments, to characterize patients referred to Wake Forest Baptist Medical Center for ECT. Characterization will occur over multiple visits to be aligned with the normal course of patient care.

Data collected may be used in hypothesis driven analyses to:

1. classify treatment resistant depression versus healthy controls and non-treatment resistant depression
2. predictors of ECT treatment success versus failure
3. characterize brain and behavioral changes consistent with treatment success versus failure
4. predict who will need maintenance ECT therapy
5. determine what changes in decision-making behavior are apparent in patients who require ECT maintenance therapy versus those who do not.

Conditions

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Depression Treatment Resistant Depression

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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subjects with treatment-resistant depression

approximately 48 subjects with treatment-resistant depression will undergo (1) clinical assessments, (2) perform a computer-based decision-making task while (3) their brain activity is monitored using a 3T MRI scanner.

clinical assessments

Intervention Type OTHER

Behavioral tasks will be executed via a computer interface. Below, we provide an estimated timeline for each visit and subsequently provide detail for the relevant stages.

Each participant's visit will last approximately 4-5 hours. Each visit will consist of the following tasks (in this order):

healthy subjects

approximately 48 healthy subjects will undergo (1) clinical assessments, (2) perform a computer-based decision-making task while (3) their brain activity is monitored using a 3T MRI scanner.

No interventions assigned to this group

subjects with non treatment-resistant depression

approximately 48 subjects with non-treatment-resistant depression will undergo (1) clinical assessments, (2) perform a computer-based decision-making task while (3) their brain activity is monitored using a 3T MRI scanner.

No interventions assigned to this group

Interventions

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clinical assessments

Behavioral tasks will be executed via a computer interface. Below, we provide an estimated timeline for each visit and subsequently provide detail for the relevant stages.

Each participant's visit will last approximately 4-5 hours. Each visit will consist of the following tasks (in this order):

Intervention Type OTHER

Other Intervention Names

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computer-based decition making task 3T MRI scan

Eligibility Criteria

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Inclusion Criteria

* Adult volunteers (ages 18-85)
* Treatment-resistant depressed patients must meet criteria in standard-of-care evaluation for ECT treatment
* Clinically depressed patients must meet criteria in standard-of-care evaluation for depression.


* Healthy adult volunteers (ages 18-85)

Exclusion Criteria

* Individuals who cannot have MRI scanning
* Individuals not able to provide written consent and verbal assent
* Individuals not able to understand task instructions or consent documents
* Women who are pregnant

For healthy subject volunteers:


* Individuals diagnosed with depression (regardless of treatment status)
* Individuals who cannot have MRI scanning
* Individuals not able to provide written consent and verbal assent
* Individuals not able to understand task instructions or consent documents
* Women who are pregnant
Minimum Eligible Age

18 Years

Maximum Eligible Age

85 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Wake Forest University Health Sciences

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Kenneth T Kishida, PhD

Role: PRINCIPAL_INVESTIGATOR

Wake Forest University Health Sciences

Locations

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Wake Forest School of Medicine

Winston-Salem, North Carolina, United States

Site Status

Countries

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United States

References

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Kishida KT, King-Casas B, Montague PR. Neuroeconomic approaches to mental disorders. Neuron. 2010 Aug 26;67(4):543-54. doi: 10.1016/j.neuron.2010.07.021.

Reference Type BACKGROUND
PMID: 20797532 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 22177032 (View on PubMed)

Wang XJ, Krystal JH. Computational psychiatry. Neuron. 2014 Nov 5;84(3):638-54. doi: 10.1016/j.neuron.2014.10.018. Epub 2014 Nov 5.

Reference Type BACKGROUND
PMID: 25442941 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 26906507 (View on PubMed)

Berlim MT, Turecki G. Definition, assessment, and staging of treatment-resistant refractory major depression: a review of current concepts and methods. Can J Psychiatry. 2007 Jan;52(1):46-54. doi: 10.1177/070674370705200108.

Reference Type BACKGROUND
PMID: 17444078 (View on PubMed)

Other Identifiers

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IRB00056131

Identifier Type: -

Identifier Source: org_study_id

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