F32.0, F32.1, F32.2, F32.8, F32.9, F33.0, F33.1 F33.2 , F33.8, F33.9, F34.1, F40.0, F40.1, F40.2, F40.8, F40.9, F41.0, F41.1, F41.2, F41.3, F41.8, F41.9
Conditions
Interventions
Group 1: Individuals diagnosed with anxiety and/or depression disorders, undergoing task-based and resting-state fMRI, ECG, and blood pressure measurements, combined with cognitive tasks.
Group 2: Hea
Sponsors
Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurology
Eligibility
Sex/Gender
All
Age
18 Years to 55 Years
Inclusion criteria
Inclusion criteria: - Only for the anxiety and depression group: Psychiatric diagnosis of anxiety disorder (including panic attacks, agoraphobia, generalized anxiety, social anxiety, adjustment disorder with anxious reaction and anxiety-NOS) and/or mood disorder (major depression, dysphoria, adjustment disorder with depressive reaction, depressive episode). - Age 18-55 - Normal or corrected-to-normal vision - Voluntary participation and signing of the declaration of consent - German as a mother tongue or fluency in German (CEFR C1)
Exclusion criteria
Exclusion criteria: - Active psychosis - Diagnosis of bipolar disorder/ history of manic episodes - Significant suicidal intent requiring enhanced care - Presence of any contraindications for MRI examinations (see Appendix 1E MRI consent form) including claustrophobia, pacemakers, intracranial metal clips, cochlear implants, cerebrospinal fluid shunts, braces, and implanted medication pumps. - Neurological illnesses (e.g., epilepsy) or head trauma - Persons unable to give consent (e.g., in the case of dementia) - Pregnancy or planned pregnancy at the time of the study - Breastfeeding women - Lack of consent to the disclosure of incidental findings - Only for the control group: Diagnosis of anxiety and/or mood disorders - Only for the control group: Previous or current psychiatric diagnosis (not including ADHD)
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Primary endpoints: 1.Examining whether the performance on the cognitive tasks and the associated brain responses and heart rate variations can accurately predict classification to health or diagnosis, using ML classifiers. 2.Examining whether the performance on the cognitive tasks and the associated brain responses and heart rate variations can accurately predict the level of symptom severity, using ML regressors. 3.Examining whether distinct cognitive performance, associated brain responses, heart rate variations can differentiate between subtypes across the anxiety and depression group and uniquely characterize each subgroup through advanced ML clustering analysis. | — |
Secondary
| Measure | Time frame |
|---|---|
| Analysis of the relationship between cognitive task performance, brain activity (fMRI), and physiological responses (HRV and BP) to better understand how these factors interact with symptoms. | — |
Countries
Germany
Contacts
Public ContactThalia Richter
Max Planck Institute for Human Cognitive and Brain Sciences
Outcome results
None listed