Complex Dynamic Systems in Mood Disorders
Status: | Completed |
---|---|
Conditions: | Depression, Major Depression Disorder (MDD), Psychiatric, Bipolar Disorder |
Therapuetic Areas: | Psychiatry / Psychology, Pulmonary / Respiratory Diseases |
Healthy: | No |
Age Range: | 18 - 65 |
Updated: | 4/21/2016 |
Start Date: | November 2011 |
End Date: | December 2014 |
Complex Dynamic Systems in Mood Disorders is an observational, exploratory study of the
relationship between voice samples, heart rate, respiration, movement, galvanic skin
conductance, and sleep architecture with mood states in patients with Major Depressive
Disorder, Bipolar Disorder, and healthy controls. The overall hypothesis is that nonlinear
dynamic analyses will be able to reveal hidden patterns of complexity in each domain of
voice, heart rate variability, movement, arousal, and sleep stage data.
relationship between voice samples, heart rate, respiration, movement, galvanic skin
conductance, and sleep architecture with mood states in patients with Major Depressive
Disorder, Bipolar Disorder, and healthy controls. The overall hypothesis is that nonlinear
dynamic analyses will be able to reveal hidden patterns of complexity in each domain of
voice, heart rate variability, movement, arousal, and sleep stage data.
Aim 1: To assess multichannel physiologic measures associated with mood disorders.
Hypothesis: The overall hypothesis is that nonlinear dynamic analyses will be able to reveal
hidden patterns of complexity in each domain of voice, heart rate variability (RR
intervals), movement, arousal, and sleep stage data.
Aim 2: To assess differences in patterns and complexity of multiple physiological measures
in patients with MDD compared to healthy controls.
Hypothesis: MDD will be associated with decreased measures of complexity and increased
measures of approximate entropy compared to healthy controls.
Aim 3: To assess differences in patterns and complexity of multiple physiologic measures in
patients with BD compared to healthy controls.
Hypothesis: BD will be associated with decreased measures of complexity and increased
measures of approximate entropy compared to healthy controls.
Aim 4: To assess changes in patterns and complexity of multiple physiologic measures at
baseline and after 2 weeks of treatment for patients with MDD and BD.
Hypothesis: Measures of complexity will increase and measures of approximate entropy will
decrease in the first two weeks of treatment.
Aim 5: To assess the relationship between changes in patterns and complexity of multiple
physiologic measures and changes in mood state.
Hypothesis: Measures of complexity will increase and measures of approximate entropy will
decrease, especially for those who are much or very much improved
Hypothesis: The overall hypothesis is that nonlinear dynamic analyses will be able to reveal
hidden patterns of complexity in each domain of voice, heart rate variability (RR
intervals), movement, arousal, and sleep stage data.
Aim 2: To assess differences in patterns and complexity of multiple physiological measures
in patients with MDD compared to healthy controls.
Hypothesis: MDD will be associated with decreased measures of complexity and increased
measures of approximate entropy compared to healthy controls.
Aim 3: To assess differences in patterns and complexity of multiple physiologic measures in
patients with BD compared to healthy controls.
Hypothesis: BD will be associated with decreased measures of complexity and increased
measures of approximate entropy compared to healthy controls.
Aim 4: To assess changes in patterns and complexity of multiple physiologic measures at
baseline and after 2 weeks of treatment for patients with MDD and BD.
Hypothesis: Measures of complexity will increase and measures of approximate entropy will
decrease in the first two weeks of treatment.
Aim 5: To assess the relationship between changes in patterns and complexity of multiple
physiologic measures and changes in mood state.
Hypothesis: Measures of complexity will increase and measures of approximate entropy will
decrease, especially for those who are much or very much improved
Inclusion Criteria:
- Age > 18 and < 65.
- Meet DSM-IV criteria for MDD (n=5), BD (n=5), or healthy controls with no psychiatric
diagnosis (n=5).
- Willing and able to wear a wearable device to measure sleep parameters
- Willing and able to provide voice samples.
- Subjects with MDD must not be taking psychiatric medications at the time of
evaluation.Subjects with BD can be taking psychiatric medications, since it is not
feasible for patients with BD to be completely free of mood stabilizing medications.
These medications will be limited to lithium, second generation antipsychotics.
- Currently a patient or research participant at the DCRP or the BCRP or are healthy
controls enrolled in evaluation studies.
Exclusion Criteria:
- Primary sleep disorder, including restless legs syndrome, difficulties in initiating
and maintaining sleep.
- Movement disorders (e.g. Parkinson's, Huntington's, tardive dyskinesia, primary
chorea).
- Active substance abuse or dependence in the past 3 months.
- Cardiovascular or pulmonary disease, including uncontrolled hypertension,
arrhythmias, history of myocardial infarction, asthma, COPD, or pulmonary carcinoma.
- Cardiovascular or pulmonary medications (aspirin and statins are allowable).
- Anticonvulsants.
- Sedative/hypnotics (e.g. benzodiazepines, eczopiclone).
- Smokers.
- Pregnancy.
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