Predicting Cognitive Resilience Against Sleep Loss
Status: | Completed |
---|---|
Conditions: | Insomnia Sleep Studies |
Therapuetic Areas: | Psychiatry / Psychology |
Healthy: | No |
Age Range: | 20 - 45 |
Updated: | 5/5/2014 |
Start Date: | April 2013 |
End Date: | October 2014 |
Contact: | Hannah Gogel |
Email: | hgogel@mclean.harvard.edu |
Phone: | 617-855-2238 |
Multimodal Neuroimaging to Predict Cognitive Resilience Against Sleep Loss
Resilience is the ability to cope effectively and adapt to a wide range of stressful
environmental challenges. Sleep loss has been shown to reduce activity in the brain regions
responsible for resilience. The ability to resist the effects of sleep loss appears to be a
stable, trait-like quality. This study will attempt to predict individuals' trait-resistance
to sleep loss based on their neurobiology.
environmental challenges. Sleep loss has been shown to reduce activity in the brain regions
responsible for resilience. The ability to resist the effects of sleep loss appears to be a
stable, trait-like quality. This study will attempt to predict individuals' trait-resistance
to sleep loss based on their neurobiology.
Resilience, the ability to cope effectively and adapt to a wide range of stressful
environmental challenges, appears to be mediated extensively by the medial prefrontal cortex
(MPFC). Sleep deprivation has been shown to reduce metabolic activity throughout the brain,
particularly the MPFC. The ability to resist the effects of sleep loss appears to be a
stable, trait-like phenomenon that is consistent across situations, suggesting that it may
reflect an enduring quality of the underlying neurobiological system. The present study aims
to identify the neural basis of resilience and effectively discriminate resistant from
vulnerable individuals during an overnight sleep deprivation session. Specifically, the
primary aims of this research are 1) to further our understanding of the role of the MPFC in
resilience and 2) to develop a statistical prediction algorithm based on multimodal
neuroimaging that will reliably discriminate between individuals who are resilient versus
vulnerable to the cognitive impairing effects of sleep loss.
environmental challenges, appears to be mediated extensively by the medial prefrontal cortex
(MPFC). Sleep deprivation has been shown to reduce metabolic activity throughout the brain,
particularly the MPFC. The ability to resist the effects of sleep loss appears to be a
stable, trait-like phenomenon that is consistent across situations, suggesting that it may
reflect an enduring quality of the underlying neurobiological system. The present study aims
to identify the neural basis of resilience and effectively discriminate resistant from
vulnerable individuals during an overnight sleep deprivation session. Specifically, the
primary aims of this research are 1) to further our understanding of the role of the MPFC in
resilience and 2) to develop a statistical prediction algorithm based on multimodal
neuroimaging that will reliably discriminate between individuals who are resilient versus
vulnerable to the cognitive impairing effects of sleep loss.
Inclusion Criteria:
- Age 20-45 years
- Right handedness as assessed by the Edinburgh Handedness Inventory
- For women: regular menstrual cycles (duration between 25 and 35 days with no more
than 3 day variation between cycle)
Exclusion Criteria:
- History of head injury with loss of consciousness or post-traumatic amnesia, or major
neurological illness
- Medical or neurologic condition that would confound interpretation of results,
including alcohol or drug abuse/dependence in the past 6 months, neurological
disorders including any history of seizures
- History of cardiac problems
- History of major depressive disorder or anxiety disorder
- Lifetime history of psychotic disorder, including bipolar disorder, schizophrenia, or
obsessive compulsive disorder
- Other DSM-IV diagnosis that could affect interpretation of results
- Mixed or left handedness
- Abnormal visual acuity that cannot be corrected by contact lenses
- Daily caffeine use exceeding 400 mg per day
- History of smoking or tobacco use in the past year
- Metal within the body, pregnancy, or other contraindication for MRI procedures
- Use of drugs or medications that could affect functional neuroimaging results (e.g.,
fluoxetine, beta-blockers)
- Psychotropic medication use within the past 6 weeks
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