purcell lab

This is a non-exhaustive list ongoing projects (primarily computational tool/methods development) and collaborations (applying these tools to existing or new data collections led by others):

Data, tools and methods

• National Sleep Research Resource: working with founding-member Dr. Susan Redline, Dr. Purcell co-directs the NSRR, an NLBI-funded respository of data for sleep science [ link ]
• Luna: we are devloping a growing library of tools designed to work with large numbers of sleep studies, with a current focus on the sleep EEG [ link ]
• Personalized sleep staging: Dr. Purcell is PI of an NHLBI-funded R01 to support the development of methods to better capture between-individual variability in automated sleep staging, and to define new quantitative metrics, beyond traditional classification of sleep stages, to better capture individual differences in sleep
• Dynamics: Dr. Purcell is PI of an NHLBI-funded R21 to develop methods to better capture ultradian dynamics in sleep signals (patterns of change within a single night)

Sleep neurophysiology, psychiatric disease and genetics

• MARS: the Mood and Rhythms of Sleep project is a newly awarded, Wellcome Trust funded project to develop sleep-based objective biomarkers for bipolar disorder and major depression.
• The role of cerebellar cortical and thalamocortical circuits in bipolar disorder: with Dr. Jen Pan (Broad Institute) and others, this new and highly multi-discplinary project funded by Breakthrough Discoveries for thriving with Bipolar Disorder (BD²) will investigate the role of gene-driven dysfunction within key brain structures to create a framework for validating targets identified in human genetic studies and potentially uncover specific therapeutic opportunities for carriers of those risk factors.
• GRINS: the Global Research Initiative on the Neurophysiology of Schizophrenia is a collaboration with investigators at the Stanley Center, Broad Institute and Wuxi Mental Health Center (China), as well as other investigators at Mass General and McLean Hospitals. This project focuses on collecting high density sleep EEG and other measures in patients with schizophrenia and matched controls.
• Animal models: in collaboration with Dr. Jen Pan at the Stanley Cener for Psychiatric Research, Broad Institute, and others, we are studying the effects of human mutations associated with psychiatric disease, in vivo in the sleep EEG.
• Sleep EEG GWAS: leveraging genetically informative datasets in the NSRR, we aim to perform genome-wide association studies to link objective measures of sleep macro and micro architecture with genetic risk for psychiatric disease.

Sleep and cognitive aging

• MESA/MrOS: working with collaborators from the MESA and MrOS studies, we have characterized multiple facets of sleep macro and micro archtiecture in almost 4,000 older adults, showing how they change with age and predict cognitive performance. Next we will focus longitudinally, to look at changes in sleep and cognition over multiple years.
• Harvard Aging Brain Study: in a collaboraiton led by Jasmeer Chatwal and others, we will be investigating sleep neurophysiological metrics in relation to PET imaging markers of cognitive aging.
• Contributions of sleep to preclinical and clinical AD: we will be collaborating on a new study led by Drs. Jayandra Himali and Matthew Pase, on the links between sleep, brain morphometry and other imaging measures.

Sleep and cognitive development

• RASP and ESP studies: these ongoing projects aim to compile pediatric sleep studies, either using retropspective clinical studies, or prospectively collecting research studies, in order to evaluate the degree to which the development and maturation of sleep patterns relate to neurodevelopmental differences in young children. This is a multi-site collaboration with NIMH Intramural researchers and other sites (Boston Childrens, Geisinger, New York University, Baylor College of Medicine).
• NIMH toddlers study: we collaborate NIMH intramural researchers Drs. Ashura Buckley and Audrey Thurm, looking at how the sleep EEG of very young children predicts cognitive development.
• Sleep and cognitive development in children: we are characterizing developmental changes in the sleep EEG, with a focus on functional connectivity indexed by coherence analysis.

Sleep epidemiology and health

• Sleep, race and health disparities: working with collaborators at Harvard School of Public Health, Dr. Purcell is PI of a NIMHD-funded R21 to better measure which aspects of sleep might contribute to racial/ethnic disparities in health outcomes
• Normative studies for sleep biomarkers: if objective sleep metrics are ever to be used as clinically useful biomarkers, it will be important to first characterize baseline sources of variability in these measures, to find unbiased and reliable measures. This involves studying sleep biomarkers in large and diverse datasets, following our work on sleep spindles, for example.