Psychiatric disorders, as well as normal aging, are often associated with a wide range of cognitive changes. Recent developments in neuroscience, particularly multimodal neuroimaging techniques, can provide better understanding of neural mechanisms that underlie these changes. Mediation analysis is a popularly used statistical method to investigate neural mechanisms. However, existing statistical methods were not designed to accommodate such large-scale, multi-dimensional, and complicated data in mediation analysis. The overarching aim of my K01 Mentored Research Development Award is to acquire training that will allow me to pursue a line of mental health research related to cognition and to develop novel statistical methods to support the emerging research in cognitive neuroimaging and mental health. I propose to receive training in: 1) cognition and its relationship with aging and psychopathology; 2) neural basis in cognition and multimodal neuroimaging; 3) functional mediation and selective mediation analysis. This will provide me with the tools to conduct research that will fill significant gaps in the statistical analyses on cognitive neuroimaging, particularly focusing on aging and neurodegeneration-associated cognitive decline: First, I propose to review and develop analytic tools to examine how aging and psychopathology affect cognitive system constructs. Understanding the patterns of age-related differences in each of these cognitive constructs and the possible heterogeneity related to the psychopathology is of great importance. I will test nonlinearity and heterogeneity in the latent cognitive constructs using two independent large data. Second, I will develop and examine activation networks (reference ability neural networks (RANNs)) associated with each of the cognitive constructs. Although it is critical to understand underlying neural networks of cognition, there are many unsolved problems in investigating the presence or structure of RANNs. I will develop a method to derive underlying networks, find RANNs taking into account possible spatial overlap among RANNs, and investigate the relationship between RANNs expression and performance on the concomitant cognitive constructs. Third, I will develop selective mediation analyses to examine the relationship between imaged neural substrates of aging and psychiatric disorder, such as regional volume loss, and cognitive decline and test if the different imaged brain modalities selectively mediate cognitive aging by influencing the expression of cognitive ability constructs. In totality, this training and research will inform hypotheses for an R01 grant application to be submitted in Year 4 of the award period. While to date I have exemplified a productive research career in biostatistics and psychiatry, I need substantially more training for successful completion of the research proposed in this application and to make a lasting contribution to the field of mental health.

Public Health Relevance

The present application develops new statistical methods to examine neural mechanisms in the context of cognitive system constructs. The training and research proposed here will form the basis for developing a new line of statistical methods to identify functional neural mechanisms related to cognitive constructs and examine the role of brain in cognitive changes associated with psychiatric disorders. These inquires have substantial promise for mental health; accurate identification of functional and structural neural system and their mechanisms is crucial to better understanding mental illness and developing new treatments.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
1K01AG051348-01
Application #
8951241
Study Section
Neuroscience of Aging Review Committee (NIA)
Program Officer
Wagster, Molly V
Project Start
2015-09-30
Project End
2019-05-31
Budget Start
2015-09-30
Budget End
2016-05-31
Support Year
1
Fiscal Year
2015
Total Cost
Indirect Cost
Name
New York State Psychiatric Institute
Department
Type
DUNS #
167204994
City
New York
State
NY
Country
United States
Zip Code
10032
Lee, Seonjoo; Zimmerman, Molly E; Narkhede, Atul et al. (2018) White matter hyperintensities and the mediating role of cerebral amyloid angiopathy in dominantly-inherited Alzheimer's disease. PLoS One 13:e0195838
Franzmeier, Nicolai; Düzel, Emrah; Jessen, Frank et al. (2018) Left frontal hub connectivity delays cognitive impairment in autosomal-dominant and sporadic Alzheimer's disease. Brain 141:1186-1200
Cheran, Gayathri; Silverman, Hannah; Manoochehri, Masood et al. (2018) Psychiatric symptoms in preclinical behavioural-variant frontotemporal dementia in MAPT mutation carriers. J Neurol Neurosurg Psychiatry 89:449-455
Kreisl, William Charles; Jin, Peng; Lee, Seonjoo et al. (2018) Odor Identification Ability Predicts PET Amyloid Status and Memory Decline in Older Adults. J Alzheimers Dis 62:1759-1766
Lee, Seonjoo; Habeck, Christian; Razlighi, Qolamreza et al. (2016) Selective association between cortical thickness and reference abilities in normal aging. Neuroimage 142:293-300
Lee, Seonjoo; Viqar, Fawad; Zimmerman, Molly E et al. (2016) White matter hyperintensities are a core feature of Alzheimer's disease: Evidence from the dominantly inherited Alzheimer network. Ann Neurol 79:929-39
Lee, Seonjoo; Zipunnikov, Vadim; Reich, Daniel S et al. (2015) Statistical image analysis of longitudinal RAVENS images. Front Neurosci 9:368