The Research Core of Neuroscience-based Mental Health Assessment and Prediction (NeuroMAP) will provide the scientific infrastructure that supports all projects. The Research Core will utilize the Research Domain Criteria (RDoC) framework to provide a multilevel assessment, intervention, and analysis that cut across all projects consisting of assays for cells and molecules, circuits & physiology, symptoms & behavior, and a standardized intervention for longitudinal prediction as well as bioinformatics to apply sophisticated statistical approaches to generate clinically meaningful predictions. The multi-level assessment provided by the Research Core will focus on three domains: (a) positive valence (systems that support ?what makes us feel good?), (b) negative valence (systems that support ?what makes us feel bad?), and (c) interoception and arousal (systems that underlie the ?brain body connection?). Experienced investigators, who have developed a standardized pathway of acquiring and analyzing, will lead the components: (a) Cells and Molecules, i.e. standardized bioassays; (b) Circuits & Physiology, i.e. multimodal imaging by combining EEG and fMRI; (c) Symptoms & Behavior, i.e. standardized recruitment using PhenX measures and the NIH PROMIS system, and (d) Intervention, i.e. using a well-validated exposure and behavioral activation therapy. The Research Core will support the projects that will use a neuroscience-based multi-level assessment approach to (1) delineate the neural processing dysfunctions in individuals with mood, anxiety, and eating disorders, and (2) utilize these measures to predict clinically meaningful outcomes. This Core will provide the bioinformatics for the cross-sectional phase of the NeuroMAP investigator projects (Year 1-3) and apply machine-learning tools to generate predictions at a single subject level for the longitudinal phase of the projects (Year 3-5).
The specific aims are: (1) To provide a standardized multi-level assessment procedure for all NeuroMAP projects. (2) To support all NeuroMAP research infrastructure. (3) To create a trans-project repository of multi-level data. Creating a Research Core strikes a reasonable balance between centralizing most, but not all, assessment procedures. The NeuroMAP investigators are able to develop and utilize assessments that are germane to the specific project, but also rely on standardized procedures for the core domains. By pooling subjects across projects who have undergone standardized multilevel baseline assessments one can conduct secondary analyses of individual differences in individuals with mood, anxiety and eating disorders that may help to guide future research projects. In particular, this database will allow young investigators, e.g. postdoctoral fellows, associate investigators, or even graduate students, to generate new research questions and projects with patient populations relatively quickly and inexpensively. These projects can naturally evolve into future NeuroMAP projects if some of the current NeuroMAP investigators advance to independent investigators.
The Research Core will provide people, tools, and procedures to collect, process, and analyze the data in a standardized manner for the projects. The Core will focus on three domains, brain systems that support: (a) ?what makes us feel good?, (b) ?what makes us feel bad?, and (c) ?the brain body connection?. This core will assure that data are collected more quickly and efficiently than if these procedures were to be established by each investigator individually. By centralizing these aspects we will generate a uniform database, which will provide other young researchers as a resource to ask new questions and generate pilot results.
Cha, Yoon-Hee; Shou, Guofa; Gleghorn, Diamond et al. (2018) Electrophysiological Signatures of Intrinsic Functional Connectivity Related to rTMS Treatment for Mal de Debarquement Syndrome. Brain Topogr 31:1047-1058 |
Feinstein, Justin S; Khalsa, Sahib S; Yeh, Hung et al. (2018) The Elicitation of Relaxation and Interoceptive Awareness Using Floatation Therapy in Individuals With High Anxiety Sensitivity. Biol Psychiatry Cogn Neurosci Neuroimaging 3:555-562 |
DeVille, Danielle C; Kerr, Kara L; Avery, Jason A et al. (2018) The Neural Bases of Interoceptive Encoding and Recall in Healthy Adults and Adults With Depression. Biol Psychiatry Cogn Neurosci Neuroimaging 3:546-554 |
Hassanpour, Mahlega S; Luo, Qingfei; Simmons, W Kyle et al. (2018) Cardiorespiratory noise correction improves the ASL signal. Hum Brain Mapp 39:2353-2367 |
Ford, Bart N; Yolken, Robert H; Dickerson, Faith B et al. (2018) Reduced immunity to measles in adults with major depressive disorder. Psychol Med :1-7 |
Arabnejad, M; Dawkins, B A; Bush, W S et al. (2018) Transition-transversion encoding and genetic relationship metric in ReliefF feature selection improves pathway enrichment in GWAS. BioData Min 11:23 |
Al Zoubi, Obada; Ki Wong, Chung; Kuplicki, Rayus T et al. (2018) Predicting Age From Brain EEG Signals-A Machine Learning Approach. Front Aging Neurosci 10:184 |
Savitz, Jonathan; Harrison, Neil A (2018) Interoception and Inflammation in Psychiatric Disorders. Biol Psychiatry Cogn Neurosci Neuroimaging 3:514-524 |
Khalsa, Sahib S; Hassanpour, Mahlega S; Strober, Michael et al. (2018) Interoceptive Anxiety and Body Representation in Anorexia Nervosa. Front Psychiatry 9:444 |
Mucci, Viviana; Cha, Yoon-Hee; Wuyts, Floris L et al. (2018) Perspective: Stepping Stones to Unraveling the Pathophysiology of Mal de Debarquement Syndrome with Neuroimaging. Front Neurol 9:42 |
Showing the most recent 10 out of 11 publications