权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Dysfunctional State Representations in Psychosis: From Neurophysiology to Neuroplasticity-based Treatment

精神病中的功能障碍状态表征：从神经生理学到基于神经可塑性的治疗

基本信息

批准号：
10597064
负责人：
A DAVID REDISH
金额：
$ 306.1万
依托单位：
UNIVERSITY OF MINNESOTA
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-04-01 至 2025-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10597064
关键词：
Ablation Affect Behavior Behavioral Brain Characteristics Clinical Computer Models Data Data Analyses Electroencephalography Environment Equilibrium Expectancy Failure Feedback Functional Magnetic Resonance Imaging Functional disorder Generations Heterogeneity Human Leadership Learning Mediating Mental disorders Methodology Modeling Modification Mus N-Methylaspartate Neuronal Plasticity Noise Outcome Parameter Estimation Participant Patient Recruitments Patients Pattern Performance Persons Physiology Precision therapeutics Process Psychopathology Psychoses Randomized Regimen Reversal Learning Role Signal Transduction Slice Structure Subgroup Synapses System Testing Training Translating Variant animal data behavior measurement cell type cognitive training computational neuroscience data acquisition data modeling early psychosis experimental study functional magnetic resonance imaging/electroencephalography genetic manipulation genetic variant improved lens network models neural neural information processing neurophysiology nonhuman primate novel sensory system treatment as usual

项目摘要

PROJECT SUMMARY: OVERALL To respond adaptively to the environment, the brain must process information to develop accurate and stable representations of the current state of the environment (“state representation”). This requires precise neural activity timing synchrony between prefrontal and sensory systems and within prefrontal networks. Our Center focuses on the unifying hypothesis that processes underlying state representation dysfunction are relevant to psychosis, providing a window into pathophysiologic heterogeneity and precision treatment. Four Projects span three species (nonhuman primates, mice, and humans) and eight methodologies (genetic manipulations, slice physiology, ensemble recordings, LFP, behavior, EEG, fMRI, cognitive training). We use a central computational perspective to translate and integrate across species and methodologies: Changes in neural information processing affect parameters underlying attractor dynamics and influence state representation processes. Such changes create observable effects in behavior and neurophysiology, which we can study through the lens of attractor network models to inform our understanding of pathophysiologic heterogeneity, clinical trajectories, and precision treatment. Each Project: 1) Uses the same behavioral tasks to probe components of state representation across species and experiments; 2) Accesses parallel neurophysiologic metrics, with a focus on neural system activity timing, excitatory-inhibitory balance, and noise; 3) Uses advanced data-driven causal discovery analyses to facilitate cross-paradigm integration and novel hypothesis generation. The Projects are supported by a Translational Neurophysiology Core, a Computational Core, and an Administrative Core. Aim 1 investigates behavior and neurophysiology of state representation dysfunctions characteristic of psychosis in a nonhuman primate model of prefrontal network failure in psychosis mediated through NMDA-R signaling (PROJECT 1); in mice with cell type-specific ablation of NMDA-R function and carrying psychosis- associated genetic variants (PROJECT 2); and from an EEG-fMRI study of healthy controls and people with early psychosis (PROJECT 3). Aim 2 develops attractor network models of state representation at multiple levels of detail, incorporating behavioral, synaptic, and cellular microcircuit data from animal neurophysiology studies (PROJECTS 1 & 2) to identify parameters that account for state representation dysfunctions characteristic of psychosis and the behavioral and neurophysiological observations made in humans (PROJECTS 3 & 4). Aims 3 and 4 focus on reliability and predictive significance of state representation dysfunctions in early psychosis, and precision treatment approaches targeting specific dysfunctions.

项目总结：总体