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

项目总结：总体 为了对环境做出适应性反应，大脑必须处理信息，以形成准确和稳定的 环境当前状态的表示法(“状态表示法”)。这需要精确的神经 前额叶和感觉系统之间以及前额叶网络内的活动时序同步。 我们的中心专注于统一的假设，即处理潜在的状态表征功能障碍的过程是 与精神病相关，提供了了解病理生理异质性和精确治疗的窗口。四 项目跨越三个物种(非人类灵长类动物、小鼠和人类)和八种方法(遗传 手法、切片生理学、合奏录音、LFP、行为、EEG、功能磁共振成像、认知训练)。我们使用一种 跨物种和方法进行翻译和整合的中心计算视角：变化 神经信息处理影响吸引子动力学和影响状态下的参数 陈述过程。这些变化在行为和神经生理学方面产生了明显的影响，我们 可以通过研究吸引子网络模型的透镜来了解我们的病理生理学 异质性、临床轨迹和精确治疗。 每个项目：1)使用相同的行为任务来探索不同物种的状态表征组件 和实验；2)访问并行的神经生理学指标，重点是神经系统活动计时， 兴奋-抑制平衡和噪声；3)使用高级数据驱动的因果发现分析，以促进 跨范式整合和新假说的产生。这些项目得到了翻译公司的支持 神经生理学核心、计算核心和管理核心。 目的1研究状态表征功能障碍的行为和神经生理学特征。 NMDA-R介导的精神病前额叶网络衰竭的非人灵长类动物模型中的精神病 信号(项目1)；在细胞类型特定的NMDA-R功能消融和携带性精神病的小鼠中- 相关基因变异(项目2)；以及来自对健康对照组和患有糖尿病的人的脑电-功能磁共振研究。 早期精神病(项目3)。目标2发展了状态表征的吸引子网络模型 细节层次，结合动物神经生理学的行为、突触和细胞微电路数据 研究(项目1和2)以确定说明状态表征功能障碍的参数 精神病的特征和对人类的行为和神经生理学观察 (项目3及4)。目标3和4侧重于状态表征的可靠性和预测意义 早期精神病的功能障碍，以及针对特定功能障碍的精确治疗方法。

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.