Systems-Level Dysconnectivity in First Episode Psychosis

精神分裂症(Sz)是一种令人衰弱的主要精神疾病，具有终生残疾，给 医疗保健系统和社会。尽管经过了几十年的研究，但疾病的病理生理学的潜在机制 SZ是未知的。确定Sz的大脑异常的尝试已经超越了寻找一到几个 病变部位侧重于系统级脑回路和相关脑区之间的功能(Dys)连接 跨分布式电路的信息功能集成失败的基础神经事件。有效 连通性是指一个区域的活动对稍后另一个区域的活动的影响，允许进行推断 关于方向性。我们最重要的假设是，远程大脑皮层的有效连通性是 精神分裂症的生物系统异常，特别是前额叶皮质和感觉区域之间的异常。这 建议包括对分布式系统中的结构、功能和连接性进行系统级别的检查 已知在Sz、颞叶听觉皮质和额叶下回听觉执行功能受损 大脑皮质参与了失配负波(MMN)的产生，MMN是自动检测听觉变化的指标。 我们将检查该分布式系统的节点之间的有效连接，并使用计算建模 将脑电和脑磁图的神经生理信息转化为突触电导，表明可能 系统水平缺陷的分子机制。我们方法的核心是在个人的第一次测试中 精神分裂症谱系精神病的临床接触者(首发精神分裂症谱系，FESZ)， 进行性原发和继发性疾病对大脑结构和功能的影响被降至最低。病理生理学 发病近端很可能反映了疾病病因学的关键过程。在FESz中，我们测试了3个听觉 增加模式复杂性的测试对听觉变化检测系统进行差异化征税，测量大脑 结合高时间分辨率脑电和脑磁图的神经生理学测量，并构建 脑结构的高空间分辨率测量将传感器活动投射到皮层来源，比较和 FESz与井个体(AIM 1)的比较。使用光谱有效连通性的高级测量 (相转移熵)在震源分辨活动上，我们将确定额叶和 这些任务中FESz的颞叶皮质来源(AIM 2)。接下来，使用层流大脑皮层的计算模型 电路来替换每个声源上的单个等效偶极子，我们将在 AMPA、GABA和NMDA活性可能是FESz连接障碍的基础(AIM 3)。最后，评估 精神病发作后大脑结构、功能和连通性的变化，我们将测试参与者 6个月后纵向追踪进行性损害(目标4)。我们相信研究这种相互作用 在自下而上和自上而下的皮质过程之间显示出理解基本分子的巨大希望 预测编码、学习、记忆、注意力和其他关键大脑功能的机制似乎是 被Sz妥协了。

Schizophrenia (Sz) is a debilitating major mental illness with life-long disability that disproportionately burdens the healthcare system and society. Despite decades of research, the underlying mechanisms of pathophysiology in Sz are unknown. Attempts for determining brain abnormalities in Sz have gone beyond searching for one to a few lesion locations to focusing on functional (dys)connectivity between systems-level brain circuits and the associated neural events that underlie the failure in functional integration of information across distributed circuits. Effective connectivity refers to the influence of activity in one area on activity in another at a later time, allowing inferences about directionality. Our overarching hypothesis is that long-range cortical effective connectivity is a fundamental biological system abnormality in schizophrenia, particularly between prefrontal cortex and sensory areas. This proposal comprises a systems-level examination of structure, function, and connectivity in a distributed system known to be impaired in Sz, the temporal lobe auditory cortices and the inferior frontal gyrus auditory-executive cortex involved in the generation of mismatch negativity (MMN), an index of automatic auditory change detection. We will examine effective connectivity between nodes of this distributed system, and use computational modeling to translate neurophysiological information from EEG & MEG to synaptic conductances, indicating possible molecular mechanisms of the systems-level deficits. Central to our approach is testing of individuals at their first clinical contact for schizophrenia-spectrum psychosis (first episode schizophrenia-spectrum, FESz), where the progressive primary and secondary disease effects on brain structure and function are minimized. Pathophysiology proximal to disease onset very likely reflects processes critical to disease etiology. In FESz, we test 3 auditory tests of increasing pattern complexity to differentially tax the auditory change detection system, measure brain activity with combined high-temporal resolution EEG & MEG measures of neurophysiology, and construct high-spatial resolution measures of brain structure to project sensor activity to cortical sources, compared and contrasted between FESz and well individuals (AIM 1). Using advanced measures of spectral effective connectivity (phase transfer entropy) on the source-resolved activity, we will determine dysconnectivity between the frontal and temporal cortical sources in FESz on these tasks (AIM 2). Next, using computational modeling of a laminar cortical circuit to replace single equivalent dipoles at each source, we will determine synaptic conductance deficits in AMPA, GABA, and NMDA activity that may underlie the dysconnectivity in FESz (AIM 3). Finally, to assess changes in brain structure, function, and connectivity after the onset of psychosis, we will test participants longitudinally 6 months later to track progressive impairments (AIM 4). We believe studying the interactions between bottom-up and top-down cortical processes shows great promise for understanding the basic molecular mechanisms of predictive coding, learning, memory, attention, and other key brain functions that seem to be compromised by Sz.