Trans-Diagnostic Relations Between Functional Brain Network Integrity and Cognition

 描述（由申请人提供）：认知障碍是精神健康障碍的一种致残特征，对精神分裂症、双相情感障碍和重度抑郁症患者的影响最严重。这些人群经历的认知缺陷与日常功能障碍有关，使认知成为治疗和干预的关键目标。尽管需要治疗，但尚不清楚精神分裂症、双相情感障碍和抑郁症患者经历的认知障碍是否具有不同的病因，需要开发不同的干预措施，或者类似的治疗是否对所有三个临床组有效。因此，更好地了解这些缺陷如何与诊断组中的神经生物学异常相关，是干预和补救认知障碍的重要下一步。目前的项目通过评估诊断组之间大脑网络组织的差异，并测试有关这些差异如何与认知能力相关的假设，直接解决了这一步骤。研究表明，功能性大脑网络的组织和完整性支持认知功能，如记忆，执行功能和处理速度。因此，我们假设这些网络的组织可以提供与精神疾病相关的神经生物学异常的重要见解。该研究的第一个目的是测量被认为支持高阶认知的功能网络的效率，即额顶叶网络（FPN）和扣带-盖网络（CON），在精神分裂症、双相情感障碍、抑郁症和健康对照个体中。使用图论算法计算的网络效率的差异将用于预测诊断组内和诊断组之间的工作记忆、情景记忆、执行功能和处理速度任务的表现。此外，该研究的第二个目标将着眼于被称为枢纽的特定大脑区域，这些区域对于网络之间的信息传输特别重要。枢纽节点与其他网络通信的程度也将用于预测认知性能，以更好地了解特定大脑区域参与的减少是否会影响认知性能。我们预测，这些关系将在诊断组内和诊断组之间保持，并且不会观察到与组的相互作用，基于这样的假设，即认知和网络指标之间的关系在诊断组之间是相似的，但是这些指标的大小以分级的方式不同（对照组>抑郁症>双相型>精神分裂症）。通过这两个目标，我们可以更复杂地了解功能性大脑网络组织如何与认知缺陷相关，以及这些关系是否因诊断状态而异。有了这些信息，可以对精神健康障碍异常的特异性进行更有针对性的预测，从而确定解决这些临床人群中认知障碍所需的治疗类型。

 DESCRIPTION (provided by applicant): Cognitive impairments are a disabling characteristic of mental health disorders, most severely impacting individuals with schizophrenia, bipolar disorder, and major depression. The cognitive deficits experienced by these populations are associated with impairments in daily functioning, making cognition a critical target for treatment and intervention. Despite this need for treatment, it remains unclear whether the cognitive impairments experienced by patients with schizophrenia, bipolar disorder, and depression have different etiologies requiring the development of distinct interventions, or whether similar treatments would be effective for all three clinical groups. Therefore, a better understanding of how these deficits are associated with neurobiological abnormalities across diagnostic groups is an important next step in efforts to intervene on and remediate cognitive impairment. The current project directly addresses this step by assessing differences in brain network organization across diagnostic groups, and testing hypotheses about how those differences relate to cognitive ability. Research has shown that the organization and integrity of functional brain networks supports cognitive functions such as memory, executive functioning, and processing speed. Therefore, we hypothesize that the organization of those networks could provide critical insights into neurobiological abnormalities associated with mental illness. The first aim of the study will measure the efficiency of functional networks believed to support higher-order cognition, the fronto-parietal network (FPN) and the cingulo- opercular network (CON), in individuals with schizophrenia, bipolar disorder, depression, and healthy controls. Differences in network efficiency, calculated using graph theoretic algorithms, will be used to predict performance on tasks of working memory, episodic memory, executive function, and processing speed, within and across diagnostic group. Additionally, the second aim of the study will look at specific brain regions known as hubs, which are particularly important for transmittin information between networks. The degree to which a hub node communicates with other networks will be used to predict cognitive performance as well, to gain a better sense of whether reductions in the participation of specific brain regions influences cognitive performance. We predict that these relationships will hold both within and across diagnostic group, and that no interactions with group will be observed, based on the hypothesis that relationships between cognition and network metrics are similar across diagnostic groups, but that the magnitude of those metrics differs in a graded fashion (controls>depression>bipolar>schizophrenia). Through these two aims, we can gain a more complex understanding of how functional brain network organization is associated with cognitive deficits, and also whether these relationships differ depending on one's diagnostic status. With this information, more targeted predictions can be made regarding the specificity of abnormalities across mental health disorders and therefore the types of treatments necessary for addressing cognitive impairments in these clinical populations.