The Social Brain in Schizophrenia and Autism Spectrum Disorders

精神分裂症和自闭症谱系障碍的社交大脑

• 批准号: 8371649
• 负责人: Michal Assaf
• 金额: $ 59.47万
• 依托单位: HARTFORD HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-05 至 2017-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8371649
• 关键词: Age; Anterior; Base of the Brain; Behavioral; Biological; Brain; Categories; Characteristics; Clinical; Clinical Research; Cluster Analysis; Cognitive; Data; Development; Diagnosis; Diagnostic; Diagnostic Procedure; Dimensions; Disease; Electroencephalography; Empathy; Etiology; Event-Related Potentials; Functional Magnetic Resonance Imaging; Functional disorder; Genetic; Genetic Risk; Goals; Group Identifications; Heterogeneity; Human; Image; Investigation; Joints; Judgment; Linear Models; Maintenance; Maps; Matched Group; Measures; Medial; Mental disorders; Methods; Mind; Modality; Nature; Neurodevelopmental Disorder; Neurons; Neurophysiology - biologic function; Pain; Participant; Pathology; Patient Self-Report; Patients; Pattern; Play; Prefrontal Cortex; Procedures; Process; Protocols documentation; Psychiatric Diagnosis; Questionnaires; Research; Resolution; Role; Schizophrenia; Severities; Social Functioning; Social Interaction; Subgroup; Symptoms; Techniques; Testing; autism spectrum disorder; base; behavior measurement; cingulate cortex; clinical Diagnosis; computerized; endophenotype; independent component analysis; innovation; neuroimaging; neuropathology; neurophysiology; outcome forecast; relating to nervous system; response; social; social cognition; theories; tool; treatment response; treatment strategy

DESCRIPTION (provided by applicant): Although traditionally considered 2 separate entities based on clinical symptoms and course, schizophrenia (SZ) and autism spectrum disorders (ASD) are heterogeneous, neurodevelopmental disorders with core deficits in social functions. Little is known, however, about the neuropathology associated with these abnormalities in these diagnoses or about the degree and nature of overlap between them. The aim of the current study is to investigate the neural correlates of 3 social cognitive processes, Theory of Mind (ToM), social judgment, and empathy, using a multimodal approach incorporating functional MRI (fMRI) and event related potential (ERP) data, in relation to the nosological diagnoses of ASD and SZ and their clinical and functional symptoms. Eighty SZ and 80 high-functioning ASD patients, ages 18-30, as well as matched healthy controls (HC) will complete the protocol. Participants' social functions will be characterized with self-report questionnaires, computerized tests, role-play and observational tools. Neuronally, ToM will be evaluated with a 2-player interactive fMRI Domino task, social judgment with an fMRI Trustworthiness task and empathy with an ERP Empathy to Pain task. We will (1) identify group differences based on categorical diagnostic mapping in social functions and social cognition-related neural deficits. We will further relate patients' social functions and symptoms to abnormal activation of specific brain circuits; (2) Identify patient sub-groups based on integrated multi-modal neural abnormalities related to social cognitive processes, independent of symptom-based diagnostic categories. We will first use an innovative data-driven method, joint independent component analysis (jICA), to fuse the data from all imaging tasks and to identify the upper 30% impaired patients (either SZ or ASD) and 30% of patients most similar to HC, based on brain activity during the different social tasks. The clinical characteristics of these subgroups will be further evaluated. Then the jICA most discriminative single or integrated components will be entered into a cluster ICA (cICA) to identify natural patient subgroups independently of formal clinical diagnosis. We hypothesize that while both SZ and ASD groups will show abnormal social functions and related brain activity compared to HC, some findings will overlap while others will be diagnosis specific. Importantly, we anticipate that the non-diagnostic based analyses (aim 2) will demonstrate the ability of brain based classifying procedures to identify neurobiologically-based patient subgroups that are more homogeneous than current symptom based categories with respect to clinical and behavioral characteristics. Such subgroups can then be evaluated with regard to differential treatment response and possible etiologies, such as genetic risk variables. If successful, the current study will support the emerging shift in clinical and research paradigms for ASD and SZ specifically and more generally for psychiatric illnesses, toward using dimensional biological (vs. categorical behavioral) measures to identify meaningful patient groups. This in turn will advance etiologic and treatment research for these illnesses. PUBLIC HEALTH RELEVANCE: The goals of the current proposal are (1) to characterize the commonalities and differences related to social- processes between autism spectrum disorders (ASDs) and schizophrenia (SZ) patients, by directly comparing their social functions and fMRI and ERP brain activity during several social cognitive process tasks; and (2) to use the neurophysiological features of social cognition as a dimensional classifier of patients into more natural and meaningful sub-groups. These biologically defined subgroups are potentially more advantageous than traditional symptom-based categorical diagnoses for future research on illness etiologies and treatments.

描述（由申请人提供）：虽然传统上根据临床症状和病程被认为是两个独立的实体，但精神分裂症 (SZ) 和自闭症谱系障碍 (ASD) 是异质性神经发育障碍，具有社会功能的核心缺陷。然而，人们对这些诊断中与这些异常相关的神经病理学或它们之间重叠的程度和性质知之甚少。本研究的目的是使用结合功能性 MRI (fMRI) 和事件相关电位 (ERP) 数据的多模式方法，研究 3 个社会认知过程、心智理论 (ToM)、社会判断和同理心的神经相关性，与 ASD 和 SZ 的疾病诊断及其临床和功能症状相关。 80 名 18-30 岁的 SZ 和 80 名高功能 ASD 患者以及匹配的健康对照 (HC) 将完成该方案。参与者的社会功能将通过自我报告问卷、计算机化测试、角色扮演和观察工具来表征。在神经元方面，ToM 将通过 2 人交互式 fMRI 多米诺任务进行评估，通过 fMRI 可信度任务进行社会判断评估，并通过 ERP 同理心任务进行同理心评估。我们将（1）根据社会功能和社会认知相关神经缺陷的分类诊断图来识别群体差异。我们将进一步将患者的社会功能和症状与特定脑回路的异常激活联系起来； (2) 根据与社会认知过程相关的综合多模式神经异常来识别患者亚组，独立于基于症状的诊断类别。我们将首先使用创新的数据驱动方法，即联合独立成分分析 (jICA)，融合所有成像任务的数据，并根据不同社交任务期间的大脑活动来识别最高 30% 的受损患者（SZ 或 ASD）和与 HC 最相似的 30% 患者。这些亚组的临床特征将得到进一步评估。然后，jICA 最具辨别力的单个或集成组件将被输入到集群 ICA (cICA) 中，以独立于正式的临床诊断来识别自然患者亚组。我们假设，虽然与 HC 相比，SZ 组和 ASD 组都会表现出异常的社会功能和相关的大脑活动，但一些发现会重叠，而另一些则为特定诊断。重要的是，我们预计基于非诊断的分析（目标 2）将证明基于大脑的分类程序能够识别基于神经生物学的患者亚组，这些亚组在临床和行为特征方面比当前基于症状的类别更加同质。然后可以根据不同的治疗反应和可能的病因（例如遗传风险变量）来评估此类亚组。如果成功，当前的研究将支持 ASD 和 SZ 的临床和研究范式的新兴转变，特别是更普遍的精神疾病，转向使用维度生物学（相对于分类行为）测量来识别有意义的患者群体。这反过来又将推进这些疾病的病因学和治疗研究。 公共健康相关性：当前提案的目标是（1）通过直接比较自闭症谱系障碍（ASD）和精神分裂症（SZ）患者在几个社会认知过程任务中的社会功能以及功能磁共振成像和ERP大脑活动，来表征自闭症谱系障碍（ASD）和精神分裂症（SZ）患者之间与社会过程相关的共性和差异； （2）利用社会认知的神经生理学特征作为患者的维度分类器，将其分为更自然和更有意义的亚组。这些生物学定义的亚组可能比传统的基于症状的分类诊断更有利于未来疾病病因和治疗的研究。