Characterizing Cognitive Impairment in Schizophrenia via Computational Modeling a

通过计算模型描述精神分裂症的认知障碍

• 批准号: 8715432
• 负责人: ALAN ANTICEVIC
• 金额: $ 35.48万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-25 至 2017-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8715432
• 关键词: Behavior; Behavioral; Belief; Biological Assay; Brodmann' s area; Cells; Clinical; Cognition; Cognitive; Cognitive deficits; Computer Simulation; Data; Diagnosis; Disease; Environment; Equilibrium; Feedback; Feeling; Foundations; Functional Magnetic Resonance Imaging; Functional disorder; Glutamate Receptor; Goals; Human; Impaired cognition; Individual; Ketamine; Lateral; Link; Maintenance; Measurable; Mental disorders; Methodology; Methods; Mind; Modeling; Molecular; N-Methyl-D-Aspartate Receptors; N-Methylaspartate; Neurophysiology - biologic function; Neurosciences; Output; Pathology; Patients; Perception; Performance; Pharmaceutical Preparations; Plant Roots; Predisposition; Prefrontal Cortex; Process; Psychiatry; Recruitment Activity; Recurrence; Research; Schizophrenia; Short-Term Memory; Source; Symptoms; Synapses; System; Testing; Thinking; Translating; Work; base; cognitive function; design; distraction; functional disability; healthy volunteer; improved; innovation; mathematical model; models and simulation; neuroimaging; neuromechanism; neuropathology; neuropsychiatry; novel; operation; psychopharmacologic; public health relevance; receptor function; relating to nervous system; success; tool

DESCRIPTION (provided by applicant): The field of psychiatry has made substantial progress towards understanding mental illness using basic neuroscience methods, but the explanatory gap between cellular hypotheses and clinical phenomena remains vast. This gap is particularly evident in our understanding of schizophrenia, a devastating disorder whose core feature is disrupted cognition. Schizophrenia patients present with debilitating cognitive deficits, not adequately treated by available therapies. Understanding and restoring cognitive function is critical to improving patients' lives. One way to close this gap is to investigate the clinical phenomena by combining several scientific methodologies, at multiple levels of analysis. Therefore, this proposal broadly aims to align functional neuroimaging with biophysically-realistic computational models of neural function and to test model predictions using safe and reversible pharmacological manipulations in healthy volunteers. It further aims to directly compare findings to deficits observed in schizophrenia patients. Ultimately, the current proposal will bridge levels of explanation to mechanistically understand cognitive dysfunction in schizophrenia. One severely compromised cognitive operation in schizophrenia is working memory: the ability to temporarily hold and manipulate information in mind. Disruptions in working memory compromise patients' ability to track thoughts, ideas, and feelings, severely limiting even basic functioning. Although functional neuroimaging studies repeatedly link working memory disturbances to prefrontal dysfunction, synaptic mechanisms remain elusive. One leading hypothesis proposes disruption in the balance of excitation and inhibition in cortical micro-circuitry caused by hypo-function of the N-methyl-D-aspartate (NMDA) glutamate receptor. However, to test this hypothesis in relation to disrupted cognition, and to ultimately develop medications that alleviate cognitive dysfunction in schizophrenia, we need to go a step beyond neuroimaging. We need an understanding of working memory dysfunction at the level of cellular mechanisms, which is where treatments are developed. The specific aims of this proposal are: i) to extend an established biophysically-realistic computational model of working memory to 'mimic' hypothesized NMDA receptor pathology and use it to make behavioral and neural predictions regarding deficits observed in schizophrenia; ii) experimentally test those predictions using a leading safe pharmacological model of schizophrenia that perturbs the precise mechanism in healthy volunteers, namely transient NMDA antagonism via ketamine; iii) to relate these pharmacological results to deficits observed in patients using behavior and functional neuroimaging. The proposed project will close the explanatory gap and help develop a multi-level mechanistic understanding of cognitive dysfunction in schizophrenia. Ultimately, the success of this research will fertilize rationally-guided treatments and improve the lives of people suffering from this devastating disorder.

描述(由申请人提供)：精神病学领域在使用基本神经科学方法理解精神疾病方面取得了实质性进展，但细胞假说和临床现象之间的解释差距仍然很大。这一差距在我们对精神分裂症的理解中尤为明显，精神分裂症是一种毁灭性的疾病，其核心特征是认知障碍。精神分裂症患者存在衰弱的认知缺陷，没有得到现有治疗方法的充分治疗。了解和恢复认知功能是改善患者生活的关键。缩小这一差距的一种方法是通过在多个分析水平上结合几种科学方法来调查临床现象。因此，这项建议的主要目的是使功能神经成像与神经功能的生物物理现实计算模型保持一致，并使用安全和可逆的药物操作在健康志愿者中测试模型预测。它还旨在将研究结果与在精神分裂症患者中观察到的缺陷进行直接比较。最终，目前的提议将架起解释层面的桥梁，以机械地理解精神分裂症的认知功能障碍。精神分裂症患者的一种严重损害的认知操作是工作记忆：在脑海中暂时持有和操纵信息的能力。工作记忆的中断损害了患者追踪想法、想法和感觉的能力，甚至严重限制了基本功能。尽管功能神经成像研究一再将工作记忆障碍与前额叶功能障碍联系起来，但突触机制仍然难以捉摸。一个主要的假说提出，由于N-甲基-D-天冬氨酸(NMDA)谷氨酸受体功能低下，大脑皮质微电路的兴奋和抑制平衡被破坏。然而，为了测试这一假说与认知障碍的关系，并最终开发出缓解精神分裂症认知功能障碍的药物，我们需要超越神经成像。我们需要在细胞机制的水平上了解工作记忆障碍，这是开发治疗方法的地方。这项建议的具体目标是：i)扩展一个已建立的生物物理-现实工作记忆计算模型，以“模拟”假设的NMDA受体病理，并用它对精神分裂症中观察到的缺陷做出行为和神经预测；ii)使用领先的安全的精神分裂症药理学模型对这些预测进行实验验证，该模型扰乱了健康志愿者的精确机制，即通过氯胺酮进行短暂的NMDA拮抗；iii)将这些药理结果与患者使用行为和功能神经成像观察到的缺陷联系起来。拟议的项目将缩小解释上的差距，并有助于发展对精神分裂症认知功能障碍的多层次机械理解。最终，这项研究的成功将促进合理指导的治疗，并改善患有这种毁灭性疾病的人的生活。