Neural mechanisms of sensory predictions in schizophrenia with hallucinations

精神分裂症幻觉感觉预测的神经机制

基本信息

批准号：
9262998
负责人：
Guillermo Horga
金额：
$ 19.63万
依托单位：
NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-06-01 至 2019-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9262998
关键词：
Animal Model Auditory Auditory Hallucination Auditory area Award Belief Brain Chronic Clinical assessments Code Cognition Computer Simulation Computing Methodologies Cues Development Disease Economic Burden Environment Ethics Event Experimental Designs Fostering Functional Magnetic Resonance Imaging Functional disorder Funding Future Generations Goals Hallucinations Hearing Homelessness Human Hybrids Imprisonment Lead Learning Life Expectancy Light Link Magnetic Resonance Maps Medical Mentors Methods Modeling Neurobiology Neurosciences Research Participant Patients Perception Pharmacotherapy Phenotype Phonation Probability Process Psychotic Disorders Recording of previous events Refractory Research Research Personnel Research Proposals Research Training Resources Rest Risk Role Schizophrenia Sensory Signal Transduction Speech Speech Discrimination Stimulus Symptoms Telephone Testing Thalamic structure Time Training Training Programs Unemployment United States National Institutes of Health Verbal Auditory Hallucinations Voice Vulnerable Populations Work analytical method attenuation base brain abnormalities brain dysfunction career computational neuroscience design disability expectation experience experimental study functional outcomes imaging approach imaging modality improved insight neural correlate neurobiological mechanism neuroimaging neuromechanism neuropsychiatric disorder new therapeutic target novel novel strategies patient oriented research persistent symptom programs psychotic symptoms public health relevance relating to nervous system response sensory cortex sensory mechanism sensory stimulus sensory system social therapy development

项目摘要

DESCRIPTION (provided by applicant): Active psychosis in schizophrenia is among the most severe and burdensome medical conditions worldwide. However, the mechanisms of psychotic symptoms in this disorder, such as hallucinations (i.e., abnormal percepts in the absence of external sensory stimuli), remain elusive. This K23 application presents a research and training program that will support the applicant on a path towards becoming an NIH-funded independent investigator focused on the application of functional neuroimaging to the study of psychotic symptoms in schizophrenia. The activities in this application build on the candidate's prior training and are set in a resource-rich environment that will foster his development of expertise in (1) advanced analytic methods and study conduct for functional magnetic resonance imaging (fMRI) research; (2) computational neuroscience; (3) perception and cognition research; (4) pathophysiology and clinical assessment of schizophrenia; and (5) responsible and ethical conduct in scientific research with vulnerable populations. Combining functional magnetic resonance imaging (fMRI) and computational modeling, the current research proposal seeks to (1) define the neural mechanisms that generate hallucinations in schizophrenia; and (2) inform the development of a computational model of hallucinations based on predictive coding, an empirically-validated theoretical framework that supports a role of sensory systems in learning and predicting regularities in the external environment. The overarching hypothesis is that abnormal prediction-based attenuation of sensory cortical function produces excessive activity in the sensory cortex that generates hallucinations. To test this hypothesis, the present study will employ a novel speech discrimination fMRI paradigm, two groups of patients with schizophrenia, those with active, frequent auditory verbal hallucinations and those without a significant history of hallucinations, and a third group of healthy controls. This design will allo for testing a direct link between dysfunction in sensory predictive-coding mechanisms and the online experience of hallucinations in patients with schizophrenia, and will thus inform the neurobiological basis of psychotic symptoms in this disorder. Together, this training and research program will facilitate the candidate's transition to an independent research career and will help identify new therapeutic targets for refractory psychosis. RELEVANCE: The novel application of the predictive-coding framework and model-based fMRI to the study of psychotic symptoms will shed new light on the mechanisms of generation of psychotic symptoms, thus filling an important gap in schizophrenia research. This project will serve to develop an explanatory model of hallucinations that can be used to generate specific, testable hypotheses for future neuroscience research in both humans and non-human animal models, and to uncover novel targets (sensory prediction deficits) likely modifiable by treatment via learning or pharmacotherapy.

描述（由申请人提供）：精神分裂症中的积极精神病是全球最严重，最繁重的医疗状况之一。然而，这种疾病中精神病症状的机制，例如幻觉（即在没有外部感觉刺激的情况下异常感知）仍然难以捉摸。该K23应用程序提出了一项研究和培训计划，该计划将支持申请人迈向成为NIH资助的独立研究者，该研究人员致力于将功能性神经影像应用于精神分裂症的精神病症状研究。本申请中的活动以候选人的先前培训为基础，并设置在资源丰富的环境中，该环境将促进他在（1）高级分析方法和功能磁共振成像（fMRI）研究方面的专业知识的发展；（2）计算神经科学；（3）感知和认知研究；（4）精神分裂症的病理生理学和临床评估；（5）与弱势群体的科学研究中负责和道德行为。当前的研究建议结合了功能磁共振成像（fMRI）和计算建模，试图（1）定义在精神分裂症中产生幻觉的神经机制；（2）为基于预测编码的幻觉计算模型的开发，这是一个经验验证的理论框架，该框架支持感觉系统在学习和预测外部环境中规律性方面的作用。总体假设是，基于预测的感觉皮质功能的衰减会在产生幻觉的感觉皮质中产生过度活性。为了检验这一假设，本研究将采用一种新的语音歧视fMRI范式，两组精神分裂症患者，具有活跃的，频繁的听觉言语幻觉的患者，以及没有重要幻觉病史的患者以及第三组健康的对照。这种设计将在感官预测编码机制中的功能障碍与精神分裂症患者幻觉的在线经验之间进行直接联系，因此将为这种疾病中精神病的神经生物学基础提供信息。这项培训和研究计划将共同促进候选人向独立研究职业的过渡，并有助于确定难治性精神病的新治疗靶标。相关性：预测编码框架和基于模型的fMRI在精神病症状研究中的新颖应用将为精神病症状的产生机理提供新的启示，从而填补了精神分裂症研究的重要空白。该项目将有助于开发幻觉的解释模型，该模型可用于在人类和非人类动物模型中为未来的神经科学研究生成特定的，可检验的假设，并揭示可能通过学习或药物治疗来治疗的新目标（感觉预测缺陷）。