Real time fMRI feedback and auditory processing in schizophrenia

精神分裂症的实时功能磁共振成像反馈和听觉处理

基本信息

  • 批准号:
    8509122
  • 负责人:
  • 金额:
    $ 18.21万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2013
  • 资助国家:
    美国
  • 起止时间:
    2013-06-10 至 2015-04-30
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Auditory verbal hallucinations (AH) have long been a hallmark of schizophrenia (SZ) symptomatology and one of its major diagnostic features (Andreasen and Flaum, 1991; DSM-IV). It has been demonstrated that the brain regions implicated in AH are involved in different aspects of language processing. This brain network includes the temporal cortex and especially the superior temporal gyrus (STG), anterior cingulate (ACC), inferior frontal gyrus (IFG), and temporo-parietal junction (TPJ). Until recently, AH were primarily controlled with antipsychotic medication which was often ineffective. In this application, we propose to use a cutting-edge biofeedback method of real-time functional imaging neuro-feedback (rt-fMRI) to reduce the frequency of AH and to better understand brain processes involved in AH. We adopt the Hugdahl 2009 model of AH according to which AH result from abnormalities in self-monitoring of speech, in selective attention and in auditory perceptual processes. We focus on the role of auditory cortex, specifically the STG, as a target area of neuro-feedback training for the treatment of AH in SZ. Based on existing literature, we posit that that improved function in the STG will normalize the entire network involved in the experience of AH. We predict that the activation in the STG (and regions forming AH network: IFG, ACC, and TPJ) will increase as a result of receiving feedback from that region which will lead to a better performance on the task of recognizing self/other voice as measured by fMRI activation levels pre-and post-rt-fMRI training and by reduction in positive symptoms and especially AH. The rt-fMRI neuro-feedback relies on recent advances in computer technology that allows subjects to see the level of activation in the selected brain region and to regulate ths activation following the training provided. Subjects are taught to up-regulate or down-regulate fMRI signal within a specific brain region selected based on the activation task. Importantly, reported activation changes are possible only if the subject receives a feedback from his/her target area and not when she/he receives it from a different subject or a different area than the target one (sham). It has been recently demonstrated that this approach may be helpful in many clinical conditions, among them schizophrenia (Haller 2010; Sitaran 2011;Linden 2012;Veit 2009; Hartwell 2012; Li 2012, Ruiz 2011). In this study we propose to study 30 chronic SZ patients and 30 normal control (NC) individuals (half of them will receive real and half will receive a sham fMRI feedback). We will use both fMRI (including two measures of connectivity) and clinical measures of the effectiveness of the rt-fMRI feedback. Based on the existing literature and our preliminary data, we predict that we will successfully improve auditory processing within the STG and within the targeted network and that it will lead to improvement in the clinical symptoms and especially in the frequency of AH.
描述(由申请人提供):听觉幻言(AH)长期以来一直是精神分裂症(SZ)症状学的标志,也是其主要诊断特征之一(Andreasen 和 Flaum,1991;DSM-IV)。已经证明,与 AH 相关的大脑区域涉及语言处理的不同方面。该大脑网络包括颞皮质,特别是颞上回(STG)、前扣带回(ACC)、额下回(IFG)和颞顶交界处(TPJ)。直到最近, AH 主要通过抗精神病药物进行控制,但通常无效。在此应用中,我们建议使用实时功能成像神经反馈(rt-fMRI)的尖端生物反馈方法来降低 AH 的频率并更好地了解 AH 涉及的大脑过程。我们采用 Hugdahl 2009 AH 模型,根据该模型,AH 是由言语自我监控、选择性注意和听觉感知过程异常引起的。我们重点关注听觉皮层(特别是 STG)的作用,作为治疗 SZ 中 AH 的神经反馈训练的目标区域。根据现有文献,我们认为 STG 中的改进功能将使参与 AH 体验的整个网络正常化。我们预测,STG(以及形成 AH 网络的区域:IFG、ACC 和 TPJ)的激活将由于收到来自该区域的反馈而增加,这将导致在识别自我/其他声音的任务中表现更好,这是通过 rt-fMRI 训练前后的 fMRI 激活水平以及阳性症状(尤其是 AH)的减少来衡量的。 rt-fMRI 神经反馈依赖于计算机技术的最新进展,该技术允许受试者查看所选大脑区域的激活水平,并在提供的训练后调节该激活。受试者被教导在根据激活任务选择的特定大脑区域内上调或下调功能磁共振成像信号。重要的是,只有当受试者从他/她的目标区域收到反馈时,报告的激活变化才有可能,而不是当她/他从与目标区域不同的受试者或不同区域收到反馈时(假)。最近已经证明,这种方法可能对许多临床病症有帮助,其中包括精神分裂症(Haller 2010;Sitaran 2011;Linden 2012;Veit 2009;Hartwell 2012;Li 2012;Ruiz 2011)。在这项研究中,我们计划研究 30 名慢性精神分裂症患者和 30 名正常对照 (NC) 个体(其中一半将收到真实的功能磁共振成像反馈,一半将收到假的功能磁共振成像反馈)。我们将使用 fMRI(包括两种连接性测量)和 rt-fMRI 反馈有效性的临床测量。根据现有文献和我们的初步数据,我们预测我们将成功改善 STG 内和目标网络内的听觉处理,并将改善临床症状,尤其是 AH 频率。

项目成果

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MARGARET A NIZNIKIEWICZ其他文献

MARGARET A NIZNIKIEWICZ的其他文献

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{{ truncateString('MARGARET A NIZNIKIEWICZ', 18)}}的其他基金

Real-time fMRI Neurofeedback as a Tool to Mitigate Auditory Hallucinations in Patients with Schizophrenia
实时功能磁共振成像神经反馈作为减轻精神分裂症患者幻听的工具
  • 批准号:
    10615478
  • 财政年份:
    2022
  • 资助金额:
    $ 18.21万
  • 项目类别:
Real-time fMRI Neurofeedback as a Tool to Mitigate Auditory Hallucinations in Patients with Schizophrenia
实时功能磁共振成像神经反馈作为减轻精神分裂症患者幻听的工具
  • 批准号:
    10019700
  • 财政年份:
    2018
  • 资助金额:
    $ 18.21万
  • 项目类别:
Real-time fMRI Neurofeedback as a Tool to Mitigate Auditory Hallucinations in Patients with Schizophrenia
实时功能磁共振成像神经反馈作为减轻精神分裂症患者幻听的工具
  • 批准号:
    10704690
  • 财政年份:
    2018
  • 资助金额:
    $ 18.21万
  • 项目类别:
Real time fMRI feedback and auditory processing in schizophrenia
精神分裂症的实时功能磁共振成像反馈和听觉处理
  • 批准号:
    8676940
  • 财政年份:
    2013
  • 资助金额:
    $ 18.21万
  • 项目类别:
Neurophysiological and MRI Studies of Schizophrenia
精神分裂症的神经生理学和 MRI 研究
  • 批准号:
    9337244
  • 财政年份:
    2009
  • 资助金额:
    $ 18.21万
  • 项目类别:
Semantic knowledge and its underlying structures in schizophrenia-an fMRI study
精神分裂症的语义知识及其底层结构——一项功能磁共振成像研究
  • 批准号:
    7251770
  • 财政年份:
    2007
  • 资助金额:
    $ 18.21万
  • 项目类别:
Language Systems in Schizophrenia: Behavioral & ERP Data
精神分裂症的语言系统:行为
  • 批准号:
    6891683
  • 财政年份:
    2002
  • 资助金额:
    $ 18.21万
  • 项目类别:
Language Systems in Schizophrenia: Behavioral & ERP Data
精神分裂症的语言系统:行为
  • 批准号:
    7075440
  • 财政年份:
    2002
  • 资助金额:
    $ 18.21万
  • 项目类别:
Language Systems in Schizophrenia: Behavioral & ERP Data
精神分裂症的语言系统:行为
  • 批准号:
    6742536
  • 财政年份:
    2002
  • 资助金额:
    $ 18.21万
  • 项目类别:
Language Systems in Schizophrenia: Behavioral & ERP Data
精神分裂症的语言系统:行为
  • 批准号:
    6471942
  • 财政年份:
    2002
  • 资助金额:
    $ 18.21万
  • 项目类别:

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