课题基金 / 基金详情

Linking brain dynamics and language processing in the severely injured brain

Linking brain dynamics and language processing in the severely injured brain
将严重受伤大脑的大脑动力学和语言处理联系起来
批准号:
8311462
负责人:
Jonathan Cheney Bardin
金额:
$3.53万
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-03-01 至 2012-12-31

项目摘要

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中文摘要
翻译
描述(申请人提供):许多严重脑损伤患者没有可靠的运动输出通道,使得准确评估认知能力非常困难或不可能。考虑到这种混乱,必须开发床边检查的替代方法,以便更准确地测量患者的认知状态。这一建议旨在利用脑电图测量听觉语言的神经反应。具体而言,将使用先进的频谱方法来表征严重脑损伤受试者和对照组对自然语言的脑电图反应的时间和空间方面。我们将对大脑对语言的反应进行嵌套和分层的研究。特别是,我们将解决三个问题:对向前和向后的口语是否有不同的反应,大脑对不同类别的单个单词是否有不同的反应,以及大脑对连续叙述中特定的语义内容标记是否有反应。对这三个层次的语言内容的分析将使我们能够建立个体受试者对语言的神经反应的分级表示。核心假设是,脑电图测量的语言反应标记物将阐明脑损伤后认知功能的神经基础。此外,对于那些确实表现出一致床边行为的患者,我假设这些措施将与昏迷恢复量表修订(CRS-R)定义的操作行为标准相关联。首先,为了识别与语言内容呈现同时发生的脑电图变化,受试者将听取与个人相关的故事以及同一故事的时间反转版本。对这些数据的分析将揭示是否有一种特定的大脑活动模式选择性地反映语言处理,以及这种标记是否与患者的外在行为有关。其次,为了确定受试者是否对不同类别的单词表现出不同的神经反应,正常受试者和患者将听10个名词的重复,这些名词来自两个类别:可以用手操纵的物体和可以提供住所的物体,这两个类别以前在正常人的大脑中很容易区分。然后,我将训练一个分类器来区分不同类别的单词。我将首先证明,正常受试者和至少一些脑损伤受试者的大脑活动表现出一种可以分类的不同反应。然后,我们将测试一个假设,即在患者数据上训练的分类器的成功将与患者的CRS-R评分评分。第三,在连续脑电图中,对正常受试者和重度脑损伤受试者播放自然主义叙事,以识别连续叙事中发生的叙事转变的神经活动。围绕叙事转变的数据将使用平均光谱和围绕感兴趣的事件的光谱图来分析,以确定是否有证据表明受试者能够积极地跟随故事。
英文摘要
DESCRIPTION (provided by applicant): Many severely brain-injured patients have no reliable motor output channel, making accurate assessments of cognitive ability very difficult or impossible. Given this confound, it is essential that alternative approaches to the bedside exam be developed to allow for more accurate measurements of a patient's cognitive state. This proposal aims to use EEG measures of the neural response to auditory language for this purpose. Specifically, advanced spectral methods will be used to characterize temporal and spatial aspects of EEG responses to natural language in severely brain-injured subjects and controls. We will conduct a nested and hierarchical study of the brain's response to language. In particular, we will address three questions: is there a differential response to forward versus backward spoken language, does the brain respond differently to different categories of individual words, and does the brain respond to particular markers of semantic content in continuous narration. Analysis of these three levels of language content will allow us to build a graded representation of an individual subject's neural response to language. The central hypothesis is that markers of the EEG-measured response to language will elucidate the neural underpinnings of cognitive function after brain injury. Further, for those patients who do demonstrate consistent bedside behavior, I hypothesize that these measures will be linked to behavioral criteria operationally defined by the Coma Recovery Scale-Revised (CRS-R). First, in order to identify changes in the EEG that co-occur with presentation of language content, subjects will listen to personally relevant stories as well as to time-reversed versions of the same. Analysis of this data will reveal whether there is a specific pattern of brain activity that selectively reflects language processing, and whether such markers relate to outward behavior of patients. Second, to determine if subjects demonstrate a differential neural response to words from different categories, normal subjects and patients will listen to repetitions of ten nouns from two categories previously shown to be easily discriminated in normal brains: objects than can be manipulated by hand and objects than can provide shelter. I will then train a classifier to distinguish between the different categories of words. I will first demonstrate that he brain activity of normal subjects and at least some brain-injured subjects shows a differential response that can be classified. We will then test the hypothesis that the success of a classifier trained on patient data will grade with the patient's CRS-R score. Third, to identify neural activity that occurs in response to narrative shifts in continuous narration, naturalistic narrativs will be played to normal subjects and severely brain-injured subjects during continuous EEG. The data around narrative shifts will be analyzed using average spectra and spectrograms around the events of interest to determine whether there is evidence that subjects are able to actively follow a story. PUBLIC HEALTH RELEVANCE: My central hypothesis is that markers of the EEG-measured response to language will elucidate the neural underpinnings of cognitive function after severe traumatic brain injury. Further, for patients who demonstrate consistent bedside behavior, I hypothesize that these measures will be linked to operationally defined behavioral criteria. As such, the proposed experiments could provide a new set of tools for assaying the cognitive function of a brain-injured subject whose diagnosis is otherwise uncertain.
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