Dynamic Brain Imaging of Speech in Primary Progressive Aphasia

项目总结 原发性进行性失语(PPA)是一种以孤立性进行性言语丧失为特征的临床综合征 以及由于额颞叶变性(FTLD)或阿尔茨海默病(AD)而导致的语言能力。三 已经确定了PPA的临床变种：i)与语音丢失相关的对数变种(LvPPA) 能力、左侧颞顶萎缩和不典型的AD病理；ii)伴有运动的不流畅变异(NfvPPA) 语音/语法缺陷、左额下部损伤和FTLD病理；以及iii)语义变异(SvPPA)， 概念性知识丧失，前颞叶损伤，大多为FTLD型病理。在第一笔资金中 期间，我们展示了不同的PPA变种(&gt；40家酒吧)的不同功能神经病理生理学。建房 在这些发现的基础上，在这次更新中，我们重点揭示了重要的机械神经回路 PPA变种的异常。这种机械性的理解是发展的基础 对PPA进行更好的神经调节或行为干预。我们利用无与伦比的时间 结构和弥散磁共振成像的脑磁图成像(MEGI)的分辨率(解释 灰质和白质神经退行性变)、频谱图建模、语音运动控制建模、机器 学习，以及详细的认知和语言表型。具体目标是：1)确定不同的 PPA神经振荡的静息状态结构-功能成像；2)检查控制和 在PPA的语音产生中的学习；3)检查语音产生和神经之间的相互作用 PPA中的语义表示。这种独特的多模式脑成像(MEGI、结构磁共振和 扩散磁共振)、建模(频谱图、语音运动控制)、机器学习和语音神经科学 将：a)描述PPA变体中脑网络功能障碍的功能表现，以及b)确定 PPA的行为或神经调节疗法的假定的脑网络靶点和策略。

PROJECT SUMMARY Primary progressive aphasia (PPA) is a clinical syndrome characterized by isolated, progressive loss of speech and language abilities due to frontotemporal lobar degeneration (FTLD) or Alzheimer’s disease (AD). Three clinical variants of PPA have been identified: i) logopenic variant (lvPPA) associated with loss of phonological abilities, left temporal-parietal atrophy and atypical AD pathology; ii) nonfluent variant (nfvPPA) with motor speech/grammar deficits, left inferior frontal damage and FTLD pathology; and iii) semantic variant (svPPA), with conceptual knowledge loss, anterior temporal damage and mostly FTLD-type pathology. In the first funding period, we demonstrated distinct functional neuropathophysiology across PPA variants (>40 pubs). Building upon these findings, in this renewal, we focus on revealing important mechanistic neural circuit abnormalities in PPA variants. Such mechanistic understanding is the foundation for development of better neuromodulatory or behavioral interventions for PPA. We leverage the unmatched temporal resolution of magnetoencephalography imaging (MEGI) with structural and diffusion MRI (to account for neurodegeneration of grey and white matter), spectral graph modeling, speech motor control modeling, machine learning, as well as detailed cognitive and language phenotyping. The specific aims are: 1) To determine distinct resting-state structure-function imaging of neural oscillations in PPA; 2) To examine mechanisms of control and learning in the speech production in PPA; 3) To examine neural interactions between speech production and semantic representations in PPA. This unique combination of multimodal brain imaging (MEGI, structural MRI & diffusion MRI), modeling (spectral graph, speech motor control), machine learning, and speech neuroscience will: a) delineate the functional manifestations of brain network dysfunction in PPA variants, and b) identify putative brain network targets and strategies for behavioral, or neuromodulation therapies for PPA.