Dynamic Brain Imaging of Speech in Primary Progressive Aphasia

原发性进行性失语症言语的动态脑成像

基本信息

批准号：
10740640
负责人：
MARIA LUISA GORNO TEMPINI
金额：
$ 237.31万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-15 至 2026-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10740640
关键词：
Acoustics Address Affect Alzheimer&apos s Disease Alzheimer&apos s disease pathology Anterior Atrophic Bayesian Analysis Behavior Therapy Behavioral Biophysics Brain Brain imaging Categories Clinical Cognitive Data Development Diffusion Diffusion Magnetic Resonance Imaging Dorsal Feedback Foundations Frequencies Frontotemporal Lobar Degenerations Funding Generations Goals Graph Image Impaired cognition Inferior Investigation Knowledge Language Learning Left Machine Learning Magnetic Resonance Imaging Magnetoencephalography Measures Memory Methods Modeling Motor Names Nerve Degeneration Neurologic Symptoms Neurosciences Parietal Pathology Pattern Phenotype Primary Progressive Aphasia Process Production Rest Semantics Sensory Speech Structure Syndrome Testing Variant Work auditory feedback cerebral atrophy connectome functional disability gray matter machine learning method morphometry motor control multimodality nervous system disorder network dysfunction neural neural circuit neural correlate neuroimaging neuroregulation novel phonology recruit sequence learning temporal measurement theories white matter

项目摘要

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.

项目摘要主要进行性失语症（PPA）是一种临床综合征以及由于额颞叶变性（FTLD）或阿尔茨海默氏病（AD）而引起的语言能力。三已经确定了PPA的临床变体：i）与语音丧失相关的徽标变体（LVPPA）能力，剩下的临时肾上腺萎缩和非典型AD病理学； ii）带电机的非流量变体（NFVPPA）语音/语法定义，左侧额叶损伤和FTLD病理学；和iii）语义变体（SVPPA），带有概念知识丧失，前临时损害和主要是FTLD型病理学。在第一个资金中时期，我们在PPA变体中展示了独特的功能性神经病理生理学（> 40个酒吧）。建筑根据这些发现，在此续约中，我们专注于揭示重要的机械神经回路 PPA变体异常。这种机械理解是发展的基础 PPA的更好的神经调节或行为干预措施。我们利用无与伦比的临时性具有结构和扩散MRI的磁脑化成像（MEGI）的分辨率（考虑到灰色和白质的神经变性），光谱图建模，语音运动控制建模，机器学习，以及详细的认知和语言表型。具体目的是：1）确定不同的 PPA中神经振荡的静止状态结构功能成像； 2）检查控制机制和在PPA的语音制作中学习； 3）检查语音产生与 PPA中的语义表示。多模式脑成像的独特组合（MEGI，结构MRI＆扩散MRI），建模（光谱图，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，b）识别 PPA的行为或神经调节疗法的假定大脑网络目标和策略。

项目成果

期刊论文数量（18）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Functional neuronal circuitry and oscillatory dynamics in human brain organoids.

DOI：
10.1038/s41467-022-32115-4
发表时间：
2022-07-29
期刊：
Nature communications
影响因子：
16.6
作者：
通讯作者：

Subspace-based interference removal methods for a multichannel biomagnetic sensor array.

多通道生物磁传感器阵列的基于子空间的干扰消除方法。

DOI：
10.1088/1741-2552/aa7693
发表时间：
2017
期刊：
Journal of neural engineering
影响因子：
4
作者：
Sekihara,Kensuke;Nagarajan,SrikantanS
通讯作者：
Nagarajan,SrikantanS

A Novel Scanning Algorithm for MEG/EEG imaging using Covariance Partitioning and Noise Learning.

使用协方差分区和噪声学习的 MEG/EEG 成像的新型扫描算法。

DOI：
10.1109/embc.2019.8856953
发表时间：
2019
期刊：
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
影响因子：
0
作者：
Cai,Chang;Sekihara,Kensuke;Nagarajan,SrikantanS
通讯作者：
Nagarajan,SrikantanS

Beta-band activity in medial prefrontal cortex predicts source memory encoding and retrieval accuracy.

内侧前额叶皮层的β带活动可预测源记忆编码和检索的准确性。

DOI：
10.1038/s41598-019-43291-7
发表时间：
2019
期刊：
Scientific reports
影响因子：
4.6
作者：
Subramaniam,Karuna;Hinkley,LeightonBN;Mizuiri,Danielle;Kothare,Hardik;Cai,Chang;Garrett,Coleman;Findlay,Anne;Houde,JohnF;Nagarajan,SrikantanS
通讯作者：
Nagarajan,SrikantanS

Magnetoencephalography Imaging Reveals Abnormal Information Flow in Temporal Lobe Epilepsy.