NCS-FO: SOUND: Understanding the Functional Neural Dynamics Underpinning Auditory Processing Dysfunctions through a Multiscale Recording-Stimulation Framework

NCS-FO：声音：通过多尺度记录刺激框架了解支撑听觉处理功能障碍的功能神经动力学

基本信息

批准号：
2024418
负责人：
Yalda Shahriari
金额：
$ 49.99万
依托单位：
University of Rhode Island
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-10-01 至 2025-03-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2024418&HistoricalAwards=false
关键词：
NCS FO SOUND Understanding Functional

项目摘要

Auditory processing dysfunction (APD) is a common feature of many types of psychosis, including schizophrenia, and is associated with multiple core symptoms, including auditory verbal hallucinations (i.e. hearing voices). Despite APD’s high prevalence, affecting up to 80% of the psychotic population, pharmaceutical therapy is ineffective: 70% of patients either have undesirable side effects or experience persistent symptoms despite treatment. A non-pharmacological treatment strategy, such as neuromodulation (targeted stimulation of nerves), would meet an important medical need. Although neuromodulation has recently emerged as a plausible therapeutic tool for a range of neuropsychological conditions, little is understood of the abnormal neural patterns underlying APD. This project will utilize an innovative framework, integrating multiscale recording and stimulation, to explore APD and to elucidate its underlying mechanisms. The project unites a multidisciplinary team of researchers, including experts in neural signal processing, neuroscience, psychiatry, and deep learning. The proposed work will develop computational, data-driven approaches in real-world settings. These will investigate multimodal signals with distinct spatiotemporal properties, integrated with a neuroimaging study of psychosis with APD. In addition to the scientific impacts of this proposal, the proposed work will advance national health by addressing multiple existing gaps in neuroscience and psychiatry. The educational and outreach plans will provide training opportunities for women and under-represented minoroties, promoting STEM diversity in the Northeastern United States.This project has three main thrusts. All of the proposed frameworks are data-driven and will be tested on healthy controls and patients with schizophrenia, in whom APD is a core feature. The first thrust will develop a computational statistical approach to quantify hierarchical couplings between hemodynamic infra-slow oscillations (using fNIRS), and electrical high-frequency oscillations (using EEG), through a nested multimodal approach in auditory task-related settings. The second thrust introduces an innovative multimodal data fusion approach to exploit complementary strengths from electrical and vascular dynamics, toward an integrative understanding of APD. This will enable identification of across-subject and within-subject signals underlying APD. The third thrust will extent beyond functional investigations and into causal dynamics across large-scale networks. The research will develop fused causal models, to identify subject-specific causal patterns of APD, and to create individualized spatial target mapping for optimal site stimulation. The precise locations of aberrant causal patterns will be targets for transcranial direct-current stimulation (tDCS). Project outcomes include the introduction of an innovative computational data fusion approach to bridge distinct spatiotemporal scales; discovery of latent signatures and causal patterns of APD through novel neural information processing; insight into APD hierarchical mechanisms, and understanding of the cortical modulatory properties of APD.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

听觉加工功能障碍（APD）是许多类型的精神病（包括精神分裂症）的常见特征，并且与多种核心症状有关，包括听觉言语幻觉（即听到声音）。尽管APD的患病率很高，但多达80％的精神病患者，药物治疗却无效：70％的患者具有不良的副作用，或者经历了持续的症状目的地治疗。一种非药物治疗策略，例如神经调节（靶向刺激神经），将满足重要的医疗需求。尽管神经调节最近已成为针对一系列神经心理条件的合理治疗工具，但几乎几乎没有理解APD的绝对神经元模式。该项目将利用创新的框架，整合多尺度记录和刺激，探索APD并阐明其基本机制。该项目将一个多学科的研究人员组成，包括神经信号处理，神经科学，精神病学和深度学习的专家。拟议的工作将在现实世界中开发计算，数据驱动的方法。这些将研究具有不同时空特性的多模式信号，并与APD进行了精神病的神经影像学研究。除了该提议的科学影响外，拟议的工作还将通过解决神经科学和精神病学的多个现有差距来提高国家健康。教育和宣传计划将为妇女和代表性不足的少数民族提供培训机会，促进美国东北部的STEM多样性。该项目有三个主要推力。所有提出的框架都是数据驱动的，并将对健康对照和精神分裂症患者进行测试，而精神分裂症患者APD是核心特征。第一个推力将开发一种计算统计方法，以通过听觉与任务相关的设置中的嵌套多模式方法来量化血液动力学基础设施（使用FNIRS）和电高频振荡（使用EEG）之间的层次结合。第二个推力引入了一种创新的多模式数据融合方法，以利用从电气和血管动力学的完整优势到对APD的综合理解。这将使APD基础的跨受试者和受试者内部信号识别。第三个推力将超越功能投资，并进入大规模网络的因果动态。该研究将开发融合的因果模型，以识别APD的特定主体因果模式，并创建个性化的空间目标映射以实现最佳位点刺激。异常因果模式的确切位置将是经颅直流刺激（TDC）的目标。项目结果包括引入创新的计算数据融合方法来桥接不同的空间时间尺度；通过新颖的神经元信息处理发现APD的潜在特征和因果模式；对APD的APD层次结构机制以及对APD的皮质调节特性的理解的洞察力。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响评估标准，被认为值得通过评估来提供支持。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Phase-Amplitude Coupling Between EEG Cortical Oscillations and Respiration: An Exploratory Study

DOI：
10.1109/ner52421.2023.10123888
发表时间：
2023-04
期刊：
2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)
影响因子：
0
作者：
J. McLinden;S. B. Borgheai;C. Kumar;N. Rahimi;M. Shao;K. Spencer;Y. Shahriari
通讯作者：
J. McLinden;S. B. Borgheai;C. Kumar;N. Rahimi;M. Shao;K. Spencer;Y. Shahriari

Adversary on Multimodal BCI-based Classification

基于多模式 BCI 分类的对手

DOI：
发表时间：
2023
期刊：
11th International IEEE EMBS Conference on Neural Engineering
影响因子：
0
作者：
Kumar, Chetan;Donohue, James P.;Gonjari, Rohan;Rahimi, Neela;McLinden, John;Shahriari, Yalda;Shao, Ming
通讯作者：
Shao, Ming

Electrovascular Phase-Amplitude Coupling During an Auditory Task

听觉任务期间的电血管相位幅度耦合