CRCNS: Multifocal causal mapping of brain networks supporting human cognition

CRCNS：支持人类认知的大脑网络的多焦点因果图谱

基本信息

批准号：
10654871
负责人：
Aapo Nummenmaa
金额：
$ 24.94万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-07-01 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10654871
关键词：
Address Algorithms Anterior Area Behavior Behavioral Bilateral Brain Brain Mapping Brain region Cognition Cognitive Complement Complex Computer Models Computing Methodologies Consumption Custom Data Devices Diagnostic Dorsal Electroencephalography Experimental Designs FDA approved Freedom Functional Magnetic Resonance Imaging Generations Goals Head Hearing Human Inferior frontal gyrus Judgment Language Left Lesion Location Magnetic Resonance Imaging Maps Methods Modeling Motor Motor Cortex Neuronavigation Neurosciences Participant Patients Pattern Population Procedures Protocols documentation Research Response Latencies Role Semantics Societies Standardization Statistical Models Synaptic Transmission Synaptic plasticity System Techniques Technology Testing Therapeutic Time Transcranial magnetic stimulation Work clinical application cognitive function cognitive neuroscience computerized data processing computerized tools cortex mapping electric field experimental study in vivo insight instrument language comprehension language processing millisecond network models neural neural network neuroimaging neuronal circuitry novel novel strategies operation phonology response semantic processing sound speech processing success support network tool treatment optimization virtual

项目摘要

PROJECT SUMMARY: Neuroimaging methods such as functional MRI and magneto- / electroencephalography (MEG/EEG) cannot directly reveal causal relationships between regional brain activity and behavior. To allow causal inference, transcranial magnetic stimulation (TMS) has been used to perturb local cortical activity to create temporary "virtual lesions”. However, even simple behavioral tasks employ widely distributed brain networks with multiple nodes activated at different millisecond-level latencies, whereas today’s TMS technology is mainly limited to single-channel devices that target only one brain area at a time. The mismatch between the large number of network nodes and the small number of cortical areas we can target with present TMS devices forms a critical barrier in exploring network-level causal inferences in the human brain. To remove this barrier, we need TMS technology that can perturb multiple cortical locations at specific processing stages. Removing this barrier would open entirely new avenues for gaining insight into how complex cognitive functions emerge from cortical networks. For the identification of neural networks underlying cognitive operations, two steps are necessary. First, network nodes are identified as locations where the strength of the TMS-induced electric field and relevant behavioral or neuroimaging-based variables maximally correlate. This can be achieved efficiently using the unprecedented ability of the multichannel TMS array to generate different customized electric field patterns in rapid succession. Next, information flow between the network nodes is explored by stimulating the nodes in rapid temporal succession. For this, the ability of the multichannel array to switch between electric field patterns in milliseconds is crucial. The network-level mapping capabilities of the instrument will be first verified in a testbench experiment in a known network (motor system). We then proceed to studies that identify network nodes underlying language comprehension. Finally, we will use the multifocal stimulation approach to investigate information flow in the language comprehension network and develop a neural mass model of the underlying neuronal circuits for a theoretical basis. In the long term, the wider society may benefit from all applications of the proposed research through network-level TMS therapies that are optimized for modulating functional connectivity between brain regions involved in critical functions such as hearing, speech, and language processing.

项目摘要：神经影像学方法，例如功能性MRI和磁性脑电图（MEG / EEG），无法直接揭示区域行为之间的因果关系，以允许因果推理，跨性别磁刺激（TMS）已被使用以创建临时的“临时”皮质活性。病变。在探索网络级别的因果关系中，我们需要驱动多块的位置阶段的TMS技术节点被识别为TMS诱导的电场的位置以及相关的行为或基于神经成像的变量LLY相关性。快速的临时阵列。研究了ge classensenson。我们将多灶性刺激进行研究，在语言理解网络中流动D.基础神经回路的神经质量模型，以通过网络级别的方式进行了托管研究。在听力，语音和语言处理之类的CR ITICAL功能中进行了脑部。