Neurodynamics of Attention: MEG, EEG, and Modeling

注意力的神经动力学：MEG、EEG 和建模

• 批准号: 7338374
• 负责人: STEPHANIE Ruggiano JONES
• 金额: $ 16.75万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-02-01 至 2010-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7338374
• 关键词: Acetylcholine; Affect; Area; Attention; Biophysics; Brain; Characteristics; Clinical; Computer Simulation; Cortical Column; Data; Development; Diagnosis; Disease; Electroencephalography; Electrophysiology (science); Event; Frequencies; Goals; Human; Imaging Techniques; Invasive; Lead; Link; Magnetoencephalography; Mathematics; Measurement; Measures; Mediating; Mentors; Methods; Modeling; Neural Network Simulation; Neurologic; Neurons; Neurosciences; Perception; Phase; Purpose; Research; Research Personnel; Sensory; Signal Transduction; Simulate; Somatosensory Cortex; Stimulus; System; Tactile; Techniques; Testing; Thinking; Time; Training Programs; base; egg; human subject; insight; median nerve; network models; neurochemistry; programs; relating to nervous system; research study; response; selective attention; sensory stimulus; simulation; somatosensory; tool

DESCRIPTION (provided by applicant): The purpose of this proposal is to investigate the relationship between neural dynamics and attention in normal human subjects. We aim to combine insights from human macroscopic experimental measures and computational neural network modeling to test the hypothesis that selective attention affects cortical activity measured in both the time and frequency domain, and that this activity is mediated by specific cellular level neuronal events. This will be accomplished using a two-fold approach. First, we will experimentally probe the effects of attention of cortical rhythms using a sensory task. Specifically, we will use techniques recently developed at the Arthinoula A. Martinos center to simultaneously measure magnetoencephalography (MEG) and electroencephalography (EEG) signals during median nerve (MN) stimulation. We will analyze the signals generated in the primary (SI) and secondary (SII) somatosensory system in both the time and frequency domain. In the time domain, we will measure amplitudes and latencies of evoked responses, and in the frequency domain will measure spectral power and phase-locking. We will compare these measures within and between SI and SII when the subject is attending or not attending to the MN stimulation. Second, we will use neural network modeling to test if changes in the level of acetylcholine that accompany attention create a biophysical link between changes in time and frequency domain activity. This approach will entail the development of a model of a laminated cortical column(s) that reproduces the oscillatory current dipoles that are measured extracranially with MEG/EEG. Simulations with the model can also lead to new experimentally testable predictions of the effects of attention on cortical activity. This two-fold approach may lead to a better understanding of the macroscopic and cellular mechanisms of attention. This proposed five-year training program will combine the candidate's background in mathematics and computational neural network modeling with the mentor's expertise in MEG/EEG and neuroscience to investigate the influence of attention on brain neurodynamics. The broad long term objective is to create a biophysically realistic neural network model that can be used in conjunction with non-invasive clinical imaging techniques as a tool capable of diagnosing and treating neurological attention disorders.

描述（由申请人提供）：该提案的目的是研究正常人受试者中神经动力学与注意力之间的关系。我们旨在结合人类宏观实验测量和计算神经网络建模的见解，以检验以下假设：选择性注意会影响时间和频域中测量的皮质活性，并且该活性是由特定的细胞水平神经元事件介导的。这将使用两倍的方法来完成。首先，我们将使用感官任务在实验中探测皮质节奏的注意的影响。具体而言，我们将使用最近在Arthinoula A. Martinos中心开发的技术来同时测量中位神经（MN）刺激期间的磁脑摄影（MEG）和脑电图（EEG）信号。我们将分析在时间和频域中的主要（SI）和次级（SII）体感系统中产生的信号。在时间域中，我们将测量诱发响应的幅度和潜伏期，在频域中，将测量光谱功率和相锁定。当受试者参加或不参加MN刺激时，我们将比较SI和SII内部和SII之间的这些措施。其次，我们将使用神经网络建模来测试伴随注意的乙酰胆碱水平的变化是否在时间和频域活动变化之间产生生物物理联系。这种方法将需要开发一个层压皮质柱的模型，该模型再现了用MEG/EEG外颅外测量的振荡性电流偶极子。使用该模型的模拟还可以导致对注意力对皮质活性的影响的新实验测试预测。这种两倍的方法可能会使人们更好地理解注意力的宏观和细胞机制。该提出的五年培训计划将将候选人在数学和计算神经网络建模方面的背景与导师在MEG/EEG方面的专业知识和神经科学的专业知识相结合，以研究注意力对脑神经动力学的影响。广义的长期目标是创建一个具有生物物理现实的神经网络模型，该模型可以与非侵入性临床成像技术一起使用，作为能够诊断和治疗神经系统注意力障碍的工具。