Neurodynamics of Attention: MEG, EEG, and Modeling

注意力的神经动力学：MEG、EEG 和建模

• 批准号: 7558525
• 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 2010-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7558525
• 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; Lead; Link; Magnetoencephalography; Mathematics; Measurement; Measures; Mediating; Mentors; Methods; Modeling; Neural Network Simulation; Neurologic; Neurons; Neurosciences; Perception; Phase; Research; Research Personnel; Sensory; Signal Transduction; Simulate; Somatosensory Cortex; Stimulus; System; Tactile; Techniques; Testing; 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类受试者的神经动力学与注意力之间的关系。我们的目标是将人类宏观实验测量和计算神经网络模型的见解结合起来，以检验选择性注意影响时域和频域中测量的皮层活动的假设，并且这种活动是由特定的细胞水平神经元事件介导的。这将通过两种方法来完成。首先，我们将通过感官任务实验探讨皮质节律注意力的影响。具体来说，我们将使用 Arthinoula A. Martinos 中心最近开发的技术，在正中神经 (MN) 刺激期间同时测量脑磁图 (MEG) 和脑电图 (EEG) 信号。我们将在时域和频域上分析初级（SI）和次级（SII）体感系统产生的信号。在时域中，我们将测量诱发反应的幅度和延迟，在频域中将测量频谱功率和锁相。当受试者参加或不参加 MN 刺激时，我们将比较 SI 和 SII 内以及之间的这些测量。其次，我们将使用神经网络模型来测试伴随注意力的乙酰胆碱水平的变化是否在时域和频域活动的变化之间建立生物物理联系。这种方法将需要开发一个层压皮质柱模型，该模型可以再现用 MEG/EEG 颅外测量的振荡电流偶极子。该模型的模拟还可以对注意力对皮层活动的影响进行新的可实验测试的预测。这种双重方法可能会导致人们更好地理解注意力的宏观和细胞机制。这项为期五年的培训计划将把候选人的数学和计算神经网络建模背景与导师在脑磁图/脑电图和神经科学方面的专业知识相结合，以研究注意力对大脑神经动力学的影响。广泛的长期目标是创建一个生物物理上真实的神经网络模型，该模型可以与非侵入性临床成像技术结合使用，作为能够诊断和治疗神经性注意力障碍的工具。