The role of prestimulus oscillatory brain dynamics in auditory memory

项目总结：Wisniewski项目 当事件发生时，正在进行的大脑动力学会影响对事件的记忆。这在非人类和人类身上都很明显。 刺激前振荡脑的神经电磁记录(例如，脑电-脑电) 已有研究表明，状态决定神经的可塑性，并预测以后的记忆恢复。然而，一种依赖 关于相关数据、限制性记忆范例、过时的分析技术以及偏向使用视觉 和/或语言刺激在知识状态下留下了悬而未决的问题。目前仍不清楚是否 刺激前大脑状态因果影响记忆，它们的影响是否与大脑皮质来源有关 振荡活动，以及影响是否仅适用于任务的子集。这使得开发变得困难。 使用具有健康相关目标(例如，诱导大脑的系统)的刺激前脑动力学的方法 可以促进记忆的动力学)。拟议的研究采用了创新的方法学方法。 为了检验振荡刺激前脑动力学影响声音记忆的中心假说。这个 产生的数据将填补知识状态中的空白，并确定可以利用的方向 刺激前的脑动力学，以产生积极的健康结果。目标1将决定前刺激如何 振荡脑电动力学与听觉记忆表现有关。高密度(104通道)脑电将 当受试者在评估记忆准确性的记忆任务中对声音进行编码时被记录下来 和精确度。分析将揭示可以预测这些的刺激前脑电振荡动力学。 内存性能指标。震源模拟将揭示负责这些效应的大脑皮层区域和 允许描述不同来源之间的相互作用如何影响记忆。AIM 2将会调制 刺激前的大脑动力学，并测量由此对记忆的影响。既是一种感觉纠缠，也是一种 重复经颅磁刺激(RTMS)方案将被用来诱导脑振荡状态 研究对象。因为大脑状态将被有目的地操纵，这将提供一个关于 关于记忆表现的刺激前振荡活动。这个项目将产生理论上的 对大脑振荡活动在记忆过程中的功能作用的见解。例如，它直接 与关于阿尔法(~8-13赫兹)振荡的理论有关，该理论提出正在进行的阿尔法的相位和功率 应该控制传入事件的处理。允许因果推理的方法将通知正在进行的 神经科学中关于振荡是否在加工过程中起到功能作用或仅仅是 令人惊叹。通过使用多种方法(脑电、感觉夹带、rTMS)，该项目还 以确定在康复/辅助设备的开发中采取的最有用的方向。这个 该项目将与CNAP第二阶段的所有三个横向主题(学习的神经生物学和 记忆、神经调节和评估以及高级计算建模)，并将依赖于 神经信息学和认知神经科学核心。

PROJECT SUMMARY: WISNIEWSKI PROJECT Ongoing brain dynamics impact memory for events as they occur. This is evident in nonhuman and human neuroelectromagnetic recordings (e.g., electroencephalography - EEG) where prestimulus oscillatory brain states have been shown to determine neural plasticity and predict later memory retrieval. However, a reliance on correlational data, restrictive memory paradigms, outdated analysis techniques, and a bias to use visual and/or language stimuli has left open questions in the state of knowledge. It is still not clear whether prestimulus brain states causally impact memory, whether their impacts are related to the cortical source of oscillatory activity, and whether effects only apply to a subset of tasks. This makes it difficult to develop approaches that use prestimulus brain dynamics with health-relevant goals (e.g., systems that induce brain dynamics that can facilitate memory). The proposed research employs innovative methodological approaches to examine the central hypothesis that oscillatory prestimulus brain dynamics impact memory for sound. The data produced will fill gaps in the state of knowledge and identify directions that can be taken to exploit prestimulus brain dynamics to produce positive health outcomes. Aim 1 will determine how prestimulus oscillatory EEG dynamics relate to auditory memory performance. High-density (104 channel) EEG will be recorded while subjects encode sounds in memory tasks with the capability of assessing memory accuracy and precision. Analyses will reveal the prestimulus EEG oscillatory dynamics that are predictive of these memory performance metrics. Source modeling will reveal the cortical areas responsible for these effects and allow a characterization of how interactions among different sources influence memory. Aim 2 will modulate prestimulus brain dynamics and measure resulting impacts on memory. Both a sensory entrainment and repetitive transcranial magnetic stimulation (rTMS) protocol will be used to induce oscillatory brain states in subjects. Because brain states will be purposefully manipulated, this will provide a causal viewpoint on prestimulus oscillatory activity regarding memory performance. This project stands to produce theoretical insights on the functional roles of oscillatory brain activity in memory processes. For instance, it is directly relevant to theory on alpha (~8-13 Hz) oscillations which proposes that the phase and power of ongoing alpha should gate the processing of incoming events. Methods that allow causal inference will inform the ongoing debate in neuroscience as to whether oscillations play a functional role in processing or are merely epiphenomenal. Through its use of multiple methods (EEG, sensory entrainment, rTMS), the project also stands to identify the most useful directions to take in the development of rehabilitative/assistive devices. The project will link with all three of CNAP Phase 2 crosscutting themes (The Neurobiology of Learning and Memory, Neuromodulation and Assessment, and Advanced Computational Modeling) and will rely on the Neuroinformatics and Cognitive Neuroscience Cores.