Understanding the neurocognitive mechanisms of alpha-band brain oscillations using concurrent EEG-fMRI recordings

项目总结 阿尔法振荡，神经信号中8-12赫兹的波动，在不同物种之间是健壮的，随着 注意力，并在多种无序状态下受到影响，近年来已成为候选的生物标志物 注意力系统的功效，特别是在注意力障碍方面，如注意缺陷多动障碍 (ADHD)。然而，尽管阿尔法振荡被广泛接受为注意力读出信号，但重要的是 关于阿尔法振荡的机制和解释仍然存在问题。我们的目标是 研究的核心问题是，阿尔法振荡的神经认知机制是否 或者它们是否更密切地反映了其他机制，如局部处理动态或 系统范围的补药警觉性。 为了解决这个问题，我们将同时记录人类参与者的脑电和功能磁共振，并采用因果关系 模型，以识别视觉皮质的功能连接(3T扫描)和板层激活(7T扫描) 在跨越不同任务上下文的阿尔法调制期间。我们的目标是测试(1)阿尔法升高是否反映大脑皮层 抑制或紧张性警觉，(2)如果阿尔法降低反映皮质增强或局部信息 流，以及，(3)如果阿尔法调制反映自上而下的信号，或者如果它们是以下任一项的被动副产品 皮质-皮质或丘脑-皮质驱动因素。这些结果将直接影响对阿尔法振荡的解释。 注意系统效能的生物标记物在ADHD和相关条件下，概述了一个可以在 注意缺陷多动症的治疗或监测。通过考虑现有发现的可变性，这项工作 我还将区分阿尔法振荡的两个理论框架，并就最近关于 阿尔法振荡是自上而下信号的关联还是产物。

PROJECT SUMMARY Alpha oscillations, 8-12Hz fluctuations in neural signals, are robust across species, covary with states of attention, and are impacted in multiple disorder states, and in recent years have become a candidate biomarker of attention system efficacy, particularly in disorders of attention such as attention deficit hyperactivity disorder (ADHD). Yet, despite this broad acceptance of alpha oscillations as an attention read-out signal, significant questions remain regarding the mechanisms and thus interpretation of alpha oscillations. The goal of our research is to answer the central question of whether the neurocognitive mechanisms of alpha oscillations are strictly attentional or whether they more closely reflect other mechanisms such as local processing dynamics or system-wide tonic alertness. To address this question, we will record EEG and fMRI concurrently in human participants, and employ causal models, to identify functional connectivity (3T scanning) and laminar activation (7T scanning) of visual cortex during alpha modulations across different task contexts. We aim to test (1) if alpha increases reflect cortical suppression or tonic alertness, (2) if alpha decreases reflect cortical enhancement or local information flow, and, (3) if alpha modulations reflect top-down signals or if they are a passive by-product of either cortico-cortical or thalamo-cortical drivers. The results will directly impact interpretation of alpha oscillations as a biomarker of attention-system efficacy in ADHD and related conditions, outlining a model that can be targeted in treatment or monitoring of attention deficits in ADHD. By accounting for variability in existing findings, this work will also differentiate between two theoretical frameworks of alpha oscillations and speak to recent debates on whether alpha oscillations are a correlate or a product of top-down signals.