Non-invasive measures of multisensory cortical feedforward and feedback influences

多感觉皮层前馈的非侵入性测量及其反馈影响 本研究的目标是开发和应用先进的多模式神经成像方法来 通过使用人类听觉的交叉模式调制，研究信息如何在大脑区域之间流动 作为测试用例进行处理。前馈(FF)和反馈(FB)连接的分层组织 灵长类感觉区域已经建立在解剖和功能连接模式的基础上 皮质层。例如，来自其他感觉系统的信息可以调节声音的处理。 听觉皮质(AC)通过直接的FF输入、来自其他感觉皮质的横向输入和/或来自的FB效应 较高水平的多模式区域(例如，上颞沟STS)。然而，这其中每一个的确切方式 知觉和认知的机制是一个重要的开放问题。解决问题的关键障碍 这个问题是缺乏非侵入性技术来对FF和FB的影响做出详细的推断 在大脑皮质信息处理中。还需要这种技术来实现更好的诊断工具和 对包括失语症、阅读障碍或自闭症在内的异常的前额叶和前额叶突起的障碍进行随访。近期 研究表明，功能性的Ff和Fb的影响可以从局部方向间接地推断出来 磁电和脑电(MEG、EEG)源电流估计，以及来自频段的 具体的定向功能连接措施。此外，超高场的最新发展 功能磁共振成像(FMRI)使在不同深度采样小体素(&lt；1mm3)成为可能 皮层，潜在地使推断FF型和FB型层流激活模式成为可能。这些方法可能 提供关于某一区域在其他皮质区域中的分层角色的关键信息， 这是传统的大脑皮层激活模式所不具备的。基于这些科学依据 前提下，我们的目标1是将源电流方向的测量与源自以下各项的有效连接相结合 脑磁图/脑电(Subaim 1a)皮层内深度(或“层流”)分析记录的7T fMRI信号 同时采集高密度脑电数据(Subaim 1b)。我们将把结果与基于以下因素的预测进行比较 非人灵长类动物模型的研究。我们的目标2是开发新的方法来检查神经元 人体AC激活的跨模式夹带机制，包括来源的扩展 对振荡活动的定向分析。为了实现这一点，我们将结合脑磁图/脑电源估计的分析 (Subaim 2a)和同时采集的层流分辨率7T fMRI和高密度脑电数据的分析 (苏巴伊姆2b)。对于这两个目标，我们将使用来自以下方面的直接脑记录来验证我们的非侵入性结果 因医学原因植入颅内电极的癫痫患者。这些技术 这一项目的结果将显著增强我们使用 非侵入性神经成像。

Non-invasive measures of multisensory cortical feedforward and feedback influences The objective of this research is to develop and apply advanced multimodal neuroimaging methods to examine how information flows between brain areas, by using crossmodal modulation of human auditory processing as a test case. A hierarchical organization of feedforward (FF) and feedback (FB) connections among primate sensory areas has been established based on anatomical and functional connectivity patterns across cortical layers. For example, information from other sensory systems could modulate sound processing in auditory cortices (AC) through direct FF inputs, lateral inputs from other sensory cortices, and/or FB effects from higher-level polymodal areas (e.g., superior temporal sulcus STS). However, the exact way each of these mechanisms contributes to perception and cognition is an important open question. A critical barrier for resolving this question has been the lack of non-invasive techniques to make detailed inferences on FF and FB influences in cortical information processing. Such techniques are also needed to achieve better tools for the diagnosis and follow-up of disorders involving abnormal FF and FB processes, including aphasia, dyslexia, or autism. Recent studies suggest that functional FF and FB influences could be indirectly inferred from the local direction of magneto- and electroencephalography (MEG, EEG) source current estimates, as well as from frequency-band specific directed functional connectivity measures. Furthermore, recent developments in ultra-high field functional magnetic resonance imaging (fMRI) make it possible sample small voxels (< 1 mm3) at different depths of cortex, potentially enabling inferences of FF and FB type laminar activation patterns. These approaches could provide critical pieces of information regarding the hierarchical role of an area among other cortical areas, something that is not available in conventional measures of cortical activation patterns. Based on these scientific premises, our Aim 1 is to combine measures of source current direction and effective connectivity derived from MEG/EEG (Subaim 1a) with intracortical depth (or “laminar”) analyses of 7T fMRI signals recorded simultaneously with high-density EEG data (Subaim 1b). We will compare the results with predictions based on studies of non-human primate models. Our Aim 2 is to develop novel methods for examining the neuronal mechanisms of crossmodal entrainment of AC activations in humans, including an extension of the source direction analysis to oscillatory activity. To achieve this, we will combine analyses of MEG/EEG source estimates (Subaim 2a) and analyses of simultaneously acquired laminar-resolution 7T fMRI and high-density EEG data (Subaim 2b). For both Aims, we will validate our non-invasive results by using direct brain recordings from patients with epilepsy who have intracranial electrodes implanted for medical reasons. These techniques resulting from this project will significantly augment our ability to characterize cortical processes using noninvasive neuroimaging.