Localized fMRI of heterogeneous neural responses

描述（由申请人提供）：功能性磁共振成像（fMRI）无疑是神经成像方法，已成为神经科学和心理学研究人员的主力，这些研究人员希望获得与人类行为相关的大脑生理变化的局部测量。功能磁共振成像测量的高价值是基于这样一个事实，即它们已经被证明，一次又一次地表现出与局部神经群体反应的线性相关性。然而，最近在文献中有一些文章指出fMRI反应与测量或推测的神经活动之间不匹配。这些不匹配似乎仅限于只有一小部分神经群受到刺激的实验;当局部神经兴奋和抑制之间的平衡倾向于抑制时，它们似乎也最有可能发生。这些关于功能性磁共振成像反应与神经反应不相关的报告充其量是令人困惑的，对于那些希望从功能性磁共振成像数据中得出神经群体活动定量结论的科学家来说，这可能是一个麻烦。 我们的第一系列拟议的实验将表征采样分辨率的fMRI对小刺激的反应的可解释性的影响。不仅侧翼负反应混淆了对小块神经活动的fMRI反应的准确解释，因为与总神经反应相比，边界区域很大，而且大小依赖性内在抑制塑造了神经反应，但在血流动力学反应中具有未知的代表性。第一系列实验的结果将是一个计算模型，其特征在于（1）孤立的神经活动斑块边缘的神经-血液动力学耦合，以及（2）抑制性神经活动对fMRI反应的贡献。 我们的第二个系列的实验将表征功能磁共振成像反应诱发的神经网络之间的兴奋和抑制的不同平衡。所有局部神经代码都包含输入和输出之间的平衡;局部计算使用激励和抑制的平衡来塑造输入并定义输出尖峰速率。在这一系列的实验中，我们将探讨我们最近的研究表明，局部功能磁共振成像的个别图像补丁不能预测简单地从神经元的反应，最好的反应，这些刺激的影响。与一个计算模型，演示了如何整个本地神经群体的反应，可以用来预测功能磁共振成像反应，这第二系列的实验将寻求识别签名时，异质性神经反应掩盖关键信息编码的神经元亚群的血液动力学反应的特点。 总之，这些实验将提高我们使用高分辨率功能磁共振成像来表征模式化神经活动的能力，提高功能磁共振成像在临床应用中的实用性，如神经外科规划和癫痫发作部位检测。

DESCRIPTION (provided by applicant): Functional magnetic resonance imaging (fMRI) is undeniably the neuroimaging methodology that has become the workhorse for neuroscience and psychology researchers who want access to localized measurements of physiological changes in the brain that correlate with human behavior. The high value of fMRI measurements is based on the fact that they have been shown, time and again, to exhibit a linear correlation with the local neural population response. There are, however, a recent smattering of articles in the literature indicating a mismatch between the fMRI response and the measured or presumed neural activity. These mismatches appear limited to experiments in which only a small neural population is stimulated; they also seem most likely to occur when the balance between local neural excitation and inhibition is tipped in favor of inhibition. These reports of fMRI responses that fail to correlate with neural responses are puzzling at best, and potentially troublesome for scientists who want to draw quantitative conclusions about neural population activity from fMRI data. Our first series of proposed experiments will characterize the effects of sampling resolution on the interpretability of the fMRI response to small stimuli. Not only do flanking negative responses confound accurate interpretation of the fMRI response to small patches of neural activity, because the boundary regions are large compared to the total neural response, but size-dependent intrinsic inhibition shapes the neural response yet has an unknown representation in the hemodynamic response. The result of the first series of experiments will be a computational model characterizing (1) neuro-hemodynamic coupling at the edges of isolated patches of neural activity, and (2) the contribution of inhibitory neural activity to the fMRI response. Our second series of experiments will characterize fMRI response evoked by neural networks with different balances between excitation and inhibition. All local neural codes contain a balance between input and output; local computations use a balance of excitation and inhibition to shape the input and define output spiking rates. In this series of experiments, we will investigate the implications of our recent study showing that localized fMRI of individual image patches cannot be predicted simply from the responses of the neurons that respond best to those stimuli. Working with a computational model that demonstrates how the entire local neural population response can be used to predict fMRI responses, this second series of experiments will seek to identify signature hemodynamic response characteristics that are present when heterogeneous neural responses mask key information encoded in a sub-population of neurons. Together, these experiments will improve our ability to use high-resolution fMRI to characterize patterned neural activity, improving the utility of fMRI for clinicl applications such as neurosurgical planning and seizure locus detection.