The impact of ultra-high field MRI on cognitive and computational neuroimaging
The impact of ultra-high field MRI on cognitive and computational neuroimaging
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DOI：
10.1016/j.neuroimage.2017.03.060
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发表时间：
2018-03-01
期刊：
影响因子：
5.7
通讯作者：
Formisano, Elia
中科院分区：
文献类型：
--
作者：
De Martino, Federico;Yacoub, Essa;Formisano, Elia
利用超高场MRI（7 T及以上）非侵入性测量脑功能反应的能力代表了推进我们对人类大脑理解的独特机会。与较低的领域相比（3T及以下），超高场MRI具有更高的灵敏度，可用于获取具有更高空间分辨率的功能图像，以及血氧水平依赖（BOLD）信号对潜在神经元反应的更高特异性。同时，提高的分辨率和特异性能够在亚毫米尺度上研究大脑功能，到目前为止只能通过侵入性技术来完成。在这种中观空间尺度上，感知、认知和行为可以在神经计算的基本单元水平上进行探索，如皮质柱、皮质层和皮质下核。这代表了一个独特的和独特的优势，区分超高场成像和低场成像，并可以促进功能磁共振成像和神经网络的计算建模之间的更紧密的联系。到目前为止，亚毫米尺度的功能脑映射集中在感觉信息的处理和众所周知的系统上，这些系统的广泛信息可以从动物的侵入性记录中获得。它仍然是一个开放的挑战，将这种方法扩展到独特的人类功能，更普遍的是，动物模型可能是有问题的系统。为了取得成功，获得高分辨率的功能数据与大空间覆盖的可能性，神经处理的计算模型的可用性，以及准确的生物物理模型的神经血管耦合在介观尺度上都出现必要的。
The ability to measure functional brain responses non-invasively with ultra high field MRI (7 T and above) represents a unique opportunity in advancing our understanding of the human brain. Compared to lower fields (3 T and below), ultra high field MRI has an increased sensitivity, which can be used to acquire functional images with greater spatial resolution, and greater specificity of the blood oxygen level dependent (BOLD) signal to the underlying neuronal responses.Together, increased resolution and specificity enable investigating brain functions at a submillimeter scale, which so far could only be done with invasive techniques. At this mesoscopic spatial scale, perception, cognition and behavior can be probed at the level of fundamental units of neural computations, such as cortical columns, cortical layers, and subcortical nuclei. This represents a unique and distinctive advantage that differentiates ultra high from lower field imaging and that can foster a tighter link between fMRI and computational modeling of neural networks.So far, functional brain mapping at submillimeter scale has focused on the processing of sensory information and on well-known systems for which extensive information is available from invasive recordings in animals. It remains an open challenge to extend this methodology to uniquely human functions and, more generally, to systems for which animal models may be problematic. To succeed, the possibility to acquire high-resolution functional data with large spatial coverage, the availability of computational models of neural processing as well as accurate biophysical modeling of neurovascular coupling at mesoscopic scale all appear necessary.