Functional MRI is aimed at localizing cortical activity to understand the role of specific cortical regions, providing insight into the neurophysiological underpinnings of brain function. Scientists developing fMRI methodology seek to improve detection of subtle activations and to spatially localize these activations more precisely. Except for applications in the clinical environment, such as functional mapping in patients prior to neurosurgical intervention, most basic neuroscience studies involve group level random-effects analyses. Prior to grouping data, the data from each individual are typically smoothed. A wide range of motivations for smoothing have been given including to match the spatial scale of hemodynamic responses, to normalize the error distribution (by the Central Limit Theorem) to improve the validity of inferences based on parametric tests, and, in the context of inter-subject averaging smoothing has been shown necessary to project the data down to a scale where homologies in functional anatomy are expressed across subjects. This work demonstrates that, for single-subject studies, if smoothing is to be employed, the data should be acquired at lower resolutions to maximize SNR. The benefits of a low-resolution acquisition are limited by partial volume effects and by the weak impact of resolution-dependent noise on the overall group level statistics. Given that inter-subject noise dominates across a range of tasks, improvements in within-subject noise, through changes in acquisition strategy or even moving to higher field strength, may do little to improve group statistics. Such improvements however may greatly impact single-subject studies such as those used in neurosurgical planning.

译文

:功能性MRI旨在定位皮质活动,以了解特定皮质区域的作用,从而洞悉脑功能的神经生理学基础。开发功能磁共振成像方法的科学家寻求改进对微妙激活的检测,并更精确地在空间上定位这些激活。除了在临床环境中的应用(例如在神经外科手术之前对患者进行功能映射)以外,大多数基础神经科学研究都涉及组水平的随机效应分析。在对数据进行分组之前,通常会对来自每个人的数据进行平滑处理。给出了许多平滑的动机,包括匹配血液动力学响应的空间尺度,归一化误差分布(通过中央极限定理)以提高基于参数检验的推论的有效性,以及已经证明,将对象平均平滑化对于将数据投影到一定规模是必要的,在该规模上跨对象表达了功能解剖学上的同源性。这项工作表明,对于单对象研究,如果要进行平滑处理,则应以较低的分辨率获取数据以最大程度地提高SNR。低分辨率采集的好处受到部分音量影响和与分辨率有关的噪声对整个组级别统计数据的影响的限制。考虑到受试者间的噪声在所有任务中均占主导地位,通过改变采集策略甚至转向更高的场强来改善受试者内的噪声可能对改善组统计没有多大作用。但是,此类改进可能会极大地影响单项研究,例如用于神经外科计划的研究。

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