Spinoza Centre for Neuroimaging, Amsterdam, Netherlands.
Department of Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, Netherlands.
Hum Brain Mapp. 2023 Nov;44(16):5471-5484. doi: 10.1002/hbm.26459. Epub 2023 Aug 22.
Depth-resolved functional magnetic resonance imaging (fMRI) is an emerging field growing in popularity given the potential of separating signals from different computational processes in cerebral cortex. Conventional acquisition schemes suffer from low spatial and temporal resolutions. Line-scanning methods allow depth-resolved fMRI by sacrificing spatial coverage to sample blood oxygenated level-dependent (BOLD) responses at ultra-high temporal and spatial resolution. For neuroscience applications, it is critical to be able to place the line accurately to (1) sample the right neural population and (2) target that neural population with tailored stimuli or tasks. To this end, we devised a multi-session framework where a target cortical location is selected based on anatomical and functional properties. The line is then positioned according to this information in a separate second session, and we tailor the experiment to focus on the target location. Anatomically, the precision of the line placement was confirmed by projecting a nominal representation of the acquired line back onto the surface. Functional estimates of neural selectivities in the line, as quantified by a visual population-receptive field model, resembled the target selectivities well for most subjects. This functional precision was quantified in detail by estimating the distance between the visual field location of the targeted vertex and the location in visual cortex (V1) that most closely resembled the line-scanning estimates; this distance was on average ~5.5 mm. Given the dimensions of the line, differences in acquisition, session, and stimulus design, this validates that line-scanning can be used to probe local neural sensitivities across sessions. In summary, we present an accurate framework for line-scanning MRI; we believe such a framework is required to harness the full potential of line-scanning and maximize its utility. Furthermore, this approach bridges canonical fMRI experiments with electrophysiological experiments, which in turn allows novel avenues for studying human physiology non-invasively.
深度分辨功能磁共振成像(fMRI)是一个新兴的领域,由于其具有分离大脑皮层不同计算过程信号的潜力,因此越来越受欢迎。传统的采集方案存在空间和时间分辨率低的问题。线扫描方法通过牺牲空间覆盖范围来以超高速率和空间分辨率采样血氧水平依赖(BOLD)响应,从而实现深度分辨 fMRI。对于神经科学应用,能够准确地放置线(1)采样正确的神经群体,(2)用定制的刺激或任务靶向该神经群体至关重要。为此,我们设计了一个多会话框架,其中根据解剖学和功能特性选择目标皮质位置。然后,根据此信息在单独的第二次会话中定位线,并且我们针对目标位置定制实验。从解剖学上讲,通过将获取的线的名义表示投影回表面,可以确认线放置的精度。通过视觉群体感受野模型对在线的神经选择性进行功能估计,对于大多数受试者,其与目标选择性非常吻合。通过估计目标顶点的视场位置与最接近线扫描估计的视皮层(V1)位置之间的距离,可以详细量化这种功能精度;该距离的平均值约为 5.5mm。考虑到线的尺寸、采集、会话和刺激设计的差异,这验证了线扫描可以用于跨会话探测局部神经敏感性。总之,我们提出了一种用于线扫描 MRI 的精确框架;我们相信,需要这种框架来充分发挥线扫描的潜力并最大程度地提高其效用。此外,这种方法弥合了经典 fMRI 实验与电生理实验之间的鸿沟,从而为非侵入性地研究人类生理学开辟了新途径。