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Detection of the arcuate fasciculus in congenital amusia depends on the tractography algorithm

机译:先天性失语的弧形束状部的检测取决于超声检查算法

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The advent of diffusion magnetic resonance imaging (MRI) allows researchers to virtually dissect white matter fiber pathways in the brain in vivo. This, for example, allows us to characterize and quantify how fiber tracts differ across populations in health and disease, and change as a function of training. Based on diffusion MRI, prior literature reports the absence of the arcuate fasciculus (AF) in some control individuals and as well in those with congenital amusia. The complete absence of such a major anatomical tract is surprising given the subtle impairments that characterize amusia. Thus, we hypothesize that failure to detect the AF in this population may relate to the tracking algorithm used, and is not necessarily reflective of their phenotype. Diffusion data in control and amusic individuals were analyzed using three different tracking algorithms: deterministic and probabilistic, the latter either modeling two or one fiber populations. Across the three algorithms, we replicate prior findings of a left greater than right AF volume, but do not find group differences or an interaction. We detect the AF in all individuals using the probabilistic 2-fiber model, however, tracking failed in some control and amusic individuals when deterministic tractography was applied. These findings show that the ability to detect the AF in our sample is dependent on the type of tractography algorithm. This raises the question of whether failure to detect the AF in prior studies may be unrelated to the underlying anatomy or phenotype.
机译:扩散磁共振成像(MRI)的出现使研究人员能够在体内虚拟解剖大脑中的白质纤维通路。例如,这使我们能够表征和量化健康和疾病人群之间纤维束的差异,并根据训练的变化而变化。基于扩散核磁共振成像,现有文献报道,在某些控制个体和先天性失语症患者中不存在弓形束(AF)。鉴于存在失语症的细微损害,完全没有这样的主要解剖结构是令人惊讶的。因此,我们假设未能在该人群中检测到房颤可能与所使用的跟踪算法有关,并不一定反映了它们的表型。使用三种不同的跟踪算法分析了对照组和娱乐性个体的扩散数据:确定性和概率性算法,后者对两个或一个纤维群进行建模。在这三种算法中,我们复制了左前大于右前AF量的先前发现,但未发现组差异或交互作用。我们使用概率2纤维模型在所有个体中检测到房颤,但是,当应用确定性束摄影术时,在某些控制和娱乐性个体中追踪失败。这些发现表明,在我们的样本中检测房颤的能力取决于超声成像算法的类型。这就提出了一个问题,即先前研究中未能检测到房颤是否可能与潜在的解剖结构或表型无关。

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