Evaluating Models of the Ageing BOLD Response

IF 3.5 2区 医学 Q1 NEUROIMAGING
R. N. Henson, W. Olszowy, K. A. Tsvetanov, P. S. Yadav, Cam-CAN, P. Zeidman
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引用次数: 0

Abstract

Neural activity cannot be directly observed using fMRI; rather it must be inferred from the hemodynamic responses that neural activity causes. Solving this inverse problem is made possible through the use of forward models, which generate predicted hemodynamic responses given hypothesised underlying neural activity. Commonly-used hemodynamic models were developed to explain data from healthy young participants; however, studies of ageing and dementia are increasingly shifting the focus toward elderly populations. We evaluated the validity of a range of hemodynamic models across the healthy adult lifespan: from basis sets for the linear convolution models commonly used to analyse fMRI studies, to more advanced models including nonlinear fitting of a parameterised hemodynamic response function (HRF) and nonlinear fitting of a biophysical generative model (hemodynamic modelling, HDM). Using an exceptionally large sample of participants, and a sensorimotor task optimized for detecting the shape of the BOLD response to brief stimulation, we first characterised the effects of age on descriptive features of the response (e.g., peak amplitude and latency). We then compared these to features from more complex nonlinear models, fit to four regions of interest engaged by the task, namely left auditory cortex, bilateral visual cortex, left (contralateral) motor cortex and right (ipsilateral) motor cortex. Finally, we validated the extent to which parameter estimates from these models have predictive validity, in terms of how well they predict age in cross-validated multiple regression. We conclude that age-related differences in the BOLD response can be captured effectively by models with three free parameters. Furthermore, we show that biophysical models like the HDM have predictive validity comparable to more common models, while additionally providing insights into underlying mechanisms, which go beyond descriptive features like peak amplitude or latency, and include estimation of nonlinear effects. Here, the HDM revealed that most of the effects of age on the BOLD response could be explained by an increased rate of vasoactive signal decay and decreased transit rate of blood, rather than changes in neural activity per se. However, in the absence of other types of neural/hemodynamic data, unique interpretation of HDM parameters is difficult from fMRI data alone, and some brain regions in some tasks (e.g., ipsilateral motor cortex) can show responses that are more difficult to capture using current models.

Abstract Image

评估老化 BOLD 反应模型
使用 fMRI 无法直接观察到神经活动,而必须根据神经活动引起的血液动力学反应来推断。使用前向模型可以解决这一逆向问题,该模型根据假设的潜在神经活动生成预测的血液动力学反应。常用的血液动力学模型是为了解释健康年轻参与者的数据而开发的;然而,对老龄化和痴呆症的研究正日益将重点转向老年人群。我们评估了一系列健康成年人血液动力学模型的有效性:从常用于分析 fMRI 研究的线性卷积模型的基集,到更先进的模型,包括参数化血液动力学响应函数(HRF)的非线性拟合和生物物理生成模型(血液动力学建模,HDM)的非线性拟合。我们使用了一个特别大的参与者样本和一个为检测短暂刺激下 BOLD 反应形状而优化的感觉运动任务,首先描述了年龄对反应描述性特征(如峰值振幅和延迟)的影响。然后,我们将这些特征与更复杂的非线性模型的特征进行了比较,这些非线性模型拟合了任务所涉及的四个相关区域,即左侧听觉皮层、双侧视觉皮层、左侧(对侧)运动皮层和右侧(同侧)运动皮层。最后,我们根据这些模型在交叉验证多元回归中对年龄的预测程度,验证了这些模型的参数估计在多大程度上具有预测效力。我们的结论是,具有三个自由参数的模型可以有效捕捉 BOLD 反应中与年龄相关的差异。此外,我们还表明,像 HDM 这样的生物物理模型的预测有效性可与更常见的模型相媲美,同时还能提供对潜在机制的见解,这些见解超越了峰值振幅或潜伏期等描述性特征,还包括对非线性效应的估计。在这里,HDM 揭示了年龄对 BOLD 反应的大部分影响可以用血管活性信号衰减率增加和血液转运率降低来解释,而不是神经活动本身的变化。然而,在缺乏其他类型的神经/血流动力学数据的情况下,仅从 fMRI 数据很难对 HDM 参数做出独特的解释,而且某些任务中的某些脑区(如同侧运动皮层)可能会出现目前的模型更难捕捉的反应。
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来源期刊
Human Brain Mapping
Human Brain Mapping 医学-核医学
CiteScore
8.30
自引率
6.20%
发文量
401
审稿时长
3-6 weeks
期刊介绍: Human Brain Mapping publishes peer-reviewed basic, clinical, technical, and theoretical research in the interdisciplinary and rapidly expanding field of human brain mapping. The journal features research derived from non-invasive brain imaging modalities used to explore the spatial and temporal organization of the neural systems supporting human behavior. Imaging modalities of interest include positron emission tomography, event-related potentials, electro-and magnetoencephalography, magnetic resonance imaging, and single-photon emission tomography. Brain mapping research in both normal and clinical populations is encouraged. Article formats include Research Articles, Review Articles, Clinical Case Studies, and Technique, as well as Technological Developments, Theoretical Articles, and Synthetic Reviews. Technical advances, such as novel brain imaging methods, analyses for detecting or localizing neural activity, synergistic uses of multiple imaging modalities, and strategies for the design of behavioral paradigms and neural-systems modeling are of particular interest. The journal endorses the propagation of methodological standards and encourages database development in the field of human brain mapping.
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