Combining fMRI and Eye-tracking for the Study of Social Cognition.

IF 2.9 Q2 NEUROSCIENCES
Neuroscience Insights Pub Date : 2021-12-16 eCollection Date: 2021-01-01 DOI:10.1177/26331055211065497
Kristin Marie Rusch
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引用次数: 1

Abstract

The study of social cognition with functional magnetic resonance imaging (fMRI) affords the use of complex stimulus material. Visual attention to distinct aspects of these stimuli can result in the involvement of remarkably different neural systems. Usually, the influence of gaze on neural signal is either disregarded or dealt with by controlling gaze of participants through instructions or tasks. However, behavioral restrictions like this limit the study's ecological validity. Thus, it would be preferable if participants freely look at the stimuli while their gaze traces are measured. Yet several impediments hamper a combination of fMRI and eye-tracking. In our recent work on neural Theory of Mind processes in alexithymia, we propose a simple way of integrating dwell time on specific stimulus features into general linear models of fMRI data. By parametrically modeling fixations, we were able to distinguish neural processes asssociated with specific stimulus features looked at. Here, I discuss opportunities and obstacles of this approach in more detail. My goal is to motivate a wider use of parametric models - usually implemented in common fMRI software packages - to combine fMRI and eye-tracking data.

Abstract Image

Abstract Image

结合fMRI和眼动追踪技术研究社会认知。
功能磁共振成像(fMRI)研究社会认知提供了复杂刺激材料的使用。对这些刺激的不同方面的视觉注意会导致涉及到显著不同的神经系统。通常,注视对神经信号的影响要么被忽略,要么通过指令或任务来控制被试的注视。然而,像这样的行为限制限制了研究的生态有效性。因此,如果参与者自由地看着刺激物,同时测量他们的注视轨迹,这将是可取的。然而,有几个障碍阻碍了功能磁共振成像和眼球追踪的结合。在我们最近对述情障碍的神经心理理论过程的研究中,我们提出了一种简单的方法,将特定刺激特征的停留时间整合到fMRI数据的一般线性模型中。通过参数化建模固定,我们能够区分与特定刺激特征相关的神经过程。在这里,我将更详细地讨论这种方法的机遇和障碍。我的目标是推动参数化模型的更广泛使用——通常在通用的功能磁共振成像软件包中实现——将功能磁共振成像和眼动追踪数据结合起来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Neuroscience Insights
Neuroscience Insights Neuroscience-Neuroscience (all)
CiteScore
6.10
自引率
0.00%
发文量
24
审稿时长
9 weeks
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