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Time-domain analysis for extracting fast-paced pupil responses

机译:时域分析用于提取快节奏的瞳孔反应

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摘要

The eye pupil reacts to cognitive processes, but its analysis is challenging when luminance varies or when stimulation is fast-paced. Current approaches relying on deconvolution techniques do not account for the strong low-frequency spontaneous changes in pupil size or the large interindividual variability in the shape of the responses. Here a system identification framework is proposed in which the pupil responses to different parameters are extracted by means of an autoregressive model with exogenous inputs. In an example application of this technique, pupil size was shown to respond to the luminance and arousal scores of affective pictures presented in rapid succession. This result was significant in each subject (N = 5), but the pupil response varied between individuals both in amplitude and latency, highlighting the need for determining impulse responses subjectwise. The same method was also used to account for pupil size variations caused by respiration, illustrating the possibility to model the relation between pupil size and other continuous signals. In conclusion, this new framework for the analysis of pupil size data allows us to dissociate the response of the eye pupil from intermingled sources of influence and can be used to study the relation between pupil size and other physiological signals.
机译:眼瞳对认知过程有反应,但是当亮度变化或刺激快节奏时,其分析是具有挑战性的。当前依赖于去卷积技术的方法不能解决瞳孔大小的强烈低频自发变化或响应形状中较大的个体差异。这里提出了一种系统识别框架,其中通过具有外生输入的自回归模型来提取对不同参数的瞳孔响应。在此技术的示例应用中,显示的瞳孔大小对快速连续呈现的情感图片的亮度和唤醒分数有反应。该结果在每个受试者中都是显着的(N = 5),但是瞳孔反应的幅度和潜伏期在个体之间有所不同,这突出表明需要确定受试者的冲动反应。相同的方法也用于解决由呼吸引起的瞳孔尺寸变化,从而说明了对瞳孔尺寸与其他连续信号之间的关系建模的可能性。总而言之,这种用于分析瞳孔大小数据的新框架使我们能够从混杂的影响源中分离出眼瞳孔的反应,并可用于研究瞳孔大小与其他生理信号之间的关系。

著录项

  • 期刊名称 Scientific Reports
  • 作者

    Alexandre Zénon;

  • 作者单位
  • 年(卷),期 -1(7),-1
  • 年度 -1
  • 页码 41484
  • 总页数 10
  • 原文格式 PDF
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