在检测轻微环境刺激方面,眼动追踪比皮肤传导反应更灵敏

Saman Khazaei, Rose T Faghih
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摘要

皮肤电导(SC)和眼球追踪数据是两种潜在的唤醒相关心理生理信号,可作为对厌恶刺激(如电击)的感知间非条件反应(UR)。目前的研究通过解码隐藏的唤醒和感知间意识(IA)状态,调查了这些信号在检测轻微电击时的灵敏度。虽然已有成熟的框架可从 SC 信号中解码唤醒状态,但还缺乏一种系统的方法可从瞳孔测量和眼球注视测量中解码 IA 状态。我们从眼动数据中提取了基于生理的特征,以恢复与 IA 相关的神经活动。采用贝叶斯过滤框架,我们解码了使用轻微电击的恐惧条件反射和消退实验中的 IA 状态。我们使用从同时收集的 SC 数据中得到的二进制和标记点过程(MPP)观察结果独立解码了潜在的唤醒状态。与从未伴有电击的试验(CS-)相比,在始终伴有电击的试验(CS + US+)中,11 名受试者中有 8 人的 IA 状态明显更高(p 值为 0.001)。根据解码的基于 SC 的唤醒状态,只有 5 名(二元观察)和 4 名(MPP 观察)受试者在 CS + US+ 试验中的唤醒状态明显高于 CS- 试验。总之,从眼动跟踪数据中解码出的隐藏大脑状态与呈现的轻微刺激更吻合。通过眼动跟踪数据追踪内隐状态,可以开发出治疗神经精神疾病和神经退行性疾病的非接触式监测器。
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Eye tracking is more sensitive than skin conductance response in detecting mild environmental stimuli
The skin conductance (SC) and eye tracking data are two potential arousal-related psychophysiological signals that can serve as the interoceptive unconditioned response (UR) to aversive stimuli (e.g., electric shocks). The current research investigates the sensitivity of these signals in detecting mild electric shock by decoding the hidden arousal and interoceptive awareness (IA) states. While well-established frameworks exist to decode the arousal state from the SC signal, there is a lack of a systematic approach that decodes the IA state from pupillometry and eye gaze measurements. We extract the physiological-based features from eye tracking data to recover the IA-related neural activity. Employing a Bayesian filtering framework, we decode the IA state in fear conditioning and extinction experiments where mild electric shock is used. We independently decode the underlying arousal state using binary and marked point process (MPP) observations derived from concurrently collected SC data. 8 of 11 subjects present a significantly (p-value < 0.001) higher IA state in trials that were always accompanied by electric shock (CS + US+) compared to trials that were never accompanied by electric shock (CS−). According to the decoded SC-based arousal state, only 5 (binary observation) and 4 (MPP observation) subjects present a significantly higher arousal state in CS + US+ trials than CS− trials. In conclusion, the decoded hidden brain state from eye tracking data better agrees with the presented mild stimuli. Tracking IA state from eye tracking data can lead to the development of contactless monitors for neuropsychiatric and neurodegenerative disorders.
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