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Superposition Model Predicts EEG Occipital Activity during Free Viewing of Natural Scenes

机译:叠加模型可预测自由观看自然场景时的脑电枕活动

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摘要

Visual event-related potentials (ERPs) produced by a stimulus are thought to reflect either an increase of synchronized activity or a phase realignment of ongoing oscillatory activity, with both mechanisms sharing the assumption that ERPs are independent of the current state of the brain at the time of stimulation. In natural viewing, however, visual inputs occur one after another at specific subject-paced intervals through unconstrained eye movements. We conjecture that during natural viewing, ERPs generated after each fixation are better explained by a superposition of ongoing oscillatory activity related to the processing of previous fixations, with new activity elicited by the visual input at the current fixation. We examined the electroencephalography (EEG) signals that occur in humans at the onset of each visual fixation, both while subjects freely viewed natural scenes and while they viewed a black or gray background. We found that the fixation ERPs show visual components that are absent when subjects move their eyes on a homogeneous gray or black screen. Single-trial EEG signals that comprise the ERP are predicted more accurately by a model of superposition than by either phase resetting or the addition of evoked responses and stimulus-independent noise. The superposition of ongoing oscillatory activity and the visually evoked response results in a modification of the ongoing oscillation phase. The results presented suggest that the observed EEG signals reflect changes occurring in a common neuronal substrate rather than a simple summation at the scalp of signals from independent sources.
机译:刺激产生的与视觉事件相关的电位(ERP)被认为反映了同步活动的增加或正在进行的振荡活动的相位重新排列,两种机制都共享这样的假设:ERP独立于大脑当前的大脑状态。刺激时间。但是,在自然观看中,视觉输入会通过不受限制的眼睛运动以特定的对象定间隔连续出现。我们推测,在自然观察期间,每次固定后生成的ERP都可以通过与先前固定的处理相关的正在进行的振荡活动的叠加来更好地解释,而新的活动由当前固定的视觉输入引起。我们检查了在每次视觉注视开始时在人类中发生的脑电图(EEG)信号,而受试者自由观看自然场景时,以及他们观看黑色或灰色背景时。我们发现,当对象在均质的灰色或黑色屏幕上移动眼睛时,注视ERPs会显示缺少的视觉组件。通过叠加模型比通过相位重置或诱发反应和刺激无关的噪声相加能更准确地预测包含ERP的单次EEG信号。正在进行的振荡活动和视觉诱发的响应的叠加导致正在进行的振荡阶段的改变。提出的结果表明,观察到的EEG信号反映了在常见神经元基质中发生的变化,而不是来自独立来源的信号头皮上的简单求和。

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