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扫视抑制揭示了人类大脑中自动和自愿信号的时间。

Saccadic inhibition reveals the timing of automatic and voluntary signals in the human brain.

机构信息

Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, CF10 3AT, Cardiff, United Kingdom.

出版信息

J Neurosci. 2011 Aug 31;31(35):12501-12. doi: 10.1523/JNEUROSCI.2234-11.2011.

Abstract

Neurophysiological and phenomenological data on sensorimotor decision making are growing so rapidly that it is now necessary and achievable to capture it in biologically inspired models, for advancing our understanding in both research and clinical settings. However, the main impediment in moving from elegant models with few free parameters to more complex biological models in humans lies in constraining the more numerous parameters with behavioral data (without human single-cell recording). Here we show that a behavioral effect called "saccadic inhibition" (1) is predicted by existing complex (neuronal field) models, (2) constrains crucial temporal parameters of the model, precisely enough to address individual differences, and (3) is not accounted for by current simple decision models, even after significant additions. Visual onsets appearing while an observer plans a saccade knock out a subpopulation of saccadic latencies that would otherwise occur, producing a clear dip in the latency distribution. This overlooked phenomenon is remarkably well time locked across conditions and observers, revealing and characterizing a fast automatic component of visual input to oculomotor competition. The neural field model not only captures this but predicts additional features that are borne out: the dips show spatial specificity, are lawfully modulated in contrast, and occur with S-cone stimuli invisible to the retinotectal route. Overall, we provide a way forward for applying precise neurophysiological models of saccade planning in humans at the individual level.

摘要

关于感觉运动决策的神经生理学和现象学数据增长如此之快,以至于现在有必要并且可以在受生物启发的模型中捕捉它,从而在研究和临床环境中增进我们的理解。然而,从具有少量自由参数的优雅模型向更复杂的人类生物学模型迈进的主要障碍在于,用行为数据(无人类单细胞记录)来约束更多的参数。在这里,我们表明,一种称为“眼跳抑制”的行为效应(1)可以由现有的复杂(神经元场)模型预测,(2)精确地约束了模型的关键时间参数,足以解决个体差异问题,(3)即使在大量添加后,也不能由当前的简单决策模型来解释。当观察者计划进行眼跳时,视觉起始会消除否则会出现的一部分眼跳潜伏期,从而导致潜伏期分布出现明显的下降。这种被忽视的现象在不同条件和观察者之间具有极好的时间锁定性,揭示并描述了视觉输入到眼球运动竞争的快速自动成分。该神经场模型不仅可以捕捉到这一点,还可以预测出其他一些已被证实的特征:潜伏期下降具有空间特异性,在对比度上有规律地调制,并且在 S 锥体刺激下发生,而 S 锥体刺激对视网膜 - 视路是不可见的。总的来说,我们为在个体水平上将精确的眼跳规划神经生理学模型应用于人类提供了一种方法。

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