What the flip? What the P-N flip can tell us about proactive suppression
What the flip? What the P-N flip can tell us about proactive suppression
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DOI：
10.1162/jocn_a_01901
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发表时间：
2022-03
期刊：
影响因子：
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通讯作者：
Joyce Tam;Chloe Callahan-Flintoft;Brad Wyble
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文献类型：
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作者：
Joyce Tam;Chloe Callahan-Flintoft;Brad Wyble
视觉搜索中的显著干扰物是否可以被主动抑制以完全阻止注意捕获一直存在争议，因为主动抑制的发生意味着最初的注意转移并不完全由身体显著性驱动。虽然在EEG中存在Pd成分（与抑制相关）而没有先前的N2 pc成分（与选择相关）已被用作主动抑制的证据，但这些ERP与潜在机制之间的联系并不总是清楚的。这在最近的两篇观察到相同波形模式的论文中得到了例证，其中早期的Pd样成分翻转为N2 pc样成分，但提供了非常不同的解释（Drisdelle & Eimer，Psychophysiology，58（9），1-12，2021; Kerzel & Burra，认知神经科学杂志，32（6），1170-1183，2020）。使用RAGNAROC（Wyble等人，Psychological Review，127（6），1163-1198，2020），一种反射性注意力的计算模型，我们成功地模拟了这种ERP模式，对其现有架构进行了最小的改变，为EEG中的这种翻转提供了一种简约和机械的解释，这与之前的两种解释都是独一无二的。我们的账户支持主动抑制的发生，并证明了将计算建模纳入理论建设的好处。
It has been debated whether salient distractors in visual search can be proactively suppressed to completely prevent attentional capture, as the occurrence of proactive suppression implies that the initial shift of attention is not entirely driven by physical salience. While the presence of a Pd component in the EEG (associated with suppression) without a preceding N2pc component (associated with selection) has been used as evidence for proactive suppression, the link between these ERPs and the underlying mechanisms is not always clear. This is exemplified in two recent papers that observed the same waveform pattern, where an early Pd-like component flipped to a N2pc-like component, but provided very different interpretations (Drisdelle & Eimer, Psychophysiology, 58(9), 1-12, 2021; Kerzel & Burra, Journal of Cognitive Neuroscience, 32(6), 1170-1183, 2020). Using RAGNAROC (Wyble et al., Psychological Review, 127(6), 1163-1198, 2020), a computational model of reflexive attention, we successfully simulated this ERP pattern with minimal changes to its existing architecture, providing a parsimonious and mechanistic explanation for this flip in the EEG that is unique from both of the previous interpretations. Our account supports the occurrence of proactive suppression and demonstrates the benefits of incorporating computational modelling into theory building.