Early cortical sensitivity and speeded target selection underlie incidentally learned prioritization of visual features

优先次序 刺激(心理学) N2pc 脑电图 计算机科学 感觉系统 大脑活动与冥想 意识的神经相关物 心理学 认知心理学 认知 感知 人工智能 神经科学 视觉感受 管理科学 经济
作者
Kevin Ortego,Douglas A. Addleman,Viola S. Störmer
出处
期刊:The Journal of Neuroscience [Society for Neuroscience]
卷期号:: e0607252025-e0607252025
标识
DOI:10.1523/jneurosci.0607-25.2025
摘要

Adaptive behavior relies on prioritizing relevant sensory information, and decades of research have shown that current task goals and stimulus saliency influence this prioritization. Recent behavioral work indicates that incidental experience with frequently relevant locations or non-spatial features also shapes behavioral prioritization. The present study investigates the neural processing stages affected by incidental learning of non-spatial visual features. We recorded neural activity with high temporal resolution using electroencephalography while human participants (female and male) searched for visual targets that had predictable features (i.e. that appeared more frequently in a particular color). We found that incidental learning of the statistical structure was accompanied by an early differentiation of neural activity for relevant compared to irrelevant features beginning at ∼120ms post stimulus onset, followed by an earlier-onset selection of the target item, as indexed by a latency shift of the N2pc (∼200ms), and changes in later memory and response-related processes, marked by amplitude modulations of the LPC (>400ms). Importantly, the magnitude of the effects across all three neural measures strongly tracked individual differences in the behavioral benefits of learned prioritization, suggesting that successful learning of feature regularities depends on modulating the flow of information across multiple processing stages. Significance Statement The human brain is highly sensitive to the statistical structure of the sensory environment. Behavioral work has shown that participants rapidly learn what spatial locations or visual features are more frequently relevant in a task, and can exploit these regularities to improve task performance. In the present study, we tested how incidental learning of statistical regularities influences neural processing. By measuring the brain’s responses with high temporal resolution, we found that incidental learning changes patterns of neural activity in early processing stages, accelerates subsequent attentional selection, and modulates later memory-related activity. These neural changes were stronger in participants who learned more effectively. Overall, this demonstrates that incidental experience can shape the flow of information across multiple stages of neural processing.
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