METHODS: The current work uses convolutional networks to decode neural signals during a free-viewing visual search task in a closed-loop paradigm within an open-world virtual environment. From the decoded activity we construct fixation-locked response profiles that enable estimations of the variable latency of any P300 analogue around the moment of fixation. We then use these estimates to investigate which factors best reduce variable latency and, thus, predict the onset time of the response. We consider measurable, search-related factors encompassing top-down (i.e., goal driven) and bottom-up (i.e., stimulus driven) processes, such as fixation duration and salience. We also consider saccade size as an intermediate factor reflecting the integration of these two systems.
RESULTS: The results show that of these factors only saccade size reliably determines the onset time of P300 analogous activity for this task. Specifically, we find that for large saccades the variability in response onset is small enough to enable analysis using traditional ensemble averaging methods.
CONCLUSIONS: The results show that P300 analogous activity does occur during closed-loop, free-viewing visual search while highlighting distinct differences between the open-loop version of this response and its real-world analogue. The results also further establish saccades, and saccade size, as a key factor in real-world visual processing.
方法:当前的工作使用卷积网络在开放世界虚拟环境中以闭环范式的自由观看视觉搜索任务期间解码神经信号。从解码的活动中,我们构建了固定锁定的响应曲线,可以估计固定时刻附近任何P300类似物的可变延迟。然后,我们使用这些估计来调查哪些因素最好地减少可变延迟,因此,预测反应的开始时间。我们认为是可衡量的,与搜索相关的因素包括自上而下(即,目标驱动)和自下而上(即,刺激驱动)过程,如固定持续时间和显着性。我们还认为扫视大小是反映这两个系统集成的中间因素。
结果:结果表明,在这些因素中,只有扫视大小可靠地决定了P300类似活动的开始时间。具体来说,我们发现,对于大型扫视,响应发作的变异性足够小,可以使用传统的集合平均方法进行分析。
结论:结果表明,P300类似活动确实发生在闭环过程中,免费观看视觉搜索,同时突出显示该响应的开环版本与其真实世界模拟之间的明显差异。结果还进一步建立了扫视,和扫视大小,作为现实世界视觉处理的关键因素。