Nicholls Victoria I, Alsbury-Nealy Benjamin, Krugliak Alexandra, Clarke Alex
Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, UK.
Department of Psychology, University of Toronto, Toronto, M5S 3G3, Canada.
Wellcome Open Res. 2023 Jul 14;7:165. doi: 10.12688/wellcomeopenres.17856.2. eCollection 2022.
The environments that we live in impact on our ability to recognise objects, with recognition being facilitated when objects appear in expected locations (congruent) compared to unexpected locations (incongruent). However, these findings are based on experiments where the object is isolated from its environment. Moreover, it is not clear which components of the recognition process are impacted by the environment. In this experiment, we seek to examine the impact real world environments have on object recognition. Specifically, we will use mobile electroencephalography (mEEG) and augmented reality (AR) to investigate how the visual and semantic processing aspects of object recognition are changed by the environment. We will use AR to place congruent and incongruent virtual objects around indoor and outdoor environments. During the experiment a total of 34 participants will walk around the environments and find these objects while we record their eye movements and neural signals. We will perform two primary analyses. First, we will analyse the event-related potential (ERP) data using paired samples t-tests in the N300/400 time windows in an attempt to replicate congruency effects on the N300/400. Second, we will use representational similarity analysis (RSA) and computational models of vision and semantics to determine how visual and semantic processes are changed by congruency. Based on previous literature, we hypothesise that scene-object congruence would facilitate object recognition. For ERPs, we predict a congruency effect in the N300/N400, and for RSA we predict that higher level visual and semantic information will be represented earlier for congruent scenes than incongruent scenes. By collecting mEEG data while participants are exploring a real-world environment, we will be able to determine the impact of a natural context on object recognition, and the different processing stages of object recognition.
我们生活的环境会影响我们识别物体的能力，与出现在意外位置（不一致）相比，当物体出现在预期位置（一致）时，识别会更容易。然而，这些发现是基于物体与其环境隔离的实验。此外，尚不清楚识别过程的哪些组成部分会受到环境的影响。在本实验中，我们试图研究现实世界环境对物体识别的影响。具体而言，我们将使用移动脑电图（mEEG）和增强现实（AR）来研究物体识别的视觉和语义处理方面如何因环境而改变。我们将使用AR在室内和室外环境周围放置一致和不一致的虚拟物体。在实验过程中，共有34名参与者将在这些环境中走动并找到这些物体，同时我们记录他们的眼球运动和神经信号。我们将进行两项主要分析。首先，我们将在N300/400时间窗口中使用配对样本t检验分析事件相关电位（ERP）数据，试图复制N300/400上的一致性效应。其次，我们将使用表征相似性分析（RSA）以及视觉和语义的计算模型来确定视觉和语义过程如何因一致性而改变。基于先前的文献，我们假设场景 - 物体一致性将促进物体识别。对于ERP，我们预测N300/N400中会出现一致性效应，对于RSA，我们预测与不一致场景相比，一致场景中更高层次的视觉和语义信息将更早地得到表征。通过在参与者探索现实世界环境时收集mEEG数据，我们将能够确定自然环境对物体识别的影响以及物体识别的不同处理阶段。
