Artificially-Generated Scenes Demonstrate the Importance of Global Properties during Early Scene Perception
Year: 2020
Type: article
Abstract: Artificially-Generated Scenes Demonstrate the Importance of Global Properties during Early Scene Perception.During scene perception, studies have shown the importance of the global distribution of a scene.Electrophysiological studies have found these global effects concentrated corresponding to the second positive and first negative peaks (P2 and N1, respectively) of the Event-related potential (ERP) during the first 600 ms of scene perception.We sought to understand in Experiment 1, to what extent early responses to scenes were driven by mid-level global information such as the degree of naturalness or openness in a scene image in the absence of specific low-and high-level information (color and semantic object detail).This was done using artificially-generated stimuli controlling for two global scene properties (GSPs) of spatial boundary and naturalness while minimizing color and semantic object information.Significant effects were observed on the P2 and N1 components as well as the P1 component.However, the question of whether scene perception is dominated by global or local factors had yet to be answered leading to Experiment 2. During Experiment 2, for half the trials scenes were presented in an inverted orientation.We found only an orientation interaction approaching significance corresponding to the P1 time course.to the authors thesis project Additionally, the author would like to thank his parents, Mbulelo Mzozoyana and Teri Mzozoyana and grandmother, Mildred Sherron, for their continued financial and emotional support throughout the entirety of his education.Finally, the author would like to thank fellow graduate student Birken Noesen for taking time to code the experiments the author was then able to conduct and former undergraduate student Jordan Keller for assisting the author in preparing the participants for the experiments as well as assisting with data organization and statistical analysis.
Author: Mavuso Wesley Mzozoyana
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W3133893712