Nonadditive integration of visual information in ensemble processing

Tongyu Wang; Yuqing Zhao; Jianrong Jia

doi:10.1016/j.isci.2023.107988

Nonadditive integration of visual information in ensemble processing

iScience. 2023 Sep 19;26(10):107988. doi: 10.1016/j.isci.2023.107988. eCollection 2023 Oct 20.

Authors

Tongyu Wang¹, Yuqing Zhao¹, Jianrong Jia^{1

2}

Affiliations

¹ Department of Psychology, Hangzhou Normal University, Hangzhou 311121, Zhejiang, China.
² Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou 311121, Zhejiang, China.

Abstract

Statistically summarizing information from a stimulus array into an ensemble representation (e.g., the mean) improves the efficiency of visual processing. However, little is known about how the brain computes the ensemble statistics. Here, we propose that ensemble processing is realized by nonadditive integration, rather than linear averaging, of individual items. We used a linear regression model approach to extract EEG responses to three levels of information: the individual items, their local interactions, and their global interaction. The local and global interactions, representing nonadditive integration of individual items, elicited rapid and independent neural responses. Critically, only the neural representation of the global interaction predicted the precision of the ensemble perception at the behavioral level. Furthermore, spreading attention over the global pattern to enhance ensemble processing directly promoted rapid neural representation of the global interaction. Taken together, these findings advocate a global, nonadditive mechanism of ensemble processing in the brain.

Keywords: Cognitive neuroscience; Neuroscience; Sensory neuroscience.