A machine learning approach to predict perceptual decisions: an insight into face pareidolia.

ABSTRACT: The perception of an external stimulus not only depends upon the characteristics of the stimulus but is also influenced by the ongoing brain activity prior to its presentation. In this work, we directly tested whether spontaneous electrical brain activities in prestimulus period could predict perceptual outcome in face pareidolia (visualizing face in noise images) on a trial-by-trial basis. Participants were presented with only noise images but with the prior information that some faces would be hidden in these images, while their electrical brain activities were recorded; participants reported their perceptual decision, face or no-face, on each trial. Using differential hemispheric asymmetry features based on large-scale neural oscillations in a machine learning classifier, we demonstrate

SUBMITTER: Barik K 

PROVIDER: S-EPMC6363645 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature