Investigating the Uncanny Valley Phenomenon Through the Temporal Dynamics of Neural Responses to Virtual Characters

TL;DR

This study explores the neural and perceptual mechanisms behind the Uncanny Valley phenomenon by analyzing EEG responses and self-reports to understand why near-human virtual characters evoke discomfort.

Contribution

It combines neural data and subjective feedback to investigate the cognitive and perceptual origins of the Uncanny Valley effect, offering new insights into its underlying mechanisms.

Findings

Neural responses differ when viewing near-human characters.

Self-reported discomfort correlates with specific neural activity patterns.

Insights into the temporal dynamics of uncanny responses.

Abstract

The Uncanny Valley phenomenon refers to the feeling of unease that arises when interacting with characters that appear almost, but not quite, human-like. First theorised by Masahiro Mori in 1970, it has since been widely observed in different contexts from humanoid robots to video games, in which it can result in players feeling uncomfortable or disconnected from the game, leading to a lack of immersion and potentially reducing the overall enjoyment. The phenomenon has been observed and described mostly through behavioural studies based on self-reported scales of uncanny feeling: however, there is still no consensus on its cognitive and perceptual origins, which limits our understanding of its impact on player experience. In this paper, we present a study aimed at identifying the mechanisms that trigger the uncanny response by collecting and analysing both self-reported feedback and EEG data.