Influence of autistic traits and communication role on eye contact behavior during face-to-face interaction

Abstract

Eye contact is a central component in face-to-face interactions. It is important in structuring communicative exchanges and offers critical insights into others' interests and intentions. To better understand eye contact in face-to-face interactions, we applied a novel, non-intrusive deep-learning-based dual-camera system and investigated associations between eye contact and autistic traits as well as self-reported eye contact discomfort during a referential communication task, where participants and the experimenter had to guess, in turn, a word known by the other individual. Corroborating previous research, we found that participants' eye gaze and mutual eye contact were inversely related to autistic traits. In addition, our findings revealed different behaviors depending on the role in the dyad: listening and guessing were associated with increased eye contact compared with describing words. In the listening and guessing condition, only a subgroup who reported eye contact discomfort had a lower amount of eye gaze and eye contact. When describing words, higher autistic traits were associated with reduced eye gaze and eye contact. Our data indicate that eye contact is inversely associated with autistic traits when describing words, and that eye gaze is modulated by the communicative role in a conversation.

Keywords: Autism; Deep learning; Eye contact; Face-to-face; Gaze convergence.

Figure 1

Graphical illustration of the experimental setup and task, see camera system on table and Android phone on the stand displaying the word. The describer’s hand, holding the wireless mouse, is below the table. Cameras, positioned centrally at 29.5 cm above the table, angled at 30°.

Figure 2

Kernel density estimations for the participants gaze coordinates in the two conditions. The dotted lines enclose the eye area of interest. Facial landmarks (left eye, right eye, and the mouth) used to define the area are shown as small black circles. n = 20.

Figure 3

Boxplot to display the percentage of gaze to the experimenter’s eye area per condition. The box indicates the quartiles of the dataset, and the whiskers extend to represent the remainder of the distribution. p-value is from paired t-test. n = 20.

Figure 4

Partial regression plot, depicting the isolated impact of AQ scores on gaze to the eye while controlling for other factors. Points represent partial relationship and the green line shows the fitted regression model. The 95% CI is shown in faded green. p-value is from t-test.