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. 2017 Dec:141:191-203.
doi: 10.1016/j.visres.2016.10.013. Epub 2016 Dec 18.

The categories, frequencies, and stability of idiosyncratic eye-movement patterns to faces

Affiliations

The categories, frequencies, and stability of idiosyncratic eye-movement patterns to faces

Joseph Arizpe et al. Vision Res. 2017 Dec.

Abstract

The spatial pattern of eye-movements to faces considered typical for neurologically healthy individuals is a roughly T-shaped distribution over the internal facial features with peak fixation density tending toward the left eye (observer's perspective). However, recent studies indicate that striking deviations from this classic pattern are common within the population and are highly stable over time. The classic pattern actually reflects the average of these various idiosyncratic eye-movement patterns across individuals. The natural categories and respective frequencies of different types of idiosyncratic eye-movement patterns have not been specifically investigated before, so here we analyzed the spatial patterns of eye-movements for 48 participants to estimate the frequency of different kinds of individual eye-movement patterns to faces in the normal healthy population. Four natural clusters were discovered such that approximately 25% of our participants' fixation density peaks clustered over the left eye region (observer's perspective), 23% over the right eye-region, 31% over the nasion/bridge region of the nose, and 20% over the region spanning the nose, philthrum, and upper lips. We did not find any relationship between particular idiosyncratic eye-movement patterns and recognition performance. Individuals' eye-movement patterns early in a trial were more stereotyped than later ones and idiosyncratic fixation patterns evolved with time into a trial. Finally, while face inversion strongly modulated eye-movement patterns, individual patterns did not become less distinct for inverted compared to upright faces. Group-averaged fixation patterns do not represent individual patterns well, so exploration of such individual patterns is of value for future studies of visual cognition.

Keywords: Eye-movements; Face perception; Face recognition; Idiosyncratic; Individual differences; Pattern similarity measure.

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Figures

Figure 1
Figure 1
Schematic of trial sequences. A face was only presented if the participant successfully maintained fixation for a total of 1.5 seconds. After face onset in the study phase, participants were free to study the face for up to 10 seconds and pressed a button to begin the next trial. In the test phase, faces were presented for one second only and participants responded with button presses to indicate whether the face was ‘old’ or ‘new’.
Figure 2
Figure 2
Distribution of peak eye-movement density among all participants. The four natural clusters are indicated in different dot colors. The underlain face image is the average of all the relevant faces presented during the experiments.
Figure 3
Figure 3
Participants’ spatial density maps for Caucasian faces from the Other-Race experiment ordered by facial recognition performance, as measured by d’. The focal densities on the left and right edges of the face reflect participants’ gaze at left and right pre-stimulus start positions before their first saccades.
Figure 4
Figure 4
Participants’ spatial density maps for upright faces from the Face Orientation experiment ordered by facial recognition performance, as measured by d’.
Figure 5
Figure 5
Discrimination indices within- and between- Time Window (1st – 5th second) for the Other-Race experiment (all Race of Face conditions pooled and Start Position conditions averaged). Discrimination indices within each time window significantly decreased with time. Further, the between- 1st and 5th second discrimination index was not significantly greater than zero and was significantly lower than that for within the 5th second. Error bars represent ± 1 standard error.
Figure 6
Figure 6
Discrimination indices within- and between- Face Orientation (upright, inverted) conditions of the Face Orientation experiment (Start Position conditions averaged). The between-orientation discrimination index was significantly lower than either within-orientation discrimination index. Error bars represent ± 1 standard error.

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