Exploring emotional expression recognition in aging adults using the Moving Window Technique

Abstract

Adult aging is associated with difficulties in recognizing negative facial expressions such as fear and anger. However, happiness and disgust recognition is generally found to be less affected. Eye-tracking studies indicate that the diagnostic features of fearful and angry faces are situated in the upper regions of the face (the eyes), and for happy and disgusted faces in the lower regions (nose and mouth). These studies also indicate age-differences in visual scanning behavior, suggesting a role for attention in emotion recognition deficits in older adults. However, because facial features can be processed extrafoveally, and expression recognition occurs rapidly, eye-tracking has been questioned as a measure of attention during emotion recognition. In this study, the Moving Window Technique (MWT) was used as an alternative to the conventional eye-tracking technology. By restricting the visual field to a moveable window, this technique provides a more direct measure of attention. We found a strong bias to explore the mouth across both age groups. Relative to young adults, older adults focused less on the left eye, and marginally more on the mouth and nose. Despite these different exploration patterns, older adults were most impaired in recognition accuracy for disgusted expressions. Correlation analysis revealed that among older adults, more mouth exploration was associated with faster recognition of both disgusted and happy expressions. As a whole, these findings suggest that in aging there are both attentional differences and perceptual deficits contributing to less accurate emotion recognition.

Fig 1

(A) Example of unblurred faces showing anger, fear, happiness, and disgust. (B) Example of the same expressions blurred and the movable window. (C) The regions of interest. Note, publication of the NimStim models included in this Fig is in accordance with the terms of agreement for the stimulus set, which can be found at http://www.macbrain.org/resources.htm.

Fig 2

(A) percentage of exploration time by regions of interest and age group; * indicates a signficant group difference (p < .05). (B) percentage of exploration time by regions of interest and emotion. YA = younger adults; OA = older adults; Error bars represent standard error of the mean. Note FACE = face remainder (face minus eye_L, eye_R, nose, mouth); HEAD = hairline/ears.

Fig 3. Exploration heat maps showing location of exploration time as a function of age group and time course (1^st third, 2^nd third, 3^rd third) of the exploration session.

Data are pooled across all emotions, since the ROI analysis did not reveal any interactions between age and emotion. Mouse exploration data (x,y) were weighted by exploration time and smoothed with a 48-pixel Gaussian filter. Each individual heat map is scaled from zero time (blue) to the point of maximal exploration time (red).

Fig 4. Last ROI to be explored.

(A) percentage of trials on which exploration ended (i.e., position of the moving window at the end of the trial) on the left eye, right eye, nose, or mouth, broken down by age group; * indicates a signficant group difference (p < .05). (B) percentage of trials on which exploration ended on the left eye, right eye, nose, or mouth, broken down by emotion. YA = younger adults; OA = older adults; Error bars represent standard error of the mean.

Fig 5

Scatter plots of eyes-mouth % difference scores vs. RT for (A) happy faces, (B) disgusted faces. Positive values on the x-axis represent more eye-viewing; negative values represent more mouth-viewing. Lower values on the y-axis indicate shorter response time (i.e., faster detection of emotion).