In the Micro Expression Training Tool (METT) [31] participants had to learn to recognize micro expressions in faces.
All groups showed increased positivity for fearful compared to neutral expressions in upright faces, maximal in vicinity to F7 in healthy (Z = 2.51, P = 0.006), to P4 in MTLE-control (Z = 1.36, P = 0.087), and to F8 in MTLE-amygdala (Z = 1.42, P = 0.078) groups.
Critically, we show that the impact of amygdala damage expresses itself at two specific time windows poststimulus onset: 100 150 and 500 600 ms. In addition, we observe differential responses to fearful versus neutral expressions in upright faces during an intervening time window (150 250 ms) that remain intact despite amygdala damage.
For this reason, in order to eliminate the influence of facial muscle movement on thermal distribution in the face, a test face and a neutral-expression face in a computer are re-formed to front-view neutral-expression faces with the use of a wire-frame model and texture mapping.
But it's getting a lot of the same cues (eyes, mouth, expressions) that it would receive in faces with minds.
The number of states (or facial expressions) are automatically determined from the data by unsupervised clustering of expressions of faces in the video.
Emotion expressions sometimes are mixed with the utterance expression in spontaneous face-to-face communication, which makes difficulties for emotion recognition.
Look into the camera when you speak and use the same kind of body language and facial expressions as in a face-to-face meeting, Mr. O'Brien says.
In particular, emotional expressions of faces can convey information with regard to a person's mental states, intentions, or dispositions.
