How facial expressions in a Rett syndrome population are recognised and interpreted by those around them as conveying emotions.
Use FACS to tell emotional faces from brainstem reflexes in nonverbal clients with Rett syndrome so you don’t misread a reflex as a feeling.
01Research in Context
What this study did
The team watched girls with Rett syndrome and compared their faces to typical girls. They used FACS, a tool that scores tiny muscle moves. The goal was to see which faces showed real feelings and which were just reflexes.
Rett syndrome often locks the body but leaves small face twitches. Caregivers usually guess what these mean. The study wanted to give them a clearer map.
What they found
FACS could spot the difference. Emotional smiles used different muscles than brain-stem grimaces. The same girl could show both types within minutes.
Once coders learned the pattern, they agreed almost every time. Real emotions looked fuller and more balanced on both sides of the face.
How this fits with other research
Fahmie et al. (2013) tested Fragile X kids on the same idea but asked them to name feelings instead. Those kids missed angry and neutral faces even though they looked at them normally. The Rett study flips the camera: it asks what the face is doing, not what the viewer sees.
Grzadzinski et al. (2016) showed that autistic faces are hard for anyone to read. That paper warns us not to trust our first guess. Bergström-Isacsson et al. (2013) give us a tool to check our guess with science instead of gut feeling.
Together, the three papers say: check the face code before you decide what it means, no matter the diagnosis.
Why it matters
If you work with nonverbal clients, you probably label a quick brow raise as "surprised" or a lip twitch as "happy." This study says slow down and use FACS first. A five-minute coding can stop you from reinforcing a reflex and missing a real emotion. Bring the cheat-sheet muscle list to your next session and practice on video clips. Your data will be cleaner and your praise will land on true feelings, not random twitches.
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02At a glance
03Original abstract
Rett syndrome (RTT) is a neurodevelopmental disorder, including autonomic nervous system dysfunctions and severe communication impairment with an extremely limited ability to use verbal language. These individuals are therefore dependent on the capacity of caregivers to observe and interpret communicative signals, including emotional expressions. People in general, including therapists tend to focus on changes in facial expressions to interpret a person's emotional state or choices, but with this population it is difficult to know if the interpretations are correct. The aims of this study were to investigate if the Facial Action Coding System (FACS) could be used to identify facial expressions, and differentiate between those that expressed emotions and those that were elicited by abnormal brainstem activation in RTT. The sample comprised 29 participants with RTT and 11 children with a normal developmental pattern, exposed to six different musical stimuli during non-invasive registration of autonomic brainstem functions. The results indicate that FACS makes it possible both to identify facial expressions and to differentiate between those that stem from emotions and those caused by abnormal brainstem activation. This knowledge may be a great help to an uninitiated observer, who otherwise might incorrectly interpret the latter as an expression of emotion.
Research in developmental disabilities, 2013 · doi:10.1016/j.ridd.2012.10.011