Autism Facial Expressions
Unveiling the Link Between Autism and Facial Expression Processing
Facial expressions are a core component of social communication, serving as vital non-verbal cues that convey emotions and intentions. For individuals with autism spectrum disorder (ASD), the ability to produce, recognize, and interpret these cues can be markedly different, impacting social interactions and relationship building. This article explores the nuances of facial expressiveness in autism, examining behavioral patterns, neurological underpinnings, technological advances, and implications for social cognition.
Common Facial Expressions and Their Variation in Autism
What are common facial expressions observed in individuals with autism?
Individuals with autism often display differences in facial expressiveness compared to neurotypical individuals. They tend to make less eye contact and have unique gaze patterns, which influence how their facial expressions are perceived.
Autistic individuals typically produce facial expressions that are less frequent and less natural. Their expressions may be more subdued, subtle, or atypical, often making it difficult for others to interpret their emotional state accurately.
While they are capable of genuine emotional expressions, these are sometimes less recognizable or perceived as overly intense or exaggerated by observers unfamiliar with autism. For instance, they might produce smiles or frowns that are similar in strength to those of neurotypical people, but these are less often produced unconsciously and less spontaneously.
Additionally, expressing appropriate emotions in social situations can pose a challenge. They may produce expressions that do not match the social context or emotional experience, leading to misunderstandings in social interactions.
Despite experiencing a full range of emotions internally, the outward display is often less perceptible or may appear idiosyncratic. Such differences in facial expression variables can hinder social communication and the understanding of emotional cues.
Research suggests that these atypical expressions are partly due to differences in internal neural representations of facial emotions. This means that, although the capacity to feel emotion remains intact, the external display and recognition of emotions through facial cues are compromised.
In summary, autistic individuals generally show reduced and sometimes atypical facial expressiveness, which impacts how they communicate and are perceived in social environments.
Facial Features Associated with Autism
What are the facial features that may be associated with autism?
People with autism spectrum disorder (ASD) often exhibit specific facial features that can signal underlying neurodevelopmental factors. These features include a broader top face and a shorter middle face, which are structural variations that differentiate them from neurotypical individuals.
Wider eyes and a broader mouth are frequently observed, adding to the distinct facial morphology associated with ASD. Elevated intercanthal distance, known as hypertelorism, is another characteristic feature. This increased distance between the inner corners of the eyes has gained attention as a potential biomarker for early detection and severity assessment in autism.
Facial asymmetry is also common, especially in regions such as the supraorbital (above the eyes) and periorbital (around the eyes) areas. These asymmetries might reflect atypical brain development patterns.
Interestingly, greater facial masculinity has been linked to ASD, correlating with increased social-communication challenges. Variations in cranio-facial dimensions, including facial height and breadth, help identify subgroups within the spectrum, often aligning with levels of clinical severity and developmental outcomes.
These cranio-facial features are more than superficial traits; they mirror underlying neurodevelopmental processes. Structural anomalies observed in individuals with ASD highlight the importance of facial morphology as potential biomarkers.
Biomarkers and early detection
Research into facial features aims to discover reliable biomarkers for early diagnosis. Features like hypertelorism and specific facial dimensions could support early screening efforts, especially when combined with genetic and behavioral assessments.
Incorporating advanced imaging and 3D facial analysis allows for precise measurement of cranio-facial features. Such technological approaches improve understanding of the developmental pathways involved in ASD.
Facial asymmetry and morphology
Facial asymmetry, particularly in the orbital and peri-orbital regions, suggests atypical neural and muscular development. These morphological differences are often subtle but may be significant when assessing risk factors or condition severity.
Overall, cranio-facial characteristics in individuals with autism provide insights into the neurobiological foundations of the disorder. Recognizing these features not only aids in understanding ASD but also enhances early diagnosis and personalized intervention strategies.
| Feature | Description | Relevance |
|---|---|---|
| Broader top face | Increased width across the upper face | Marker for neurodevelopmental variation |
| Shorter middle face | Reduced facial height in midregion | Reflects cranio-facial development |
| Wider eyes | Increased intercanthal distance | Potential early biomarker |
| Facial asymmetry | Uneven facial regions | Indicates atypical growth |
| Increased masculinity | More prominent features | Correlated with social-communication difficulties |
Search Query
For further exploration, search for "Cranio-facial features and biomarkers in autism" to find detailed studies and latest advances in this field.
Understanding the ‘Autism Smile’ and Social Signaling
What is an autism smile?
An "autism smile" generally refers to atypical smiling behaviors observed in children with autism spectrum disorder (ASD). These smiles often differ from typical social smiles in both frequency and appearance.
Children with autism may produce brief, fleeting smiles that are shorter in duration and less frequent compared to neurotypical children. They might also exhibit delayed social smiling, where the usual timing of smiling in response to social stimuli takes longer.
Recognizing genuine versus atypical smiles can be challenging. Autistic individuals may produce smiles of similar intensity and size as neurotypical controls when they do smile, but these expressions can seem exaggerated or seem less natural to observers.
Furthermore, children with autism often have difficulty recognizing and producing authentic social smiles, which involve more than just lip movement—they require the coordination of emotional understanding and social cues.
Some features of the autism smile include repetitive or limited smiling behaviors, reduced spontaneous mimicry of others’ facial expressions, and limited engagement in social communication.
Understanding these atypical smiling patterns is crucial for early diagnosis and effective intervention. It helps caregivers and clinicians distinguish between different social signaling behaviors and develop strategies that support social engagement and emotional reciprocity.
How do these differences impact social interactions?
Since smiling is a powerful social signal indicating friendliness, cooperation, and emotional sharing, atypical or limited smiles in autism can contribute to misunderstandings or social barriers.
Individuals with autism may appear less approachable or less engaged, influencing how people respond to their social cues. Recognizing the nuances of these facial expressions can guide more empathetic interactions and tailored social skills training.
Are there technological advances in understanding facial expressions?
Recent developments include machine learning algorithms that objectively analyze facial expressions, distinguishing between genuine and atypical smiles with high precision. These tools can quantify subtle facial movements—like microexpressions—that are difficult to observe unaided.
Such technology not only aids in diagnostic assessments but also enhances our understanding of social communication in autism, presenting opportunities for innovative interventions and support systems.
Facial Recognition: Challenges in Autism
How do individuals with autism recognize, imitate, and respond to facial expressions?
Individuals with autism often find it difficult to recognize and interpret facial expressions that convey emotions. This challenge is especially evident with subtle, brief, or spontaneous expressions, which are vital for effective social interactions. Studies show that a large portion, around 63%, of people with autism exhibit significant impairments in facial emotion recognition, impacting their ability to respond appropriately during social exchanges.
Recognizing emotions involves not just identifying facial cues but also understanding their context. Research indicates that these recognition difficulties are generally broad, affecting both receptive skills and the ability to interpret facial features accurately. These problems are not strictly dependent on age or IQ; rather, they tend to persist across the lifespan, although some development of compensatory strategies can occur.
Children with autism might use different visual scanning patterns when observing faces, such as focusing less on critical areas like the eyes or mouth. Interventions, including exposure to service animals or targeted social skills training, can improve these scanning patterns, enabling better recognition over time.
Imitating facial expressions is another area where challenges emerge. Adults with autism, particularly those without intellectual impairment, often imitate less accurately and more slowly than neurotypical individuals. The quality and timing of imitation are linked with how well emotions are recognized, suggesting that better imitation skills support improved emotional understanding.
Responding to facial cues also varies among autistic individuals. Some produce facial expressions that are less intense, less natural, or difficult to interpret, which can hinder social communication. Interestingly, when prompted, many can produce facial expressions of emotion of similar quality to neurotypical individuals, indicating that the difficulties may be rooted more in spontaneous expression and perception rather than in emotional capacity.
Overall, these recognition, imitation, and response challenges contribute to the social difficulties faced by many individuals with autism. However, advances in technology, such as machine learning algorithms, are opening new avenues for objective assessment and tailored interventions that may enhance understanding and communication skills in the future.
| Aspect of Facial Expression | Typical Performance | Challenges in Autism | Additional Insights |
|---|---|---|---|
| Recognition of emotions | Rapid and accurate | Impaired, especially for happiness and neutral faces | Performance can be improved with targeted training |
| Imitation of expressions | Precise and timely | Slower, less detailed | Increases in imitation accuracy support better emotion recognition |
| Spontaneous facial responses | Natural, often matching emotional states | Less natural, more exaggerated or subdued | Prompted expressions improve recognition recognition accuracy |
| Use of technology in assessment | Limited | Emerging, including machine learning tools | May surpass human accuracy and aid intervention |
Understanding these nuances in facial communication helps illuminate the social interaction barriers faced by those with autism and guides the development of supportive therapies and technologies.
Impact of Autism on Facial Expression Production & Recognition
How does autism influence the production and recognition of facial expressions?
Individuals with autism spectrum disorder (ASD) experience notable differences in both creating and interpreting facial expressions. Autistic individuals often produce facial expressions that are less frequent, less natural, and of lower emotional quality. Their expressions—such as smiles or frowns—are typically subtler and shorter in duration compared to neurotypical individuals. While they can produce emotions similar in strength and size to non-autistic controls when prompted, spontaneous expressions tend to be less recognizable.
Research shows that autistic individuals are less likely to unconsciously mimic others’ facial cues during social interactions. This reduced mimicry and synchronization can hinder social bonding and communication. Moreover, their facial expressions often appear exaggerated or odd to observers, even though they report experiencing emotions at comparable levels to neurotypical peers.
On the recognition front, autistic individuals face challenges in accurately identifying emotions from faces. Studies utilizing tasks like the Penn Emotion Recognition Test reveal that they struggle especially with recognizing happiness, and sometimes confuse neutral expressions for negative emotions like anger or sadness. This misinterpretation often correlates with greater communication difficulties and poorer emotional understanding.
Additionally, recognition impairments extend to the rapid detection of facial emotions. People with autism tend to process happy faces more slowly and are less adept at quickly discriminating emotional expressions from neutral or competing stimuli. This slower processing impacts their ability to respond socially in a timely manner.
Imitation studies also show that when instructed, autistic individuals can mimic facial expressions but do so more slowly and less precisely than neurotypical individuals. The quality of imitation—measured by how closely it matches the target expression—relates directly to better emotion recognition accuracy.
What is known about the neurological basis of these difficulties?
Atypical activity in the brain's neural networks influences facial emotion processing in ASD. For example, abnormalities in the amygdala and other regions involved in social cognition and prediction error signaling can impair the internal representation of facial emotions. This disruption makes it challenging for autistics to interpret emotional cues accurately.
Advanced models suggest that the brain’s predictive processing—which helps anticipate and interpret facial movements—is impaired in ASD. Such neural differences contribute to the idiosyncratic and less recognizable facial expressions observed in autistic individuals.
How technology is helping improve understanding
Emerging tools leverage machine learning and AI to analyze microexpressions—tiny facial movements often invisible to the naked eye. These advances aim to create more objective assessments of facial expression production and recognition in ASD.
One promising development is automated systems that evaluate whether facial expressions genuinely convey intended emotions, often surpassing human evaluators in precision. Such tools could eventually aid in early diagnosis and facilitate communication strategies tailored for autistic individuals.
| Aspect | Characteristics | Underlying Factors |
|---|---|---|
| Expression frequency and naturalness | Less frequent; subtler, shorter expressions | Atypical internal representation; reduced mimicry |
| Recognition impairments | Difficulty recognizing happiness; confusion of neutral with negative emotions | Neural prediction errors; delayed processing |
| Neurological basis | Atypical activity in amygdala and related areas | Disrupted emotional processing pathways |
| Technological interventions | Machine learning analysis of microexpressions | Enhanced diagnostic and communication tools |
Understanding these production and recognition challenges helps develop interventions and technologies that improve social interactions and emotional comprehension for individuals with autism.
Microexpressions and Subtle Facial Cues in Autism
What are the facial features that may be associated with autism?
Facial features linked to autism include a broader top face, a shorter middle face, wider eyes, and a wider mouth. Some individuals also exhibit increased intercanthal distance, known as hypertelorism, which may act as a biological marker for early detection and severity of autism.
Facial asymmetry is another characteristic, especially in the supraorbital and periorbital regions—areas around the eyes and forehead. Increased facial masculinity has been observed and appears to be correlated with higher levels of social-communication challenges.
In addition, variations in cranio-facial dimensions such as facial height and breadth are notable. These differences can help identify subgroups within the autism spectrum, often associated with clinical severity and outcomes. Overall, cranio-facial anomalies in ASD reveal underlying neurodevelopmental differences that influence facial structure.
How does micromovement analysis contribute to understanding social communication in autism?
Recent research utilizes micro-movement spike analysis to examine tiny facial movements that are otherwise difficult to detect by the naked eye. These minuscule movements, called microexpressions or micromovements, occur during emotional expressions like smiling or surprise.
Studies show that autistic individuals use the same basic facial movements as neurotypical individuals but tend to produce them with significantly lower intensity. This subtleness makes their expressions less noticeable and less recognizable, affecting social interactions.
Analyzing short videos of spontaneous facial expressions from over 120 participants, including non-speaking individuals, has revealed that these microexpressions are often too subtle for human perception. Tracking these micromovements allows researchers to better understand how emotions are conveyed and perceived.
How are subtle facial expressions and communication challenges related?
Subtle expressions — those that are too faint or brief for easy detection — may hinder accurate emotional recognition in autism. For instance, autistic individuals might produce positive or negative emotions with less intensity, making it challenging for others to interpret their feelings correctly.
Moreover, these microexpressions are influenced by internal neural processes. A neural network model simulating brain functions involved in prediction and emotion recognition indicates that abnormalities in neural activity—particularly in how the brain predicts facial movements—contribute to the difficulty autistic individuals have in expressing and recognizing emotions.
How can improved diagnostic tools aid autistic individuals?
Advances in technology, especially machine learning and AI, are paving the way for better diagnostic tools. Automated systems can objectively measure facial microexpressions, surpassing human ability in precision and consistency.
Using accessible tools like smartphone cameras, these systems analyze subtle facial cues in real-time, offering a non-invasive method for early detection and personalized intervention. By understanding microexpressions' nuances, clinicians can develop targeted therapies to enhance social communication skills.
| Feature | Description | Impact on Autism Diagnosis | Additional Notes |
|---|---|---|---|
| Cranio-facial features | Broader top face, wider eyes, increased intercanthal distance | May serve as early biomarkers | Related to neurodevelopmental processes |
| Micromovement spikes | Tiny facial movements during emotional expressions | Reveal subtleties in social signals | Hard for humans to notice, better analyzed by AI |
| Subtle expressions | Low-intensity facial cues | Contribute to social interaction difficulties | Underlying neural prediction errors |
| Diagnostic technology | Machine learning algorithms | Enhance accuracy of diagnosis | Supports early detection and intervention |
Understanding the subtle nuances of facial expressions in autism not only sheds light on the social-emotional challenges faced but also opens pathways for innovative detection and support methods. Recognizing and interpreting microexpressions could significantly improve social communication and quality of life for autistic individuals.
The Role of Neural Mechanisms and Predictive Processing
How does autism influence the production and recognition of facial expressions?
Autism spectrum disorder (ASD) affects how people produce and interpret facial expressions, often leading to less natural, exaggerated, or less recognizable emotions. Autistic individuals may produce facial expressions that appear overly intense or unusual, making it difficult for others to understand their emotional state. Conversely, their ability to recognize emotions in others' faces can be impaired, especially for happy expressions, which they often misidentify as neutral or negative. These challenges extend to social interactions, where misinterpretations can hinder connection.
Interestingly, while autistic individuals can mimic facial expressions when asked, their imitation is usually slower and less accurate. This correlates with their difficulties in recognizing emotions, as both aspects rely on similar neural processes. Neurological studies suggest that variations in activity within brain regions like the amygdala and prefrontal cortex contribute to these differences, affecting how facial movements are processed and understood.
Neurological underpinnings
Research shows that abnormalities in neural activity influence emotional processing in autism. For example, atypical development or functioning of the amygdala, a brain area crucial for emotion recognition and response, can lead to impairments in perceiving and producing facial expressions. Some studies utilize neural network models that mimic the brain's predictive processing, showing how prediction errors and abnormal neural connectivity can cause challenges in interpreting facial cues.
Predictive coding models
Predictive coding refers to the brain's ability to anticipate sensory input, facilitating smooth social interactions. In the context of autism, models suggest that the brain's predictions about facial expressions are often inaccurate or less efficient, contributing to the recognition and production difficulties observed. These models organize emotions into neural clusters based on predictions, but in ASD, disrupted prediction error mechanisms may hinder this process, leading to less accurate or exaggerated expression recognition.
Brain abnormalities and emotion recognition
Such neural differences may result in an identity where facial expressions are perceived as too subtle, exaggerated, or atypical, affecting spontaneous social interactions. For example, individuals with autism might use the same facial muscles as neurotypical people but with less intensity, or their facial movements may not align well with emotional contexts. These neural factors explain why emotion recognition, especially of genuine expressions, remains a challenge despite the capacity to experience emotions as intensely as neurotypical individuals.
Understanding these neural mechanisms provides crucial insight into autism's social and emotional challenges. It also aids in developing targeted interventions and technologies—like machine learning algorithms—that leverage neural prediction models to better diagnose and support communication in autistic individuals.
Expressive Intensity and Sociocultural Factors
What are the common facial expressions observed in individuals with autism?
People with autism spectrum disorder (ASD) often display facial expressions that are less frequent and less natural compared to neurotypical individuals. They may have reduced eye contact and gaze patterns, which are essential cues in social interactions. Their facial expressions tend to be subtle, fleeting, or atypical, making it challenging for others to interpret their emotional state.
While autistic individuals can experience a wide range of emotions internally, their external expressions sometimes appear exaggerated or unusual, especially to those unfamiliar with autism. For instance, they might produce smiles or frowns that differ in timing, intensity, or duration. These differences can lead to misunderstandings in social settings, as their expressions may not align with the emotional context or may be less recognizable.
Despite facing these challenges, research shows that when they do produce facial expressions like smiles or frowns, these can be of similar strength and amplitude as those of neurotypical individuals. The key difference lies in the subtlety and frequency of these expressions, which can hinder effective social communication and perceived emotional authenticity.
How does expression intensity vary across different cultures?
Cultural norms significantly influence how facial expressions are created and interpreted. Some cultures prefer more expressive faces, encouraging outward displays of emotion, while others value restraint and subtlety. For individuals with autism, cultural context can either mitigate or amplify the perception of their emotional expressions.
In cultures that highly value expressive behavior, subtle expressions may be overlooked or misunderstood, leading to social challenges for autistic individuals. Conversely, in cultures that emphasize control and minimal expression, autistic expressions—already subtle—may blend in more easily, but misunderstanding still remains a concern.
Furthermore, cultural expectations shape the perception of what constitutes an appropriate expression. For example, a slight smile in one culture might be seen as genuine friendliness, while in another, it might appear unnatural or insufficient. This variability emphasizes the importance of understanding cultural norms when assessing facial expressions in autism.
What is the impact on social perception?
The differences in facial expression intensity and style directly influence how others perceive and respond to individuals with autism. Less expressive faces can lead to social misinterpretations, such as assuming lack of emotion or disinterest. This can affect the development of social bonds, trust, and mutual understanding.
Moreover, the tendency for autistic expressions to appear atypical or exaggerated can evoke perceptions of oddity or insensitivity, although the individuals still experience emotions deeply. Recognizing these patterns is crucial for fostering inclusive social environments.
Modern tools like machine learning algorithms are now being developed to objectively evaluate facial expressions, helping differentiate between genuine and atypical expressions. These technologies might enhance social interactions by providing feedback or aids to interpret subtle expressions, broadening the understanding between autistic and neurotypical individuals.
| Aspect | Typical Expression | Autistic Expression | Cultural Influence |
|---|---|---|---|
| Frequency | Frequent, spontaneous | Less frequent, subtle | Varies by norms |
| Intensity | Moderate to high | Often low, subtle | Norm-dependent |
| Recognition | Easily recognizable | Less recognizable, idiosyncratic | Affects interpretation |
| Impact on social perception | Positive, engaging | Misinterpreted, perceived as odd | Norms shape understanding |
Understanding the nuances of facial expressions in autism, influenced by cultural context and individual differences, can pave the way for more effective social communication strategies and inclusive practices.
Technological Advances and Future Directions
How are new technologies transforming the analysis of facial expressions in autism?
Recent advancements in technology, particularly machine learning and artificial intelligence (AI), are dramatically changing how facial expressions in individuals with autism are studied and understood. Traditional methods relied largely on human observation, which can be subjective and limited by human perceptual capabilities.
Modern systems employ machine learning algorithms to analyze subtle facial movements called microexpressions, as well as spontaneous facial cues. These automated tools are capable of objectively assessing whether a person’s facial expression accurately conveys an intended emotion. In many cases, they even outperform human experts in precision and consistency.
One of the most promising developments is the use of accessible devices such as smartphones equipped with cameras. These can capture facial expressions in naturalistic settings and feed the data into AI models for real-time analysis. Such tools enable researchers and clinicians to identify atypical expressiveness more accurately and efficiently.
The implications for diagnosis are significant. Automated facial analysis can aid early detection of autism spectrum disorder (ASD) by recognizing atypical patterns of facial movement, which are often challenging to detect through traditional assessments. Furthermore, AI-powered tools can be used to develop personalized communication support programs, helping individuals with autism improve their social interaction skills.
Beyond individual assessment, these technologies contribute to large-scale research efforts by providing standardized, quantifiable data on facial expressiveness and emotion recognition. This data can help refine our understanding of social-emotional processing in autism.
Looking ahead, the integration of machine learning and AI into diagnostic and intervention practices promises to foster more inclusive, effective, and accessible support systems. Such innovations could significantly enhance the quality of life for autistic individuals by improving emotional awareness, social communication, and community integration.
Implications for Social Communication and Intervention Strategies
How do differences in facial expression production affect social interactions for autistic individuals?
Variations in how people with autism produce and interpret facial expressions can significantly influence their social experiences. When facial cues are less expressive, ambiguous, or atypical, it can create misunderstandings during interactions. For instance, individuals might appear detached or unresponsive, leading others to misjudge their emotional state.
These challenges often hinder the formation of social bonds and can contribute to feelings of isolation. Recognizing this, researchers and clinicians are exploring ways to help autistic individuals improve their social communication through targeted interventions.
How can training improve facial recognition and production skills?
Training programs focusing on recognizing and producing facial expressions are gaining popularity. Some methods include adaptive computer-based tools and AI-driven systems that provide real-time feedback. These technologies can analyze subtle facial movements—microexpressions—that are typically too brief or subtle for the naked eye.
For example, an automated system utilizing machine learning can assess whether a person’s facial expression accurately conveys the intended emotion. Such tools often outperform human observers in precision, offering detailed insights into subtle facial cues.
Other approaches involve direct training where individuals are instructed to mimic expressions or interpret faces in various social scenarios. Regular practice has been associated with improved accuracy both in recognizing others’ emotions and in producing more recognizable facial expressions.
What is the impact of these findings on neurodevelopmental therapies?
Understanding the role of facial expressions in social communication informs the design of neurodevelopmental interventions. Therapies can integrate exercises to enhance facial expressiveness and emotion recognition, addressing core social challenges faced by individuals with autism.
For example, incorporating biofeedback or virtual reality simulations allows individuals to practice social interactions in a controlled, supportive environment. These techniques help develop internal representations of emotional expression, which are often atypical in autism.
Moreover, leveraging accessible technologies like smartphone cameras and AI algorithms makes such training scalable and customizable. This approach allows for personalized therapy plans that adapt to individual progress and needs.
In summary, improving facial expression skills through innovative training and technology not only enhances social understanding but also supports broader goals of emotional intelligence and social adaptability. As these methods continue to evolve, they hold promise for fostering more authentic and effective communication for autistic individuals.
| Aspect | Approach | Benefits | Example Tools |
|---|---|---|---|
| Recognition | AI feedback systems | Precise analysis of subtle expressions | Smartphone apps, specialized software |
| Production | Mimicry and facial exercises | Increased recognizability of expressions | Virtual reality, biofeedback sensors |
| Social Integration | Peer-led role-playing | Improved real-world social skills | Group therapy, simulated interactions |
Towards a Better Understanding and Support for Autistic Social Communication
Advances in understanding the neural, behavioral, and technological aspects of facial expressions in autism are paving the way for improved diagnosis, intervention, and social integration strategies. Recognizing the unique facial expressiveness and perception patterns in autistic individuals not only enhances our scientific knowledge but also fosters more inclusive social environments. As new tools and therapies continue to evolve, they hold the promise of empowering autistic individuals to navigate social landscapes more effectively, ultimately enriching their emotional lives and social relationships.
References
- People with autism sometimes give ambiguous looks - The Transmitter
- Autistic Subjects' Facial Expressions Don't Always Mirror Emotions
- Can Neurotypical Individuals Read Autistic Facial Expressions ...
- Tracking Tiny Facial Movements Can Reveal Subtle Emotions in ...
- Misinterpretation of Facial Expressions of Emotion in Verbal Adults ...
- Why People With Autism Read Facial Expressions Differently
- Alexithymia, but not autism spectrum disorder, may be related to the ...