Can micro-expressions be used as a biomarker for autism spectrum disorder?

Introduction: Early and accurate diagnosis of autism spectrum disorder (ASD) is crucial for effective intervention, yet it remains a significant challenge due to its complexity and variability. Micro-expressions are rapid, involuntary facial movements indicative of underlying emotional states. It is unknown whether micro-expression can serve as a valid bio-marker for ASD diagnosis.

Comprehensive Social Trait Judgments From Faces in Autism Spectrum Disorder.

Processing social information from faces is difficult for individuals with autism spectrum disorder (ASD). However, it remains unclear whether individuals with ASD make high-level social trait judgments from faces in the same way as neurotypical individuals. Here, we comprehensively addressed this question using naturalistic face images and representatively sampled traits.

Identifying Visual Attention Features Accurately Discerning Between Autism and Typically Developing: a Deep Learning Framework.

Atypical visual attention is a hallmark of autism spectrum disorder (ASD). Identifying the attention features accurately discerning between people with ASD and typically developing (TD) at the individual level remains a challenge. In this study, we developed a new systematic framework combining high accuracy deep learning classification, deep learning segmentation, image ablation and a direct measurement of classification ability to identify the discriminative features for autism identification.

Reduced Pupil Oscillation During Facial Emotion Judgment in People with Autism Spectrum Disorder.

People with autism spectrum disorder (ASD) show abnormal face perception and emotion recognition. However, it remains largely unknown whether these differences are associated with abnormal physiological responses when viewing faces. In this study, we employed a sensitive emotion judgment task and conducted a detailed investigation of pupil dilation/constriction and oscillation in high-functioning adult participants with ASD and matched controls.

Review: Posed vs. Genuine Facial Emotion Recognition and Expression in Autism and Implications for Intervention.

Different styles of social interaction are one of the core characteristics of autism spectrum disorder (ASD). Social differences among individuals with ASD often include difficulty in discerning the emotions of neurotypical people based on their facial expressions. This review first covers the rich body of literature studying differences in facial emotion recognition (FER) in those with ASD, including behavioral studies and neurological findings.

Meta-Analyses Support a Taxonomic Model for Representations of Different Categories of Audio-Visual Interaction Events in the Human Brain.

Our ability to perceive meaningful action events involving objects, people, and other animate agents is characterized in part by an interplay of visual and auditory sensory processing and their cross-modal interactions. However, this multisensory ability can be altered or dysfunctional in some hearing and sighted individuals, and in some clinical populations. The present meta-analysis sought to test current hypotheses regarding neurobiological architectures that may mediate audio-visual multisensory processing.

Detection of Genuine and Posed Facial Expressions of Emotion: Databases and Methods.

Facial expressions of emotion play an important role in human social interactions. However, posed expressions of emotion are not always the same as genuine feelings. Recent research has found that facial expressions are increasingly used as a tool for understanding social interactions instead of personal emotions.

Deep Neural Network Reveals the World of Autism From a First-Person Perspective.

People with autism spectrum disorder (ASD) show atypical attention to social stimuli and aberrant gaze when viewing images of the physical world. However, it is unknown how they perceive the world from a first-person perspective. In this study, we used machine learning to classify photos taken in three different categories (people, indoors, and outdoors) as either having been taken by individuals with ASD or by peers without ASD.

Processing of Real-World, Dynamic Natural Stimuli in Autism is Linked to Corticobasal Function.

Many individuals with autism spectrum disorder (ASD) have been shown to perceive everyday sensory information differently compared to peers without autism. Research examining these sensory differences has primarily utilized nonnatural stimuli or natural stimuli using static photos with few having utilized dynamic, real-world nonverbal stimuli. Therefore, in this study, we used functional magnetic resonance imaging to characterize brain activation of individuals with high-functioning autism when viewing and listening to a video of a real-world scene (a person bouncing a ball) and anticipating the bounce.

Divergent Human Cortical Regions for Processing Distinct Acoustic-Semantic Categories of Natural Sounds: Animal Action Sounds vs. Vocalizations.

A major gap in our understanding of natural sound processing is knowledge of where or how in a cortical hierarchy differential processing leads to categorical perception at a semantic level. Here, using functional magnetic resonance imaging (fMRI) we sought to determine if and where cortical pathways in humans might diverge for processing action sounds vs. vocalizations as distinct acoustic-semantic categories of real-world sound when matched for duration and intensity.

Evidence for abnormalities of cortical development in adolescent-onset schizophrenia.

Voxel-Based Morphometry (VBM) identifies differences in grey matter brain structure in patients with schizophrenia relative to healthy controls, with particularly prominent differences found in patients with the more severe, adolescent-onset form of the disease. However, as VBM is sensitive to a combination of changes in grey matter thickness, intensity and folding, specific neuropathological interpretations are not possible. Here, we attempt to more precisely define cortical changes in 25 adolescent-onset schizophrenic patients and 25 age- and sex-matched healthy volunteers using Surface-Based Morphometry (SBM) to disambiguate the relative contributions of cortical thickness and surface area differences to changes in regional grey matter (GM) density measured with VBM.

Usefulness of the CANFOR-S for measuring needs among mentally disordered offenders resident in medium or low secure hospital services in the UK: a pilot evaluation.

Background: The short form of the forensic version of the Camberwell Assessment of Needs (CANFOR-S) (Thomas et al., 2003) is of potential value in all clinical forensic settings, but so far reported mainly with high security hospital patients.

Aims: To conduct a pilot study of the feasibility of using the CANFOR-S in medium and low security hospital units and to report preliminary findings there.