BACKGROUND Although it is well recognized that autism is associated with altered patterns of over- and under-connectivity, specifics are still a matter of debate. Little has been done so far to synthesize available literature using whole-brain electroencephalography (EEG) and magnetoencephalography (MEG) recordings. OBJECTIVES 1) To systematically review the literature on EEG/MEG functional and effective connectivity in autism spectrum disorder (ASD), 2) to synthesize and critically appraise findings related with the hypothesis that ASD is characterized by long-range underconnectivity and local overconnectivity, and 3) to provide, based on the literature, an analysis of tentative factors that are likely to mediate association between ASD and atypical connectivity (e.g., development, topography, lateralization). METHODS Literature reviews were done using PubMed and PsychInfo databases. Abstracts were screened, and only relevant articles were analyzed based on the objectives of this paper. Special attention was paid to the methodological characteristics that could have created variability in outcomes reported between studies. RESULTS Our synthesis provides relatively strong support for long-range underconnectivity in ASD, whereas the status of local connectivity remains unclear. This observation was also mirrored by a similar relationship with lower frequencies being often associated with underconnectivity and higher frequencies being associated with both under- and over-connectivity. Putting together these observations, we propose that ASD is characterized by a general trend toward an under-expression of lower-band wide-spread integrative processes compensated by more focal, higher-frequency, locally specialized, and segregated processes. Further investigation is, however, needed to corroborate the conclusion and its generalizability across different tasks. Of note, abnormal lateralization in ASD, specifically an elevated left-over-right EEG and MEG functional connectivity ratio, has been also reported consistently across studies. CONCLUSIONS The large variability in study samples and methodology makes a systematic quantitative analysis (i.e. meta-analysis) of this body of research impossible. Nevertheless, a general trend supporting the hypothesis of long-range functional underconnectivity can be observed. Further research is necessary to more confidently determine the status of the hypothesis of short-range overconnectivity. Frequency-band specific patterns and their relationships with known symptoms of autism also need to be further clarified.

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Is functional brain connectivity atypical in autism? A systematic review of EEG and MEG studies.

As a starting point for our review we use a developmental timeline, starting from birth and divided into major developmental epochs defined by key milestones of social cognition in typical development. For each epoch, we highlight those developmental disorders that diverge from the normal developmental pattern, what is known about these key milestones in the major disorders affecting social cognition, and any available research on the neural basis of these differences. We relate behavioural observations to four major networks of the social brain, that is, Amygdala, Mentalizing, Emotion and Mirror networks. We focus on those developmental disorders that are characterized primarily by social atypicality, such as autism spectrum disorder, social anxiety and a variety of genetically defined syndromes. The processes and aspects of social cognition we highlight are sketched in a putative network diagram, and include: agent identification, emotion processing and empathy, mental state attribution, self-processing and social hierarchy mapping involving social ‘policing’ and in-group/out-group categorization. Developmental disorders reveal some dissociable deficits in different components of this map of social cognition. This broad review across disorders, ages and aspects of social cognition leads us to some key questions: How can we best distinguish primary from secondary social disorders? Is social cognition especially vulnerable to developmental disorder, or surprisingly robust? Are cascading notions of social development, in which early functions are essential stepping stones or building bricks for later abilities, necessarily correct?

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jcpp.12162

Annual research review: Towards a developmental neuroscience of atypical social cognition.

Recent developments and studies in brain-computer interface (BCI) technologies have facilitated emotion detection and classification. Many BCI studies have sought to investigate, detect, and recognize participants’ emotional affective states. The applied domains for these studies are varied, and include such fields as communication, education, entertainment, and medicine. To understand trends in electroencephalography (EEG)-based emotion recognition system research and to provide practitioners and researchers with insights into and future directions for emotion recognition systems, this study set out to review published articles on emotion detection, recognition, and classification. The study also reviews current and future trends and discusses how these trends may impact researchers and practitioners alike. We reviewed 285 articles, of which 160 were refereed journal articles that were published since the inception of affective computing research. The articles were classified based on a scheme consisting of two categories: research orientation and domains/applications. Our results show considerable growth of EEG-based emotion detection journal publications. This growth reflects an increased research interest in EEG-based emotion detection as a salient and legitimate research area. Such factors as the proliferation of wireless EEG devices, advances in computational intelligence techniques, and machine learning spurred this growth.

Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review

Application of Higuchi's fractal dimension from basic to clinical neurophysiology

This paper proposes the design and application of an immersive virtual reality system to improve and train the emotional skills of students with autism spectrum disorders. It has been designed for primary school students between the ages of 7-12 and all participants have a confirmed diagnosis of autism spectrum disorder. The immersive environment allows the student to train and develop different social situations in a structured, visual and continuous manner. The use of a computer vision system to automatically determine the child's emotional state is proposed. This system has been created with two goals in mind, the first to update the social situations, with the student's emotional mood taken into account, and the second to confirm, automatically, if the child's behavior is appropriate in the represented social situation. The results described in this paper show a significant improvement in the children's emotional competences, in comparison with the results obtained until now using earlier virtual reality systems. Virtual reality to improve the emotional skills of ASD students.Immersive virtual reality system to create social situations where the students can practice their emotional responses.Design and implementation of protocols to evaluate the students' emotional response.Identify, develop and train appropriate emotional behaviors of ASD students.Immersive virtual reality system to create social situations to improve their emotional skills.

/pdf/design-and-application-of-an-immersive-virtual-reality-zwx4h8juxs.pdf

Design and application of an immersive virtual reality system to enhance emotional skills for children with autism spectrum disorders

Autism-Spectrum Disorders (ASD) are thought to be associated with abnormalities in neural connectivity at both the global and local levels. Quantitative electroencephalography (QEEG) is a non-invasive technique that allows a highly precise measurement of brain function and connectivity. This review encompasses the key findings of QEEG application in subjects with ASD, in order to assess the relevance of this approach in characterizing brain function and clustering phenotypes. QEEG studies evaluating both the spontaneous brain activity and brain signals under controlled experimental stimuli were examined. Despite conflicting results, literature analysis suggests that QEEG features are sensitive to modification in neuronal regulation dysfunction which characterize autistic brain. QEEG may therefore help in detecting regions of altered brain function and connectivity abnormalities, in linking behavior with brain activity, and subgrouping affected individuals within the wide heterogeneity of ASD. The use of advanced techniques for the increase of the specificity and of spatial localization could allow finding distinctive patterns of QEEG abnormalities in ASD subjects, paving the way for the development of tailored intervention strategies.

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On the Application of Quantitative EEG for Characterizing Autistic Brain: A Systematic Review

Fusiform Gyrus responses to neutral and emotional faces in children with Autism Spectrum Disorders: a High Density ERP study

Joint attention (JA), whose deficit is an early risk marker for autism spectrum disorder (ASD), has two dimensions: (1) responding to JA and (2) initiating JA. Eye-tracking technology has largely been used to investigate responding JA, but rarely to study initiating JA especially in young children with ASD. The aim of this study was to describe the differences in the visual patterns of toddlers with ASD and those with typical development (TD) during both responding JA and initiating JA tasks. Eye-tracking technology was used to monitor the gaze of 17 children with ASD and 15 age-matched children with TD during the presentation of short video sequences involving one responding JA and two initiating JA tasks (initiating JA-1 and initiating JA-2). Gaze accuracy, transitions and fixations were analyzed. No differences were found in the responding JA task between children with ASD and those with TD, whereas, in the initiating JA tasks, different patterns of fixation and transitions were shown between the groups. These results suggest that children with ASD and those with TD show different visual patterns when they are expected to initiate joint attention but not when they respond to joint attention. We hypothesized that differences in transitions and fixations are linked to ASD impairments in visual disengagement from face, in global scanning of the scene and in the ability to anticipate object's action.

/pdf/disentangling-the-initiation-from-the-response-in-joint-46hmkchap5.pdf

Giulia Campatelli

Papers

On the Application of Quantitative EEG for Characterizing Autistic Brain: A Systematic Review

Fusiform Gyrus responses to neutral and emotional faces in children with Autism Spectrum Disorders: a High Density ERP study

Disentangling the initiation from the response in joint attention: an eye-tracking study in toddlers with autism spectrum disorders

Face processing in children with ASD: Literature review