Social Interaction Behavior Research Articles

A comprehensive narrative review on psychotherapies for patients with autism spectrum disorders

Autism spectrum disorders (ASD) are complex neurodevelopmental conditions characterized by challenges in social interaction, communication, and repetitive behaviors. Psychotherapeutic interventions must tailor to meet the specific needs of individuals with ASD, given their diverse presentation of symptoms and functioning levels. This narrative review explores the range of psychotherapies available for individuals with ASD, examining their methodologies, effectiveness, and suitability. By using targeted search terms such as “autism,” “autistic disorder,” “autism spectrum disorders,” “psychotherapy,” “psychological intervention,” and “psychosocial intervention,” an extensive review of publications in English from 2000 to 2024 was conducted. This review covered several databases, including Embase, PubMed, Web of Science, Scopus, Cochrane Library, and Google Scholar. The review identified ten major psychological interventions for the treatment of individuals with ASD: behavioral therapies, developmental therapies, cognitive behavioral therapy, social skills training, speech-language therapy, occupational therapy, family therapy, mindfulness-based interventions, parent-mediated interventions, and dance movement psychotherapy. The main text elaborates on the effects of each intervention on various aspects of ASD. By providing this comprehensive overview, clinicians can select appropriate therapeutic strategies that cater to the individual profiles of those with ASD, ultimately enhancing therapeutic outcomes and quality of life for this population.

Coinfection of pulmonary lophomoniasis, tuberculosis, and hydatid cyst in a pediatric autism patient: a case report and literature review

IntroductionAutism Spectrum Disorder (ASD) is a neurodevelopmental condition marked by difficulties in social interaction, communication, and repetitive behaviors or restricted interests. Although research on the link between ASD and parasitic diseases is limited, immune deficiency and inflammation may contribute to the development of parasitic infections.Case reportWe admitted a 14-year-old boy to the hospital who had a known history of ASD because he was presenting with respiratory symptoms, including cough and hemoptysis. During his time in the hospital, after conducting a series of tests and evaluations, we made a critical diagnosis of co-infection of lophomonas, tuberculosis, and hydatid cyst. In response to this diagnosis, we initiated a treatment plan that involved administering appropriate antibiotics as well as preparing for surgical intervention.ConclusionThis case report highlights the complexities and challenges of managing such a rare combination of co-infections with TB, pulmonary hydatid disease and lophomonas in a pediatric patient with underlying developmental considerations such as ASD.

Exploring Women’s Self-Expression and Social Interaction on Social Platforms

With the rapid development of technology, social platforms have become an integral part of people’s daily lives. On these platforms, female users are not only large in number but also highly active, and they actively participate in social interaction through sharing, communication, and expression. Social platforms provide women with unprecedented space for self-expression and opportunities for social interaction, enabling them to connect with others and share their views and experiences across geographical and time constraints. Therefore, it is of great practical significance to explore women’s self-expression and social interaction on new media social platforms. By reviewing relevant literature and selecting some platforms using the case study method to gain a deeper understanding of women’s specific behaviors, feelings, and motivations on these social platforms, the thesis aims to deeply explore women’s self-expression and social interaction behaviors on new media social platforms, analyze how female users present themselves, express their views, and build up their social networks through social media platforms, and explore the challenges and trends facing new media social platforms. It also discusses the challenges and trends of new media social platforms.

O LÚDICO COMO PROPOSTA ESTRATÉGICA PARA O ENSINO, APRENDIZAGEM E DESENVOLVIMENTO DE ESTUDANTES AUTISTAS

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by atypical development, behavioral manifestations, deficits in communication and social interaction, repetitive and stereotyped behavior patterns, and may include a restricted repertoire of interests and activities. It is crucial that schools are concerned with the quality of education, which requires the collective commitment of educators and students, aiming at the integral formation of citizenship through the effective construction of knowledge. In order to better understand autism within the context of regular schools and education for autistic individuals, we chose to conduct a bibliographical research, discussing the theoretical foundations relevant to the study. Upon concluding the research, we observed that the use of play as a pedagogical method can be highly effective with autistic students, providing an interesting and fun approach to learning acquisition. We recognize that autistic students have special educational needs that must be met by teachers in order to promote their development and ensure that they follow the teaching-learning process.

Proposed Hypothesis of TWEAK/Fn14 Receptor Modulation in Autism Spectrum Disorder.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with a complex, multiple etiology that is marked by impaired social interaction, communication, and repetitive behaviour. There is presently no pharmaceutical treatment for the core symptoms of ASD, even though the prevalence of ASD is increasing worldwide. Treatment of autism spectrum disorder involves the interaction of numerous signalling pathways, such as the Wnt/beta-catenin pathway, probiotics and kynurenine pathway, PPAR pathway, PI3K-AKT-mTOR pathway, Hedgehog signaling pathway, etc. The scientific literature has revealed TWEAK/Fn14 to not be explored in the autism spectrum disorder. In vitro and in vivo, TWEAK can control a wide range of cellular responses. Recent research has revealed that TWEAK and Fn14 are expressed in the Central Nervous System (CNS) and upregulated in perivascular endothelial cells, astrocytes, neurons, and microglia in response to various stimuli, including cerebral ischemia. This upregulation is followed by cell death and an increase in Blood-brain Barrier (BBB) permeability. The study has revealed that Aurintricarboxylic Acid (ATA) acts as an agent that suppresses TWEAK/Fn14 signaling. Similarly, from the discussion, it has been emphasized that the proposed molecular TWEAK/Fn14 signalling pathway can be considered as a therapeutic approach in the management of autism spectrum disorder.

Bayesian optimization of one-dimensional convolutional neural networks (1D CNN) for early diagnosis of Autistic Spectrum Disorder

Autistic Spectrum Disorder (ASD) is a challenging neurological development disorder, which involves poor social interaction, communication, and repetitive behaviours. If autism is identified early enough it can be treated with better outcomes but present diagnostic tests are dependent on subjective opinion, consume a lot of time, and are vague. This study is aimed at optimizing one-dimensional convolutional neural networks (1D CNN) to improve the precision and speed of early ASD diagnosis. Four ASD datasets representing different age groups — toddlers, children, adolescents, and adults were modelled using one-dimensional convolutional neural networks (1D CNN). These datasets are accessible to the public on the UCI Machine Learning Repository and Kaggle, they consist of behavioural features relevant to ASD diagnosis. Each dataset underwent feature selection, categorical encoding, and missing value handling. Then, baseline 1D CNN with predefined hyperparameters was modelled on each of the datasets. Subsequently, the baseline models were optimized using the Tree-structured Parzen Estimator (TPE). An interactive web-based ASD diagnostic tool was developed, where user inputs are processed through age-specific pre-trained optimized models to determine ASD probability. The optimized 1D CNN models significantly outperformed the baseline models across all age groups and achieved scores of 100% in accuracy, precision, recall, F1-score, MCC, and AUC ROC. This implies that the optimized models can reliably identify people in various age groups who have and do not have ASD. The development of an interactive web-based diagnostic tool extends the practical utility of the models, making them accessible for clinical and at-home use.

Winning with Losses: The Surprising Success of Negative Strategies in Social Interaction Behavior.

In the vast network of social interactions and behaviors, it is common to find certain schemes that, on their own, might appear counterproductive to societal progress. When observed in isolation, these schemes often seem to hinder more than they help. However, due to society's complexity, the hidden potential of combining these seemingly detrimental schemes often goes unnoticed. Here, we investigate two such social behaviors, reputation and reciprocity, and their role in explaining Darwin's survival of the fittest, examining how these fundamental principles govern individual interactions and shape broader social dynamics. We outline the dynamics of these two social behaviors and underline the importance of combined strategies in enhancing group welfare and contributing to interdisciplinary research in social physics.

The Effect of Observational Learning and Word of Mouth Learning on Consumer Behaviors

This article explores two learning methods of social interaction in social media and e-commerce environments: observational learning and word-of-mouth learning, and their impact on consumer behavior. This article summarize the influence of two learning methods on consumer behavior in social interaction, and their differences. The article found that both observational learning and word-of-mouth learning have a significant impact on consumer behavior, with positive observational learning having a clear effect on information., Negative word-of-mouth learning information has a stronger influence on consumer decision-making. Observational learning enhances external motivation, while word-of-mouth learning stimulates internal motivation. When highly involved in product decision-making, word-of-mouth details are more critical; Low involvement products allow for more effective observation and learning of information. The impact of word-of-mouth learning on long-term decision-making increases over time. Observing and learning information spreads quickly, while word-of-mouth information spreads slowly. Understanding these mechanisms is crucial for e-commerce platforms and sellers to develop marketing strategies.

Exploring the Mechanisms of Neuronal Protection by Glial Cell Line-Derived Neurotrophic Factor in Autism Spectrum Disorder.

A complicated neurological disease known as autism spectrum disorder (ASD) is typified by issues with social interaction, communication, and repetitive behavior. The neural protective mechanisms in ASD are thought to be influenced by genetic variables, including the expression of neurotrophic genes such as glial cell line-derived neurotrophic factor (GDNF). The aim was to examine the relationship between neuronal protection and cognitive functioning by crosslinking GDNF gene expression and serum levels in individuals with relation to Mini-Mental State Examination (MMSE) scores in ASD patients. After getting study approval and informed consent of patients, this case-control study experimental study was conducted for six months between July 2023 and December 2023. The blood samples (5 ml each) were drawn from the study population (n = 140), including 100 ASD patients with a disease course of30 months based on patients' reports data and 40 healthy controls from four major clinical and hospital settings in Lahore, Karachi, and Bahawalpur from Pakistan. The analytical procedures included nucleic acid extraction, primer design and optimization, and GDNF-targeted real-time quantitative polymerase chain reaction expression analysis. To measure cognitive and behavioral deficits, enzyme-linked immunosorbent assay-based serum GDNF levels (pg/ml) and MMSE scores were compared, concluding the neuronal protection potential of GDNF. In patients with ASD, lower serum levels of GDNF (9.371 ± 2.388 pg/ml) were linked to more severe behavioral and cognitive deficits confirmed by MMSE scores (13.6 ± 3.5) of ASD patients in comparison with the control group (27.1 ± 2.1). Healthy individuals showed higher relative gene fold expression (11.71) compared to the ASD patients (5.51). There is a notable decrease in GDNF gene expression in people with ASD, which raises the possibility that GDNF is important for both cognitive performance and neuronal protection in these people. GDNF may be a useful biomarker for identifying ASD and comprehending its molecular causes, opening the door for focused treatment approaches.

Psychometric properties and factor structure of triarchic psychopathy measure (TriPM) in portuguese adolescents

Psychopathy is a personality structure characterized by a set of dysfunctional traits, impulsive and irresponsible behavior, a poor and arrogant personal style in social interactions, and a lack of prosocial emotions. Although it cannot be diagnosed in adolescents, there have been references to its presence in its population. There is substantial evidence indicating a correlation between psychopathy and antisocial and criminal behavior in young people. It is therefore important that psychopathic traits be identified as early as possible to predict and control future criminal behavior. However, the specific evaluation instruments for this population are scarce. The aim of the present study is to validate an instrument for the evaluation of psychopathy, the Triarchic Psychopathy Measure (TriPM), for use with this population. The questionnaires were applied a validation sample of 793 young or Portuguese adolescents. A confirmatory factorial analysis (CFA) was performed, and the results found were considered satisfactory, χ2(1350) = 5980.77, p < .001, RMSEA = .067 (95% CI = [.064 - .068]), CFI = .915, TLI = .910, and SRMR = .080.

Salubrious effects of proanthocyanidins on behavioral phenotypes and DNA repair deficiency in the BTBR mouse model of autism

Autism is a neurodevelopmental disorder distinguished by impaired social interaction and repetitive behaviors. Global estimates indicate that autism affects approximately 1.6% of children, with the condition progressively becoming more prevalent over time. Despite noteworthy progress in autism research, the condition remains untreatable. This serves as a driving force for scientists to explore new approaches to disease management. Autism is linked to elevated levels of oxidative stress and disturbances in the DNA repair mechanism, which may potentially play a role in its comorbidities development. The current investigation aimed to evaluate the beneficial effect of the naturally occurring flavonoid proanthocyanidins on the behavioral characteristics and repair efficacy of autistic BTBR mice. Moreover, the mechanisms responsible for these effects were clarified. The present findings indicate that repeated administration of proanthocyanidins effectively reduces altered behavior in BTBR animals without altering motor function. Proanthocyanidins decreased oxidative DNA strand breaks and accelerated the rate of DNA repair in autistic animals, as evaluated by the modified comet test. In addition, proanthocyanidins reduced the elevated oxidative stress and recovered the disrupted DNA repair mechanism in the autistic animals by decreasing the expressions of Gadd45a and Parp1 levels and enhancing the expressions of Ogg1, P53, and Xrcc1 genes. This indicates that proanthocyanidins have significant potential as a new therapeutic strategy for alleviating autistic features.

α-Synuclein aggregation decreases cortico-amygdala connectivity and impairs social behavior in mice

Abnormal accumulation of insoluble α-synuclein (α-Syn) inclusions in neurons, neurites, and glial cells is the defining neuropathology of synucleinopathies, including Parkinson's disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy. Accumulation of α-Syn inclusions in the amygdala has been well-documented in post-mortem studies of PD and DLB brains, as well as preclinical animal models of these conditions. Though α-Syn pathology is closely associated with neurodegeneration, there is a poor correlation between neuronal loss in the amygdala and the clinical features of PD and DLB. Moreover, functional interaction between the cerebral cortex and the amygdala is critical to regulating emotion, motivation, and social behaviors. The cortico-amygdala functional interaction is likely to be disrupted by the development of α-Syn pathology in the brain. Thus, we hypothesize that neuronal α-Syn inclusions disrupt cortical modulation of the amygdala circuits and are sufficient to drive social behavioral deficits. In the present work, we designed a series of longitudinal studies to rigorously measure the time courses of neurodegeneration, functional impairment of cortico-amygdala connectivity, and development of amygdala-dependent social behavioral deficits to test this hypothesis. We injected α-Syn preformed fibrils (PFFs) into the dorsal striatum to induce α-Syn aggregation in the amygdala and the medial prefrontal cortex (mPFC) of C57BL6 mice of both sexes, followed by a detailed analysis of temporal development of α-Syn pathology, synaptic deficits, and neuronal loss in the amygdala, as well as behavioral deficits at 3–12 months post injections. Development of α-Syn inclusions caused losses of cortical axon terminals and cell death in the basolateral amygdala (BLA) at 6- and 12-months post injections, respectively. At a relatively early stage of 3 months post injections, the connection strength of the mPFC-BLA synapse was decreased in PFFs-injection mice compared to controls. Meanwhile, the PFFs-injected mice showed impaired social interaction behavior, which was rescued by chemogenetic stimulation of mPFC-BLA connections. Altogether, we presented a series of evidence to delineate circuit events in the amygdala associated with the accumulation of α-Syn inclusions in the mouse brain, highlighting that functional impairment of the amygdala is sufficient to cause social behavior deficits. The present work further suggests that early circuit modulation could be an effective approach to alleviate symptoms associated with α-Syn pathology, necessitating studies of functional consequences of α-Syn aggregation.

Mild traumatic brain injury gives rise to chronic depression-like behavior and associated alterations in glutamatergic protein expression

Mild traumatic brain injury (mTBI) is known to result in chronic somatic, cognitive, and emotional symptoms. Depression is commonly reported among individuals suffering from persistent concussion symptoms; however, the underlying mechanisms are not understood. The glutamatergic system has recently been linked with mTBI and depression due to reports of similar changes in expression of glutamatergic proteins. Using a closed-head controlled cortical impact (cCCI) model in adult male rats (n = 8/group), this study investigated the emergence of self-care deficits and changes in social interaction behaviors at four, eight and twelve weeks post-injury. Western blotting was used to assess associated changes in expression of glutamate transporters and N-methyl-D-aspartate (NMDA) receptor subunits at twelve weeks. Splash test results revealed deficits in self-care behaviors beginning at eight weeks, which continued through twelve weeks in the injury group. Injured animals also exhibited decreased preference for social novelty at four weeks and loss of desire for social interaction as a whole by twelve weeks. GluN1 was increased in injured animals compared to shams in the frontal cortex and amygdala, while decreased GLT-1 was observed in the hippocampus. Linear regression was performed to evaluate relationships between behavioral and molecular variables; the results suggested that injury affects these relationships in a region-dependent manner. Together, these results suggest that the development of chronic depression-like behavior was associated with changes in glutamatergic protein expression. Deeper investigations into how injury influences glutamatergic synaptic protein expression are needed, as this has the potential to affect circuit-level neurotransmission that drives depression-like behavior following mTBI.

Transforming the future of nursing care: Artificial intelligence in pediatrics autism nursing care

The advent of artificial intelligence (AI) is revolutionizing various fields, including healthcare. AI's impact is increasingly evident in managing and caring for autistic pediatric patients [1]. The integration of AI into pediatrics autism nursing care is revolutionizing the approach to diagnosis, treatment, and ongoing management of children with autism spectrum disorder (ASD). Through their capacity to process and analyze vast amounts of data, AI technologies offer new possibilities for enhancing the precision, efficiency, and personalization of care for children with autism. ASD presents unique challenges that require specialized, often intensive, care strategies. According to Zhao et al., (2024), integrating AI into nursing care for children with autism offers promising opportunities to enhance diagnostics, personalize treatment plans, and improve overall patient outcomes [2]. This commentary explores how AI is transforming pediatric autism nursing care and the vital role nurses play in this evolving landscape. ASD is a developmental disorder characterized by challenges with social interaction, communication, and repetitive behaviors. Symptoms and their severity vary widely among individuals, making ASD a spectrum disorder. Research indicates that early diagnosis and intervention are crucial for improving outcomes, yet these can be difficult due to the complex and varied presentation of the disorder [3].

Assessing sociability using the Three-Chamber Social Interaction Test and the Reciprocal Interaction Test in a genetic mouse model of ASD.

Autism Spectrum Disorder (ASD) is a group of neurodevelopmental disorders with heterogeneous symptomatology. Arguably, the most pervasive shortfall of ASD are the deficits in sociability and the animal models of the disorder are expected to exhibit such impairments. The most widely utilized behavioral task for assessing sociability in rodents is the Three-Chamber Social Interaction Test (SIT). However, SIT has been yielding inconsistent results in social interaction behavior across different rodent models of ASD, which could be pointing to the suboptimal methodology of the task. Here, we compared social behavior assessed in SIT and in another prominent sociability behavioral assay, Reciprocal Interaction Test (RCI), in a SH3 and multiple ankyrin repeated domains 3 (SHANK3) mouse model of ASD. Head-to-head comparison showed no association (p = 0.15, 0.25, 0.43) and a fixed bias (p = 0.01, < 0.001, < 0.001) in sociability assessment between the behavioral assays in both wild-type (WT) controls and Shank3B(-/-) mice. Adult Shank3B(-/-) mice of both sexes displayed normative sociability in SIT when compared to the WT controls (p = 0.74) but exhibited less than half of social interaction (p < 0.001) and almost three times more social disinterest (p < 0.001) when compared to WT mice in RCI. At least in the Shank3B(-/-) mouse model of ASD, we presume RCI could be a preferable way of assessing social interaction compared to SIT. Considering the variability of animal models of ASD and the wide palette of tools available for the assessment of their behavior, a consensus approach would be needed for observational and interventional analyses.

Unveiling the role of IGF1R in autism spectrum disorder: a multi-omics approach to decipher common pathogenic mechanisms in the IGF signaling pathway.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition marked by impairments in social interaction, communication, and repetitive behaviors. Emerging evidence suggests that the insulin-like growth factor (IGF) signaling pathway plays a critical role in ASD pathogenesis; however, the precise pathogenic mechanisms remain elusive. This study utilizes multi-omics approaches to investigate the pathogenic mechanisms of ASD susceptibility genes within the IGF pathway. Whole-exome sequencing (WES) revealed a significant enrichment of rare variants in key IGF signaling components, particularly the IGF receptor 1 (IGF1R), in a cohort of Chinese Han individuals diagnosed with ASD, as well as in ASD patients from the SFARI SPARK WES database. Subsequent single-cell RNA sequencing (scRNA-seq) of cortical tissues from children with ASD demonstrated elevated expression of IGF receptors in parvalbumin (PV) interneurons, suggesting a substantial impact on their development. Notably, IGF1R appears to mediate the effects of IGF2R on these neurons. Additionally, transcriptomic analysis of brain organoids derived from ASD patients indicated a significant association between IGF1R and ASD. Protein-protein interaction (PPI) and gene regulatory network (GRN) analyses further identified ASD susceptibility genes that interact with and regulate IGF1R expression. In conclusion, IGF1R emerges as a central node within the IGF signaling pathway, representing a potential common pathogenic mechanism and therapeutic target for ASD. These findings highlight the need for further investigation into the modulation of this pathway as a strategy for ASD intervention.

Understanding Depression in Autism: The Role of Subjective Perception and Anterior Cingulate Cortex Volume.

The prevalence of depression is elevated in individuals with autism spectrum disorder (ASD) compared to the general population, yet the reasons for this disparity remain unclear. While social deficits central to ASD may contribute to depression, it is uncertain whether social interaction behavior themselves or individuals' introspection about their social behaviors are more impactful. Although the anterior cingulate cortex (ACC) and amygdala are frequently implicated in ASD, depression, and social functioning, it is unknown if these regions explain differences between ASD adults with and without co-occurring depression. The present study contrasted observed vs. subjective perception of autism symptoms and social performances assessed with both standardized measures and a lab task, in 65 sex-balanced (52.24% male) autistic young adults. We also quantified ACC and amygdala volume with 7-Tesla structural neuroimaging to examine correlations with depression and social functioning. We found that ASD individuals with depression exhibited differences in subjective evaluations including heightened self-awareness of ASD symptoms, lower subjective satisfaction with social relations, and less perceived affiliation during the social interaction task, yet no differences in corresponding observed measures, compared to those without depression. Larger ACC volume was related to depression, greater self-awareness of ASD symptoms, and worse subjective satisfaction with social interactions. In contrast, amygdala volume, despite its association with clinician-rated ASD symptoms, was not related to depression. Due to the cross-sectional nature of our study, we cannot determine the directionality of the observed relationships. Additionally, we included only individuals with an IQ over 60 to ensure participants could complete the social task, which excluded many on the autism spectrum. We also utilized self-reported depression indices instead of clinically diagnosed depression, which may limit the comprehensiveness of the findings. Our approach highlights the unique role of subjective perception of autism symptoms and social interactions, beyond the observable manifestation of social interaction in ASD, in contributing to depression, with the ACC playing a crucial role. These findings imply possible heterogeneity of ASD concerning co-occurring depression. Using neuroimaging, we were able to demarcate depressive phenotypes co-occurring alongside autistic phenotypes.

Autism-Related Cc2d1a Heterozygous Mice: Increased Levels of miRNAs Retained in DNA/RNA Hybrid Profiles (R-Loop).

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with a highly variable expression of phenotypes (restricted interest or activity and repetitive behavior in communication and social interactions), genes (mutation), markers (alteration of transcription) and pathways. Loss of function of the CC2D1A gene appears to primarily affect the brain, leading to a range of behavioral problems in humans. In our study published in 2020, we found that the expressions of miR-19a-3p, miR-361-5p, miR-150-5p, miR-3613-3p, miR-126-3p and miR-499a-5p were downregulated in the serum samples of autistic patients, their families and mouse models (Cc2d1a +/- and valproic acid treated males). Here, acquired non-Mendelian hereditary character in a genetically defined mouse model of autism (Cc2d1a +/-) correlates with the transcriptional alteration of five miRNAs. We seek to test the hypothesis that miRNA levels vary by changes in RNA/DNA structure during development, thereby creating transcription alteration and cell memory. Behavioral tests were conducted on the offspring of Cc2d1a (+/-) mutant and control mice, such as novel object, social interaction, marble burying and tail suspension behavior. Two RNA fractions were isolated from mouse hippocampal tissues and sperm cells via standard TRIzol extraction: free RNA and the fraction of RNA bound to DNA in the form of a DNA/RNA hybrid (R-loop). The expression levels of miR-19a-3p, miR-361-5p, miR-150-5p, miR-126-3p and miR-499a-5p were investigated by quantitative real-time RT-PCR. We report differences in the distribution of five miRNAs in the hippocampus between male and female mice, particularly in colonies of Cc2d1a (+/-) mice. Furthermore, the number of miRNAs engaged in the DNA/RNA hybrid fraction is generally higher in the mutant pedigree than in the control group. On the other hand, in sperm, both fractions are at lower levels than in controls. R-loops contribute to the physiology and pathology of organisms including human disease. Here, we report a variation in five miRNA levels between gender and tissue. Our results suggest that the transcription levels of these five miRNAs are directly regulated by their RNA.

EAV: EEG-Audio-Video Dataset for Emotion Recognition in Conversational Contexts

Understanding emotional states is pivotal for the development of next-generation human-machine interfaces. Human behaviors in social interactions have resulted in psycho-physiological processes influenced by perceptual inputs. Therefore, efforts to comprehend brain functions and human behavior could potentially catalyze the development of AI models with human-like attributes. In this study, we introduce a multimodal emotion dataset comprising data from 30-channel electroencephalography (EEG), audio, and video recordings from 42 participants. Each participant engaged in a cue-based conversation scenario, eliciting five distinct emotions: neutral, anger, happiness, sadness, and calmness. Throughout the experiment, each participant contributed 200 interactions, which encompassed both listening and speaking. This resulted in a cumulative total of 8,400 interactions across all participants. We evaluated the baseline performance of emotion recognition for each modality using established deep neural network (DNN) methods. The Emotion in EEG-Audio-Visual (EAV) dataset represents the first public dataset to incorporate three primary modalities for emotion recognition within a conversational context. We anticipate that this dataset will make significant contributions to the modeling of the human emotional process, encompassing both fundamental neuroscience and machine learning viewpoints.

Harmonizing Insights: LR-FFT Feature Extraction for Alzheimer’s and Autism Spectrum Disorder Detection in EEG Signals

Alzheimer’s Disease (AD) and Autism Spectrum Disorder (ASD) represent two distinct but equally impactful challenges in the field of neurology and cognitive health. AD is a degenerative neurological condition characterized by its progressive nature, typically affecting individuals in later stages of life. The hallmark features include cognitive impairment, mem- ory deterioration, and alterations in behavior. In contrast, ASD is a developmental disorder typically diagnosed in childhood, marked by difficulties in social interaction, communication, and repetitive behaviors. This paper explores the potential of the time-frequency feature extraction model known as the Left-Right Fast Fourier Transform (LR-FFT) in the context of these two disorders. While AD and ASD differ significantly in their onset, presentation, and demographic affected, both necessitate early and accurate diagnosis to enable timely intervention and tailored treatment strategies. Our research yields promising results, with classification accuracies reaching 88.26% for AD and 99.86% for ASD, demonstrating the LR-FFT’s potential to enhance diagnostic accuracy. By contributing to improved differentiation between these complex neurological conditions, this work aims to advance our understanding and management of AD and ASD, ultimately benefiting patients, their families, and healthcare practitioners.