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نتیجه جستجو - اوتیسم

تعداد مقالات یافته شده: 33
ردیف عنوان نوع
11 Autistic traits, personality, and evaluations of humanoid robots by young and older adults
ویژگی های اوتیستیک ، شخصیت و ارزیابی ربات های انسان دوستانه توسط افراد جوان و بزرگتر-2020
While research with individuals on the autistic spectrum has increased strongly, there is still a lack of research on autism/autistic traits in older adults. Children with autism have been proposed to benefit from interactions with social robots; for older adults, the potential role of robotics is currently being discussed. We combined these topics by assessing both young and older (Mean age ¼ 22 vs. 69 years) neurotypical adults’ evaluations of various humanoid robots presented in video clips, on multiple dimensions (likeability, companionship, dominance, threat, human-likeness). We additionally assessed autistic traits (Autism Spectrum Questionnaire – AQ) and Big- Five personality traits. Remarkably, older adults evaluated robots as more likeable. Compared to young adults, older adults also showed significantly higher levels of autistic traits (particularly in the AQ social interaction subscale), higher levels of conscientiousness, and lower levels of openness. We found strong positive correlations between ratings of likeability and human-likeness of robots across groups, and particularly in participants with high levels of autistic trait. Across robots, data also provided evidence for the uncanny valley phenomenon. Favourable evaluations of robots by older adults suggest potential for older adults on the autistic spectrum to benefit from social robots.
Keywords: Humanoid robots | Old adults | Autistic traits | Personality | Visual appearance
مقاله انگلیسی
12 Enhancement of behavioral and linguistic outcome measures in autism spectrum disorder through neuro-navigated transcranial magnetic stimulation: A pilot study
افزایش اقدامات نتیجه گیری رفتاری و زبانی در اختلال طیف اوتیسم از طریق تحریک مغناطیسی transcranial هدایت عصبی: یک مطالعه مقدماتی-2020
Autism spectrum disorder (ASD) encompasses a wide range of impairments in reciprocal social and communicative skills, as well as the presence of restrictive and/or repetitive patterns of behavior [1]. These lifelong impairments often introduce significant functional, financial, and health challenges [2]. While the environmental, genetic, and biological etiologies of ASD are not well understood [3], intense public and scientific interest in the disorder has bolstered a search for effective pharmacological and behavioral interventions [4], as well as the use of non-invasive brain stimulation via methods such as transcranial magnetic stimulation (TMS) [5]. This last approach has generated hope in the clinical community as a means of directly modulating cortical regions thought to underly behavioral function.
مقاله انگلیسی
13 Abnormal reinforcement learning in a mice model of autism induced by prenatal exposure to valproic acid
یادگیری تقویتی غیر طبیعی در یک مدل موش اوتیسمی ناشی از قرار گرفتن در معرض بارداری به اسید والپروئیک-2020
Individuals with autism spectrum disorder (ASD) display dysfunction in learning from environmental stimulus that have positive or negative emotional values, posing obstacles to their everyday life. Unfortunately, mechanisms of the dysfunction are still unclear. Although early intervention for ASD victims based on reinforcement learning are commonly used, the mechanisms and characteristics of the improvement are also unknown. By using a mice model of ASD produced by prenatal exposure to valproic acid (VPA), the present work discovered a delayed response-reinforcer forming, and an impaired habit forming in a negative reinforcement learning paradigm in VPA exposure male offspring. But the extinction of the learned skills was found to become faster than normal male animals. Since escape action of nosepoking and the motility remain unchanged in the VPA male offspring, the impaired learning and the accelerated extinction are caused by deficits in higher brain functions underlying association between the animals’ behavioral responses and the outcomes of such responses. The results further suggest that the rodent ASD model produced by prenatal exposure to VPA reproduces the deficits in reasoning or building the contingency between one’s own behaviors and the consequent outcomes of the behavior seen in ASD patients.
Keywords: Autism spectrum disorder | Reinforcement learning | Valproic acid
مقاله انگلیسی
14 Distinct Pathogenic Genes Causing Intellectual Disability and Autism Exhibit a Common Neuronal Network Hyperactivity Phenotype
ژنهای پاتوژن مشخص متمایز کننده ناتوانی ذهنی و اوتیسم از فنوتیپ بیش فعالی شبکه عصبی مشترک-2020
Pathogenic mutations in either one of the epigenetic modifiers EHMT1, MBD5, MLL3, or SMARCB1 have been identified to be causative for Kleefstra syndrome spectrum (KSS), a neurodevelopmental disorder with clinical features of both intellectual disability (ID) and autism spectrum disorder (ASD). To understand how these variants lead to the phenotypic convergence in KSS, we employ a loss-of-function approach to assess neuronal network development at the molecular, single-cell, and network activity level. KSS-gene-deficient neuronal networks all develop into hyperactive networks with altered network organization and excitatory-inhibitory balance. Interestingly, even though transcriptional data reveal distinct regulatory mechanisms, KSS target genes share similar functions in regulating neuronal excitability and synaptic function, several of which are associated with ID and ASD. Our results show that KSS genes mainly converge at the level of neuronal network communication, providing insights into the pathophysiology of KSS and phenotypically congruent disorders.
مقاله انگلیسی
15 عملکرد اجرایی، مهارت های تطبیقی، مشخصات عاطفی و رفتاری: مقایسه بین اختلال طیف اوتیسم و فنیل کتونوری
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 26
نظریه های تأثیرگذار پذیرفته اند که برخی از علائم اصلی اختلال طیف اوتیسم (ASD) ممکن است ناشی از کسری در عملکردهای اجرایی (EF) باشد. نقص EF همچنین یک علامت عصبی در افراد تحت درمان اولیه با فنیل کتونوری (PKU) محسوب می شود. اهداف این مطالعه: بررسی صحت وقایع و الگوهای اختلالات خاص EF در هر دو گروه بالینی بود تا همزیستی تغییرات EF با مشکلات سازگاری، رفتاری و عاطفی در هر شرایط بالینی را بررسی کند.
مواد و روش ها: ما EF ، مشخصات سازگار، رفتاری و عاطفی را در 21 شرکت کننده با ASD ارزیابی کردیم، 15 فرد مبتلا به PKU زودرس درمان شده، قابل مقایسه با سن و ضریب هوشی و 14 نفر از گروه کنترل، از نظر سن با گروههای بالینی قابل مقایسه هستند (دامنه سنی: 7 تا 14 سال).
یافته ها: شرکت کنندگان ASD و PKU دو مورد متفاوت ارائه دادند، اما الگوهای اختلال EF با هم همپوشانی دارند. در حالی که شرکت کنندگان در ASD فقط در انعطاف پذیری شناختی کسری خاص را نشان دادند، افراد PKU دارای اختلال گسترده تر در EF با عملکرد ضعیف تر در دو حوزه EF هسته ای (مهار، انعطاف پذیری شناختی) نسبت به گروه کنترل سالم بودند. مشخصات روانشناختی و سازگاری در شرکت کنندگان PKU معمولی بود، در حالی که شرکت کنندگان در ASD رفتاری (علائم بیرونی)، عاطفی (علائم درونی سازی) و اختلالات سازگاری (حوزه های عمومی، عملی، اجتماعی) را تجربه کردند.
نتیجه گیری: نتایج حاضر از نمایشی برای تفکیک نسبی مشخصات تطبیقی و عاطفی- رفتاری با توجه به مهارت های EF پشتیبانی می کند و نشان می دهد که اختلالات دیگر به فنوتیپ چند بعدی شرکت کنندگان در ASD کمک می کند.
کلید واژه ها: اختلال طیف اوتیسم | فنیل کتونوری | عملکرد اجرایی | رفتار سازشی | درونی و بیرونی کردن علائم
مقاله ترجمه شده
16 Identification and analysis of behavioral phenotypes in autism spectrum disorder via unsupervised machine learning
شناسایی و تجزیه و تحلیل فنوتیپ های رفتاری در اختلال طیف اوتیسم از طریق یادگیری ماشین بدون نظارت-2019
Background and objective: Autism spectrum disorder (ASD) is a heterogeneous disorder. Research has explored potential ASD subgroups with preliminary evidence supporting the existence of behaviorally and genetically distinct subgroups; however, research has yet to leverage machine learning to identify phenotypes on a scale large enough to robustly examine treatment response across such subgroups. The purpose of the present study was to apply Gaussian Mixture Models and Hierarchical Clustering to identify behavioral phenotypes of ASD and examine treatment response across the learned phenotypes. Materials and methods: The present study included a sample of children with ASD (N = 2400), the largest of its kind to date. Unsupervised machine learning was applied to model ASD subgroups as well as their taxonomic relationships. Retrospective treatment data were available for a portion of the sample (n =1034). Treatment response was examined within each subgroup via regression. Results: The application of a Gaussian Mixture Model revealed 16 subgroups. Further examination of the subgroups through Hierarchical Agglomerative Clustering suggested 2 overlying behavioral phenotypes with unique deficit profiles each composed of subgroups that differed in severity of those deficits. Furthermore, differentiated response to treatment was found across subtypes, with a substantially higher amount of variance accounted for due to the homogenization effect of the clustering. Discussion: The high amount of variance explained by the regression models indicates that clustering provides a basis for homogenization, and thus an opportunity to tailor treatment based on cluster memberships. These findings have significant implications on prognosis and targeted treatment of ASD, and pave the way for personalized intervention based on unsupervised machine learning.
Keywords: Machine learning | Autism spectrum disorder | Behavioral phenotypes | Cluster analysis | Treatment response
مقاله انگلیسی
17 From pattern classification to stratification: towards conceptualizing the heterogeneity of Autism Spectrum Disorder
از طبقه بندی الگو تا چینه بندی: به سمت مفهوم سازی ناهمگونی اختلال طیف اوتیسم-2019
Pattern classification and stratification approaches have increasingly been used in research on Autism Spectrum Disorder (ASD) over the last ten years with the goal of translation towards clinical applicability. Here, we present an extensive scoping literature review on those two approaches. We screened a total of 635 studies, of which 57 pattern classification and 19 stratification studies were included. We observed large variance across pattern classification studies in terms of predictive performance from about 60% to 98% accuracy, which is among other factors likely linked to sampling bias, different validation procedures across studies, the heterogeneity of ASD and differences in data quality. Stratification studies were less prevalent with only two studies reporting replications and just a few showing external validation. While some identified strata based on cognition and intelligence reappear across studies, biology as a stratification marker is clearly underexplored. In summary, mapping biological differences at the level of the individual with ASD is a major challenge for the field now. Conceptualizing those mappings and individual trajectories that lead to the diagnosis of ASD, will become a major challenge in the near future.
Keywords: Autism spectrum disorder | Machine learning | Pattern recognition | Classification | Clustering | Stratification | Biotypes | Precision medicine
مقاله انگلیسی
18 Heritable genotype contrast mining reveals novel gene associations specific to autism subgroups
معادله کنتراست ژنتیکی انتزاعی نشان می دهد که ژن های جدید ژن خاص برای زیرگروه های اوتیسم هستند-2018
Though the genetic etiology of autism is complex, our understanding can be improved by identifying genes and gene-gene interactions that contribute to the development of specific autism subtypes. Identifying such gene groupings will allow individuals to be diagnosed and treated according to their precise characteristics. To this end, we developed a method to associate gene combinations with groups with shared autism traits, targeting genetic elements that distinguish patient populations with opposing phenotypes. Our computational method prioritizes genetic variants for genome-wide association, then utilizes Frequent Pattern Mining to highlight potential interactions between variants. We introduce a novel genotype assessment metric, the Unique Inherited Combination support, which accounts for inheritance patterns observed in the nuclear family while estimating the impact of genetic variation on phenotype manifestation at the individual level. High-contrast variant combinations are tested for significant subgroup associations. We apply this method by contrasting autism subgroups defined by severe or mild manifestations of a phenotype. Significant associations connected 286 genes to the subgroups, including 193 novel autism candidates. 71 pairs of genes have joint associations with sub groups, presenting opportunities to investigate interacting functions. This study analyzed 12 autism subgroups, but our informatics method can explore other meaningful divisions of autism patients, and can further be applied to reveal precise genetic associations within other phenotypically heterogeneous disorders, such as Alzheimer’s disease.
Keywords: Data mining ، Autistic disorder ، Genetics ، Frequent pattern mining
مقاله انگلیسی
19 General and specific factors in the processing of faces
عوامل عمومی و خاص در پردازش چهره-2017
The ability to recognize faces varies considerably between individuals, but does performance co-vary for tests of different aspects of face processing? For 397 participants (of whom the majority were university students) we obtained scores on the Mooney Face Test, Glasgow Face Matching Test (GFMT), Cambridge Face Memory Test (CFMT) and Composite Face Test. Overall performance was significantly correlated for each pair of tests, and we suggest the term f for the factor underlying this pattern of positive correlations. However, there were large variations in the amount of variance shared by individual tests: The GFMT and CFMT are strongly related, whereas the GFMT and the Mooney test tap largely independent abilities. We do not replicate a frequently reported relationship between holistic processing (from the Composite test) and face recognition (from the CFMT)—indeed, holistic processing does not correlate with any of our tests. We report associations of performance with digit ratio and autism-spectrum quotient (AQ), and from our genome-wide association study we include a list of suggestive genetic associations with perfor mance on the four face tests, as well as with f.
Keywords: Face perception | Face recognition | f | Holistic processing | Individual differences | Autism-spectrum quotient (AQ) | Genome-wide association study (GWAS)
مقاله انگلیسی
20 Tourism and autism: Journeys of mixed emotions
گردشگری و اوتیسم: سفرهای ترکیبی از احساسات-2017
There is an evolving tourism literature around psychological wellbeing, social exclusion and disability. This paper advances tourism knowledge into the terrain of psychological health and developmental complexities, and psychological distress. It draws on a phe nomenological position to understand the lived experiences of mothers of children with developmental difficulties, in this case diagnosed with autism spectrum disorder (ASD). It discusses the emotional and everyday challenges of caring for a child diagnosed with ASD on holiday, discusses the perceived benefits holidays offer and outlines care-giving strategies adopted by mothers to manage their children’s tourism experiences. The paper discusses the uniqueness of the context of autism and problematizes popular discourses, which predominantly frame tourism as pleasurable settings of escape, stimulation, novelty and relaxation.
Keywords: Disability | Care-giving | Mothers | Children | Well-being | Mental health
مقاله انگلیسی
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