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*مغز بزرگسالان مبتلا به آوتیسم عملکرد متفاوتی دریادگیری ضمنی دارد 

 

منبع:  Carnegie Mellon University

ترجمه و تلخیص: دکتر مهدی پورمحمد – پژوهشکده علوم شناختی

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پژوهش جدید تصویربرداری تفاوت های اساسی را در مغز بزرگسالان مبتلا به اوتیسم ASD در یادگیری شناسایی کردند. این پژوهش که در مجله NeuroImage به چاپ رسیده نشان می دهد که مغز افراد مبتلا به اوتیسم  (autism spectrum disorder (ASD) ) چگونه درطول فرایند یادگیری ضمنی به تدریج با الگوهای دیداری مطابقت پیدامی کند. یادگیری ضمنی به یادگیری بدون  اطلاع و بدون آگاهی  از این که نوعی یادگیری درحال انجام است  اطلاق می شود. محققین دانشگاه Carnegie Mellon با استفاده از تکنیک تصویربرداری fMRI  دریافتند که فعالیت مغز افراد ASD هنگام آشنا شدن با الگوهایی که به صورت تکراری می بینند کندتر است. این یافته بدین معناست که مغز آنها نمی تواند همچون گروه های کنترل در این تحقیق قدیمی بودن (oldness) الگوها ی دیداری را ثبت کند.

سطح فعالیت مغزی گروههای کنترل در این تحقیق هنگام مواجهه شدن با الگوهایی که قبلاً یادگرفته شده بودند کاهش می یافت اما کاهش سطح فعالیت مغزی در بیماران ASD به طرز قابل ملاحظه ای  کمتر بود.

این یافته ها همچنین  نشان می دهد که شدت نشانه های اوتیسم افراد با میزان انطباق مغز افراد با الگوهایی که قبلاً فراگرفته شده است همبستگی دارد. این یافته شاید توضیحی براین مساله باشد که چرا بیماران مبتلا به اوتیسم ASD مشکلاتی در  شرایط یادگیری های ضمنی از جمله تفسیر قیافه های صورت دارند.

پرفسور مارسل جاست ( Marcel Just) از کالج Deitrich می گوید : این یافته همچنین می تواند جوابی برای این مساله باشد که چرا در افراد مبتلا به اوتیسم ASD درصورتی که یادگیری سرنخ های ضمنی اجتماعی آنها تغییرنماید مشکلاتی در تعامالات روزمره ی اجتماعی خواهند داشت.

جهت اطلاعات بیشتر دراین زمینه می توانید به لینک زیر مراجعه نمایید :

 

http://psychcentral.com/news/2015/11/20/brains-of-adults-with-autism-adapt-differently-in-implicit-learning/95108.html

 

Brains of Adults with Autism Adapt Differently in Implicit Learning

By Traci Pedersen

~ 2 min read

20 November 2015

 

A new imaging study has discovered a crucial difference in the way learning occurs in the brains of adults with autism spectrum disorder (ASD). The study, published in the journal NeuroImage, examined how the brains of typical and ASD individuals gradually become adapted to visual patterns during implicit learning (learning without being aware that one is learning).

Using functional magnetic resonance (fMRI) imaging, the researchers from Carnegie Mellon University found that the brain activation of ASD individuals was slower to become familiar with the pattern they repeatedly saw — meaning their brains failed to register the “oldness” of the patterns to the same degree as the control group.

 

With repeated exposures to the patterns being learned, the brains of the control participants kept decreasing their level of activation, essentially showing adaptation to the pattern. The decreases in the brain of participants with ASD, however, were significantly smaller.

The findings also showed that the severity of a person’s autism symptoms correlated with the brain’s degree of adaptation to the patterns. This may offer insight into why many real-world implicit learning situations, such as learning to interpret facial expressions, tend to pose challenges for those with ASD.

“This finding provides a tentative explanation for why people with ASD might have difficulty with everyday social interactions, if their learning of implicit social cues has been altered,” said Marcel Just, the D.O. Hebb University Professor of Psychology in the Dietrich College of Humanities and Social Sciences.

For the study, 16 high-functioning adults with ASD and 16 typical adults were trained to perform an implicit dot pattern-learning task while having their brains scanned. The target pattern was a random array of dots, which can gradually become familiar over multiple exposures despite minor changes in the pattern.

Before receiving the brain scan, both groups were familiarized with the type of task that would be used in the scanner. The ASD participants took longer than the control group to learn the task, demonstrating altered implicit learning.

The imaging shows that at the beginning of the learning session, both groups’ brain activation levels were similar. By the end of the task, the control group showed decreased activation in the posterior regions. The ASD participants’ brain activation did not decrease later in learning. In fact, it increased in frontal and parietal regions.

 

“Behaviorally, the two groups looked very similar throughout the task — both the ASD and typical participants were able to learn how to correctly categorize the dot patterns with reasonable accuracy,” Just said.

“But, because their activation levels differed, it tells us that there may be something qualitatively different in the way individuals with ASD learn and perform these kinds of task and reveals insights into the disorder that are not discernable from behavior alone.”

A second finding involved brain synchronization — a measure of how well coordinated the brain activation was across different areas of the brain. The implicit learning task was specifically designed to engage both the frontal and posterior regions of the brain, and the results showed that brain synchronization between these regions was lower in individuals with ASD.

“This lack of synchronization with frontal regions in ASD — an impairment in brain connectivity — may lead to symptoms of the disorder that involve processes that require brain coordination between frontal and other areas, such as language processing and social interaction,” Just explained.

The findings also showed that adaptation and synchronization were directly related to the severity of the participants’ ASD symptoms.

“Seeing that individuals with more atypical neural responses also had more severe ASD symptoms suggests that these neural characteristics underlie or contribute to the core symptoms of ASD,” Just said.

“It is possible that reduced neural adaptability during learning in ASD may lead to the behavioral symptoms of the disorder. For example, the ability to learn implicit social clues may be affected in ASD, leading to impaired social processing.”

Source: Carnegie Mellon University

 
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