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Query: UMLS:C0004352 (autism)
 32,579 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Neurodevelopmental disorders, including autism spectrum disorder, have been intensively investigated at the neural, cognitive, and behavioral levels, but the accumulated knowledge remains fragmented. In particular, developmental learning aspects of symptoms and interactions with the physical environment remain largely unexplored in computational modeling studies, although a leading computational theory has posited associations between psychiatric symptoms and an unusual estimation of information uncertainty (precision), which is an essential aspect of the real world and is estimated through learning processes. Here, we propose a mechanistic explanation that unifies the disparate observations via a hierarchical predictive coding and developmental learning framework, which is demonstrated in experiments using a neural network-controlled robot. The results show that, through the developmental learning process, homogeneous intrinsic neuronal excitability at the neural level induced via self-organization changes at the information processing level, such as hyper sensory precision and overfitting to sensory noise. These changes led to multifaceted alterations at the behavioral level, such as inflexibility, reduced generalization, and motor clumsiness. In addition, these behavioral alterations were accompanied by fluctuating neural activity and excessive development of synaptic connections. These findings might bridge various levels of understandings in autism spectrum and other neurodevelopmental disorders and provide insights into the disease processes underlying observed behaviors and brain activities in individual patients. This study shows the potential of neurorobotics frameworks for modeling how psychiatric disorders arise from dynamic interactions among the brain, body, and uncertain environments.
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PMID:Homogeneous Intrinsic Neuronal Excitability Induces Overfitting to Sensory Noise: A Robot Model of Neurodevelopmental Disorder. 3290 28

Potocki-Lupski syndrome is a condition mainly characterized by infantile hypotonia, developmental delay/intellectual disability (DD/ID), and congenital anomalies, caused by duplications of the 17p11.2 region, encompassing RAI1 gene. Its clinical presentation is extremely variable, especially for what concerns the cognitive level and the behavioral phenotype. Such aspects, as well as the dysmorphic/malformative ones, have been covered by previous studies; otherwise neurological features have never been systematically described. In order to delineate the neurological phenotype of Potocki-Lupski Syndrome, we collect an 8-patients cohort. Developmental milestones are delayed and a mild to moderate cognitive impairment is present in all patients, variably associated with features of autism spectrum disorder, behavioral disturb, and sleep disturb. Hypotonia appears a less frequent finding than what previously reported, while motor clumsiness/coordination impairment is frequent. EGG registration demonstrated a common pattern with excess of diffuse rhythmic activity in sleep phases or while the patient is falling asleep. Brain MRI did not reveal common anomalies, although unspecific white matter changes may be present. We discuss such findings and compare them to literature data, offering an overview on the neurological and cognitive-behavioral presentation of the syndrome.
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PMID:Neurological phenotype of Potocki-Lupski syndrome. 3304 31


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