Pubmed du 26/12/20
1. Kurz EM, Conzelmann A, Barth GM, Renner TJ, Zinke K, Born J. How Do Children with Autism Spectrum Disorder Form Gist Memory During Sleep ? – A Study of Slow Oscillation-Spindle Coupling. Sleep ;2020 (Dec 26)
Sleep is assumed to support memory through an active systems consolidation process that does not only strengthen newly encoded representations but also facilitates the formation of more abstract gist memories. Studies in humans and rodents indicate a key role of the precise temporal coupling of sleep slow oscillations (SO) and spindles in this process. The present study aimed at bolstering these findings in typically developing (TD) children, and at dissecting particularities in SO-spindle coupling underlying signs of enhanced gist memory formation during sleep found in a foregoing study in children with autism spectrum disorder (ASD) without intellectual impairment. Sleep data from 19 boys with ASD and 20 TD boys (9-12 years) were analyzed. Children performed a picture-recognition task and the Deese-Roediger-McDermott (DRM) task before nocturnal sleep (encoding) and in the next morning (retrieval). Sleep-dependent benefits for visual-recognition memory were comparable between groups but were greater for gist abstraction (recall of DRM critical lure words) in ASD than TD children. Both groups showed a closely comparable SO-spindle coupling, with fast spindle activity nesting in SO-upstates, suggesting that a key mechanism of memory processing during sleep is fully functioning already at childhood. Picture-recognition at retrieval after sleep was positively correlated to frontocortical SO-fast-spindle coupling in TD children, and less in ASD children. Critical lure recall did not correlate with SO-spindle coupling in TD children but showed a negative correlation (r=-.64, p=.003) with parietal SO-fast-spindle coupling in ASD children, suggesting other mechanisms specifically conveying gist abstraction, that may even compete with SO-spindle coupling.
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2. Li Y, Koldenhoven RM, Liu T, Venuti CE. Age-related gait development in children with autism spectrum disorder. Gait Posture ;2020 (Dec 26) ;84:260-266.
BACKGROUND : A better understanding of gait development and asymmetries in children with autism spectrum disorder (ASD) may improve the development of treatment programs and thus, patient outcomes. RESEARCH QUESTION : Does age affect walking kinematics and symmetry in children with ASD ? METHOD : Twenty-nine children (aged 6-14 years old) with mild ASD (level one) were recruited and assigned to one of the three groups based on their ages : 6-8 years (U8), 9-11 years (U11) and 12-14 years (U14). Walking kinematics were captured using an inertia measurement unit system placed bilaterally on participants’ foot, lower leg, upper leg, upper arm, pelvis, and thoracic spine. Joint angles were computed and compared among the age groups. Symmetry angles were used to assess the gait symmetry and were compared among the age groups. RESULTS : Older children exhibited less ankle dorsiflexion and knee flexion angles at heel-strike and greater plantarflexion angles at toe-off compared with younger children. In addition, a decreased pelvis and thorax axial rotation range of motion and increased shoulder flexion/extension range of motion were observed for older children. However, no age-related difference in gait symmetry was observed. SIGNIFICANCE : These findings could suggest that older children with ASD may develop gait kinematics to a more energy-efficient walking pattern.
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3. Maruo Y, Egawa K, Tonoki H, Terae S, Ueda Y, Shiraishi H. Selective Eating in Autism Spectrum Disorder Leading to Kwashiorkor and Brain Edema. Pediatr Neurol ;2020 (Dec 26) ;116:55-56.
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4. Park HJ, Choi SJ, Kim Y, Cho MS, Kim YR, Oh JE. Mealtime Behaviors and Food Preferences of Students with Autism Spectrum Disorder. Foods ;2020 (Dec 26) ;10(1)
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by a lack of social communication and restrictive, repetitive behaviors or interests. This study aimed to examine the mealtime behaviors and food preferences of students with ASD. An online questionnaire on mealtime behavior and food preferences of ASD students was conducted by caregivers including parents, and the average age of ASD students was 14.1 ± 6.1. The analysis of mealtime behavior resulted in classification into three clusters : cluster 1, the « low-level problematic mealtime behavior group » ; cluster 2, the « mid-level problematic mealtime behavior group » ; and cluster 3, the « high-level problematic mealtime behavior group ». Cluster 1 included older students than other clusters and their own specific dietary rituals. Meanwhile, cluster 3 included younger students than other clusters, high-level problematic mealtime behavior, and a low preference for food. In particular, there were significant differences in age and food preference for each subdivided ASD group according to their eating behaviors. Therefore, the content and method of nutrition education for ASD students’ needs a detailed approach according to the characteristics of each group.
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5. Pehlivanidis A, Papanikolaou K, Korobili K, Kalantzi E, Mantas V, Pappa D, Papageorgiou C. Trait-Based Dimensions Discriminating Adults with Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD) and, Co-occurring ADHD/ASD. Brain Sci ;2020 (Dec 26) ;11(1)
This study assessed the co-occurrence of attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) in newly diagnosed adults of normal intelligence and the contribution of trait-based dimensions deriving from the Barkley Adult ADHD Rating Scale-IV (BAARS-IV), the Autism-Spectrum Quotient (AQ), and the Empathy Quotient (EQ) to the differentiation of patients with ADHD, ASD, and ADHD/ASD. A total of 16.1% of patients with ADHD received a co-occurring ASD diagnosis, while 33.3% of patients with ASD received an ADHD diagnosis. Subjects with ADHD or ADHD/ASD had higher scores in all ADHD traits compared to ASD subjects. Compared to the ADHD group, the ASD group had AQ scores that were significantly greater, except for attention to detail. ADHD/ASD co-occurrence significantly increased the score of attention to detail. The total EQ score was greater in the ADHD group. In the stepwise logistic regression analyses, past hyperactivity, current inattention and impulsivity, attention switching, communication, imagination, and total EQ score discriminated ADHD patients from ASD patients. Attention to detail, imagination, and total EQ score discriminated ADHD cases from ADHD/ASD cases, while past hyperactivity and current impulsivity discriminated ASD subjects from ADHD/ASD subjects. Our findings highlight the importance of particular trait-based dimensions when discriminating adults with ADHD, ASD, and co-occurring ADHD/ASD.
