Pubmed du 13/07/15

Pubmed du jour

2015-07-13 12:03:50

1. {{Correction: Correction: A Reciprocal Model of Face Recognition and Autistic Traits: Evidence from an Individual Differences Perspective}}. {PLoS One};2015;10(7):e0133092.

[This corrects the article DOI: 10.1371/journal.pone.0094013.].

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2. Bailey DB, Jr., Wheeler A, Berry-Kravis E, Hagerman R, Tassone F, Powell CM, Roche M, Gane LW, Sideris J. {{Maternal Consequences of the Detection of Fragile X Carriers in Newborn Screening}}. {Pediatrics};2015 (Jul 13)
OBJECTIVES: The possibility of newborn screening for fragile X syndrome is complicated by the potential for identifying premutation carriers. Although knowing the child’s carrier status has potential benefits, the possibility of late-onset disorders in carrier children and their parents raises concerns about whether such information would be distressing to parents and potentially more harmful than helpful. This study sought to answer this question by offering voluntary fragile X screening to new parents and returning results for both the full mutation and premutation FMR1 gene expansions. We tested the assumption that such information could lead to adverse mental health outcomes or decision regret. We also wanted to know if child age and spousal support were associated with the outcomes of interest. METHODS: Eighteen mothers of screen-positive infants with the premutation and 15 comparison mothers completed a battery of assessments of maternal anxiety, postpartum depression, stress, family quality of life, decision regret, and spousal support. The study was longitudinal, with an average of 3 assessments per mother. RESULTS: The premutation group was not statistically different from the comparison group on measures of anxiety, depression, stress, or quality of life. A subset of mothers experienced clinically significant anxiety and decision regret, but factors associated with these outcomes could not be identified. Greater spousal support was generally associated with more positive outcomes. CONCLUSIONS: Although we did not find evidence of significant adverse events, disclosure of newborn carrier status remains an important consideration in newborn screening policy.

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3. Rosenberg A, Patterson JS, Angelaki DE. {{A computational perspective on autism}}. {Proc Natl Acad Sci U S A};2015 (Jul 13)
Autism is a neurodevelopmental disorder that manifests as a heterogeneous set of social, cognitive, motor, and perceptual symptoms. This system-wide pervasiveness suggests that, rather than narrowly impacting individual systems such as affection or vision, autism may broadly alter neural computation. Here, we propose that alterations in nonlinear, canonical computations occurring throughout the brain may underlie the behavioral characteristics of autism. One such computation, called divisive normalization, balances a neuron’s net excitation with inhibition reflecting the overall activity of the neuronal population. Through neural network simulations, we investigate how alterations in divisive normalization may give rise to autism symptomatology. Our findings show that a reduction in the amount of inhibition that occurs through divisive normalization can account for perceptual consequences of autism, consistent with the hypothesis of an increased ratio of neural excitation to inhibition (E/I) in the disorder. These results thus establish a bridge between an E/I imbalance and behavioral data on autism that is currently absent. Interestingly, our findings implicate the context-dependent, neuronal milieu as a key factor in autism symptomatology, with autism reflecting a less « social » neuronal population. Through a broader discussion of perceptual data, we further examine how altered divisive normalization may contribute to a wide array of the disorder’s behavioral consequences. These analyses show how a computational framework can provide insights into the neural basis of autism and facilitate the generation of falsifiable hypotheses. A computational perspective on autism may help resolve debates within the field and aid in identifying physiological pathways to target in the treatment of the disorder.

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