Case Report: Retracing Atypical Development: A Preserved Speech Variant of Rett Syndrome

The subject of the present study is the development of a girl with the preserved speech variant of Rett disorder. Our data are based on detailed retrospective and prospective video analyses. Despite achieving developmental milestones, movement quality was already abnormal during the girl's first half year of life. In addition, early hand stereotypies, idiosyncratic vocalizations, asymmetric eye opening, and abnormal facial expressions are early signs proving that this variant of the Rett complex, too, manifests itself within the first months of life

Number word use in toddlerhood is associated with number recall performance at seven years of age

Previous studies have shown that verbal working memory and vocabulary acquisition are linked in early childhood. However, it is unclear whether acquisition of a narrow range of words during toddlerhood may be particularly related to recall of the same words later in life. Here we asked whether vocabulary acquisition of number words, location and quantifier terms over the first three years of life are associated with verbal and visuospatial working memory at seven years. Our results demonstrate that children who produced more number words between 20-26 months and started to produce the number words 1-10 earlier showed greater number recall at 7 years of age. This link was specific to numbers and neither extended to quantifier and location terms nor verbal and visuospatial working memory performance with other stimuli. These findings suggest a category-specific link between the mental lexicon of number words and working memory for numbers at an early age. © 2014 Libertus et al

Fidgety movements – tiny in appearance, but huge in impact

Objectives To describe fidgety movements (FMs), i.e., the spontaneous movement pattern that typically occurs at 3–5 months after term age, and discuss its clinical relevance. Sources A comprehensive literature search was performed using the following databases: MEDLINE/PubMed, CINAHL, The Cochrane Library, Science Direct, PsycINFO, and EMBASE. The search strategy included the MeSH terms and search strings (‘fidgety movement*’) OR [(‘general movement*’) AND (‘three month*’) OR (‘3 month*’)], as well as studies published on the General Movements Trust website (www.general-movements-trust.info). Summary of the data Virtually all infants develop normally if FMs are present and normal, even if their brain ultrasound findings and/or clinical histories indicate a disposition to later neurological deficits. Conversely, almost all infants who never develop FMs have a high risk for neurological deficits such as cerebral palsy, and for genetic disorders with a late onset. If FMs are normal but concurrent postural patterns are not age-adequate or the overall movement character is monotonous, cognitive and/or language skills at school age will be suboptimal. Abnormal FMs are unspecific and have a low predictive power, but occur exceedingly in infants later diagnosed with autism. Conclusions Abnormal, absent, or sporadic FMs indicate an increased risk for later neurological dysfunction, whereas normal FMs are highly predictive of normal development, especially if they co-occur with other smooth and fluent movements. Early recognition of neurological signs facilitates early intervention. It is important to re-assure parents of infants with clinical risk factors that the neurological outcome will be adequate if FMs develop normally

Does a detailed assessment of poor repertoire general movements help to identify those infants who will develop normally?

Background: The assessment of the quality of general movements (GMs) in young infants is a reliable and valid diagnostic tool for detecting brain dysfunction early in Life. Poor repertoire GMs are the most frequently observed abnormal GMs during the preterm, term and early postterm period. However, their predictive value for the neurological outcome is low. Aim: To find out whether a detailed scoring of poor repertoire GMs might lead to a better prediction of the neurological outcome. Subjects: We studied 18 preterm infants who were repeatedly videoed from birth to 22 weeks postterm age, including several recordings assessed as poor repertoire GMs. At 8 to 10 years, six children were neurologically normal, six had mild neurological abnormalities, and the remaining six were classified as cerebral palsy. Study design: Each GM globally assessed as poor repertoire was scored in details according to several aspects of neck and trunk, arm and Leg movements applying Prechtl's optimality concept. Results: By and large, the detailed score of poor repertoire GMs was not related to the neurological outcome. Conclusion: For the clinical application of the GM assessment, it remains important to assess the fidgety movements of those infants with poor repertoire GM trajectories in order to predict their outcome. (C) 2005 Elsevier Ireland Ltd. All rights reserved

Manual versus automated: The challenging routine of infant vocalisation segmentation in home videos to study neuro(mal)development

In recent years, voice activity detection has been a highly researched field, due to its importance as input stage in many real-world applications. Automated detection of vocalisations in the very first year of life is still a stepchild of this field. On our quest defining acoustic parameters in pre-linguistic vocalisations as markers for neuro(mal)development, we are confronted with the challenge of manually segmenting and annotating hours of variable quality home video material for sequences of infant voice/vocalisations. While in total our corpus comprises video footage of typically developing infants and infants with various neurodevelopmental disorders of more than a year running time, only a small proportion has been processed so far. This calls for automated assistance tools for detecting and/or segmenting infant utterances from real-live video recordings. In this paper, we investigated several approaches of infant voice detection and segmentation, including a rule-based voice activity detector, hidden Markov models with Gaussian mixture observation models, support vector machines, and random forests. Results indicate that the applied methods could be well applied in a semi-automated retrieval of infant utterances from highly non-standardised footage. At the same time, our results show that, a fully automated approach for this problem is yet to come