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In a longitudinal population-based study of 2,905 children, we investigated if infants' neuromotor development was associated with autistic traits in childhood. Overall motor development and muscle tone were examined by trained research assistants with an adapted version of Touwen's Neurodevelopmental Examination between ages 2 and 5 months. Tone was assessed in several positions and items were scored as normal, low, or high tone. Parents rated their children's autistic traits with the Social Responsiveness Scale (SRS) and the Pervasive Developmental Problems (PDP) subscale of the Child Behavior Checklist at 6 years. We defined clinical PDP if scores were >98th percentile of the norm population. Diagnosis of autism spectrum disorder (ASD) was clinically confirmed in 30 children. We observed a modest association between overall neuromotor development in infants and autistic traits. Low muscle tone in infancy predicted autistic traits measured by SRS (adjusted beta=0.05, 95% CI for B: 0.00-0.02, P=0.01), and PDP (adjusted beta=0.08, 95% CI for B: 0.04-0.10, P<0.001). Similar results emerged for the association of low muscle tone and clinical PDP (adjusted OR=1.36, 95% CI: 1.08-1.72, P=0.01) at age 6 years. Results remained unchanged if adjusted for child intelligence. There was no association between high muscle tone and SRS or PDP. Exclusion of children with ASD diagnosis did not change the association. This large study showed a prospective association of infant muscle tone with autistic traits in childhood. Our findings suggest that early detection of low muscle tone might be a gateway to improve early diagnosis of ASD.

Objective: Using parent-completed questionnaires in (preventive) child health care can facilitate the early detection of psychosocial problems and psychopathology, including autism spectrum disorders (ASD). A promising questionnaire for this purpose is the Brief Infant-Toddler Social and Emotional Assessment (BITSEA). The screening accuracy with regard to ASD of the BITSEA Problem and Competence scales and a newly calculated Autism score were evaluated. Method: Data, that was collected between April 2010 and April 2011, from a community sample of 2-year-olds (N = 3127), was combined with a sample of preschool children diagnosed with ASD (N = 159). For the total population and for subgroups by child's gender, area under the Receiver Operating Characteristic (ROC) curve was examined, and across a range of BITSEA Problem, Competence and Autism scores, sensitivity, specificity, positive and negative likelihood ratio's, diagnostic odds ratio and Youden's index were reported. Results: The area under the ROC curve (95% confidence interval, [95%CI]) of the Problem scale was 0.90(0.87-0.92), of the Competence scale 0.93(0.91-0.95), and of the Autism score 0.95(0.93-0.97). For the total population, the screening accuracy of the Autism score was significantly better, compared to the Problem scale. The screening accuracy of the Competence scale was significantly better for girls (AUC = 0.97; 95%CI = 0.95-0.98) than for boys (AUC = 0.91; 95%CI = 0.88-0.94). Conclusion: The results indicate that the BITSEA scales and newly calculated Autism score have good discriminative power to differentiate children with and without ASD. Therefore, the BITSEA may be helpful in the early detection of ASD, which could have beneficial effects on the child's development.

Background: Maternal depression and anxiety during pregnancy have been associated with offspring-attention deficit problems. Aim: We explored possible intrauterine effects by comparing maternal and paternal symptoms during pregnancy, by investigating cross-cohort consistency, and by investigating whether parental symptoms in early childhood may explain any observed intrauterine effect. Methods: This study was conducted in two cohorts (Generation R, n = 2,280 and ALSPAC, n = 3,442). Pregnant women and their partners completed questionnaires to assess symptoms of depression and anxiety. Child attention problems were measured in Generation R at age 3 with the Child Behavior Checklist, and in ALSPAC at age 4 with the Strengths and Difficulties Questionnaire. Results: In both cohorts, antenatal maternal symptoms of depression (Generation R: OR 1.23, 95% CI 1.05-1.43; ALSPAC: OR 1.33, 95% CI 1.19-1.48) and anxiety (Generation R: OR 1.24, 95% CI 1.06-1.46; ALSPAC: OR 1.32, 95% CI 1.19-1.47) were associated with a higher risk of child attention problems. In ALSPAC, paternal depression was also associated with a higher risk of child attention problems (OR 1.11, 95% CI 1.00-1.24). After adjusting for maternal symptoms after giving birth, antenatal maternal depression and anxiety were no longer associated with child attention problems in Generation R. Moreover, there was little statistical evidence that antenatal maternal and paternal depression and anxiety had a substantially different effect on attention problems of the child. Conclusions: The apparent intrauterine effect of maternal depression and anxiety on offspring-behavioural problems may be partly explained by residual confounding. There was little evidence of a difference between the strength of associations of maternal and paternal symptoms during pregnancy with offspring-attention problems. That maternal symptoms after childbirth were also associated with offspring-behavioural problems may indicate a contribution of

Due to the complexity of the brain, and the many genetic and environmental determinants, there are endless ways in which the brain can develop, leading to at least as many possibilities in the expression of these variations in behaviours or cognitive functioning. Although the study of the brain is as old as science itself, it is just until recently that we have begun to understand more about how the brain works. Historically, scientists who dedicated their work to understanding the central nervous system came from different disciplines: medicine, biology, psychology, physics, chemistry, mathematics. However, the study of the brain has been revolutionized when an interdisciplinary approach was taken, yielding a new synthesized perspective. Similarly, existing knowledge on infant neurological development has increased during the past decades. It is based on insights generated by paediatrics (developmental neurology), movement science and neuropsychology. Currently, neuromotor development is an accepted means of measuring the maturity and intactness of an infant’s central nervous system. Impaired development of the central nervous system in the first year of life is mainly expressed in deviances in neuromotor development.