Purpose: In this article, the authors present a tutorial on the use of developmental trajectories for studying language and cognitive impairments in developmental disorders and compare this method with the use of matching. Method: The authors assess the strengths, limitations, and practical implications of each method. The contrast between the methodologies is highlighted using the example of developmental delay and the criteria used to distinguish delay from atypical development. Results: The authors argue for the utility of the trajectory approach, using illustrations from studies investigating language and cognitive impairments in individuals with Williams syndrome, Down syndrome, and autism spectrum disorder. Conclusion: Two conclusions were reached: (a) An understanding of the underlying mechanism will be furthered by the richer descriptive vocabulary provided by the trajectories approach (e.g., in distinguishing different types of delay) and (b) an optimal design for studying developmental disorders is to combine initial cross-sectional designs with longitudinal follow-up.

The reported prevalence of psychiatric illness among adults with intellectual disability (ID) varies widely between 10 and 39%; however, many methodological problems exist. The aims of the present study were to establish the prevalence of functional psychiatric illness among adults with ID who live in the community, in order to compare the overall rate and types of psychiatric illness between the population with ID and the general population without ID, and to establish the risk factors associated with psychiatric illness in adults with ID. The study was done in two stages. In the first part, a trained psychiatrist interviewed 101 randomly selected adults with ID and their carers using the Mini Psychiatric Assessment Schedule for adults with Developmental Disability (Mini PAS‐ADD) to screen for psychiatric caseness. Out of these 101 adults, 90 had sufficient communicative abilities that made the administration of Mini PAS‐ADD possible. A second trained psychiatrist interviewed 19 out of the 20 adults who were diagnosed as psychiatric cases according to the initial Mini PAS‐ADD interview. This psychiatrist interviewed patients and their carers in line with the full PAS‐ADD interview. The second psychiatrist was blind to the initial diagnoses made according to the Mini PAS‐ADD questionnaire. A final psychiatric diagnosis was made according to International Classification of Diseases – 10^th Revision (ICD‐10) criteria. Some 14.4% (95% confidence interval = 7.4–21.4%) of the cohort had a psychiatric diagnosis according to ICD‐10 criteria: 4.4% had schizophrenia, 2.2% depressive disorder, 2.2% generalized anxiety disorder, 4.4% phobic disorder and 1% delusional disorder. The overall rate of functional psychiatric illness (point prevalence) was similar to that found in the general population (16%). However, the rates of schizophrenic illness and phobic disorder were significantly higher in the study cohort compared with those in the general population (0.4% and 1.1%, respectively). Increasing age and the presence of physical disability were significantly associated with the occurrence of psychiatric illness. Out of the 11 remaining adults with severe ID, two (18%) had a diagnosis of a psychiatric illness (one mania and one anxiety disorder) according to the Diagnostic Assessment for the Severely Handicapped (DASH) questionnaire.

Educational neuroscience is an interdisciplinary research field that seeks to translate research findings on neural mechanisms of learning to educational practice and policy and to understand the effects of education on the brain. Neuroscience and education can interact directly, by virtue of considering the brain as a biological organ that needs to be in the optimal condition to learn (‘brain health’); or indirectly, as neuroscience shapes psychological theory and psychology influences education. In this article, we trace the origins of educational neuroscience, its main areas of research activity and the principal challenges it faces as a translational field. We consider how a pure psychology approach that ignores neuroscience is at risk of being misleading for educators. We address the major criticisms of the field comprising, respectively, a priori arguments against the relevance of neuroscience to education, reservations with the current practical operation of the field, and doubts about the viability of neuroscience methods for diagnosing disorders or predicting individual differences. We consider future prospects of the field and ethical issues it raises. Finally, we discuss the challenge of responding to the (welcome) desire of education policymakers to include neuroscience evidence in their policymaking, while ensuring recommendations do not exceed the limitations of current basic science.

Intelligence, as measured by IQ, is often thought to be stable across life, but Cathy Price and colleagues investigate whether individual components are stable across adolescence, and whether fluctuations over time correlate to structural and functional brain changes. In a brain-imaging study of 33 healthy and neurologically normal individuals examined early and late in adolescence, verbal and non-verbal IQ is seen to rise and fall, with corresponding changes in grey matter in speech and movement-related regions of the brain, respectively. It seems that an individual's intellectual capacity relative to their peers can decrease or increase in the teenage years, a finding that will interest educationalists and clinical practitioners. Intelligence quotient (IQ) is a standardized measure of human intellectual capacity that takes into account a wide range of cognitive skills1. IQ is generally considered to be stable across the lifespan, with scores at one time point used to predict educational achievement and employment prospects in later years1. Neuroimaging allows us to test whether unexpected longitudinal fluctuations in measured IQ are related to brain development. Here we show that verbal and non-verbal IQ can rise or fall in the teenage years, with these changes in performance validated by their close correlation with changes in local brain structure. A combination of structural and functional imaging showed that verbal IQ changed with grey matter in a region that was activated by speech, whereas non-verbal IQ changed with grey matter in a region that was activated by finger movements. By using longitudinal assessments of the same individuals, we obviated the many sources of variation in brain structure that confound cross-sectional studies. This allowed us to dissociate neural markers for the two types of IQ and to show that general verbal and non-verbal abilities are closely linked to the sensorimotor skills involved in learning. More generally, our results emphasize the possibility that an individual’s intellectual capacity relative to their peers can decrease or increase in the teenage years. This would be encouraging to those whose intellectual potential may improve, and would be a warning that early achievers may not maintain their potential.