Modeling longitudinal changes in hippocampal subfields and relations with memory from early- to mid-childhood

The hippocampus has been suggested to show protracted postnatal developmental growth across childhood. Most previous studies during this developmental period have been cross-sectional in nature and have focused on age-related differences in either hippocampal subregions or subfields, but not both, potentially missing localized changes. This study capitalized on a latent structural equation modeling approach to examine the longitudinal development of hippocampal subfields (cornu ammonis (CA) 2-4/dentate gyrus (DG), CA1, subiculum) in both the head and the body of the hippocampus, separately, in 165 typically developing 4- to 8-year-old children. Our findings document differential development of subfields within hippocampal head and body. Specifically, within hippocampal head, CA1 volume increased between 4−5 years and within hippocampal body, CA2-4/DG and subiculum volume increased between 5−6 years. Additionally, changes in CA1 volume in the head and changes in subiculum in the body between 4−5 years related to improvements in memory between 4−5 years. These findings demonstrate the protracted development of subfields in vivo during early- to mid-childhood, illustrate the importance of considering subfields separately in the head and body of the hippocampus, document co-occurring development of brain and behavior, and highlight the strength of longitudinal data and latent modeling when examining brain development.     

Grammatical Constructions as Relational Categories

This paper argues that grammatical constructions, specifically argument structure constructions that determine the “who did what to whom” part of sentence meaning and how this meaning is expressed syntactically, can be considered a kind of relational category. That is, grammatical constructions are represented as the abstraction of the syntactic and semantic relations of the exemplar utterances that are expressed in that construction, and it enables the generation of novel exemplars. To support this argument, I review evidence that there are parallel behavioral patterns between how children learn relational categories generally and how they learn grammatical constructions specifically. Then, I discuss computational simulations of how grammatical constructions are abstracted from exemplar sentences using a domain-general relational cognitive architecture. Last, I review evidence from adult language processing that shows parallel behavioral patterns with expert behavior from other cognitive domains. After reviewing the evidence, I consider how to integrate this account with other theories of language development.     

Oral language impairments in developmental disorders characterized by language strengths: A comparison of Asperger syndrome and nonverbal learning disabilities

Asperger syndrome (AS) and nonverbal learning disabilities (NLD) are developmental disorders in which linguistic ability is reported to be stronger than in disorders from which they must be distinguished for diagnosis. Children and adults with AS and NLD share pragmatic weaknesses, atypical social behaviours, and some cognitive features. To date, potential similarities between these disorders in oral language have not been directly examined in the literature. A review of the available research suggests that adequate structural language is another area of similarity for AS and NLD. However, systematic investigations of phonology, morphology, or syntax were not found; thus, the evidence for largely intact structural language in these disorders is indirect. The review also pointed to a common semantic profile across both disorders, characterized by strong vocabulary breadth in the face of limited depth and organization. These higher-order problems with semantics are proposed to be consistent with theoretical accounts of poor integrative abilities in AS and NLD, and to contribute to the well-documented pragmatic difficulties in these disorders.     

Journal Monitor

Journals reviewed in this article:
Pediatrics (2000) , p.140
Child: Care, Health and Development (2001) , p.140
Support for Learning (2000) , p.140
British Journal of Special Education (2000) , p.141
European Journal of Special Needs Education (2000) , p.142
British Journal of Special Education (2000) , p.143
British Journal of Learning Disabilities (2000) , p.143     

Decreased centrality of cortical volume covariance networks in autism spectrum disorders

Autism spectrum disorders (ASD) are a group of neurodevelopmental conditions characterized by atypical structural and functional brain connectivity. Complex network analysis has been mainly used to describe altered network-level organization for functional systems and white matter tracts in ASD. However, atypical functional and structural connectivity are likely to be also linked to abnormal development of the correlated structure of cortical gray matter. Such covariations of gray matter are particularly well suited to the investigation of the complex cortical pathology of ASD, which is not confined to isolated brain regions but instead acts at the systems level. In this study, we examined network centrality properties of gray matter networks in adults with ASD (n = 84) and neurotypical controls (n = 84) using graph theoretical analysis. We derived a structural covariance network for each group using interregional correlation matrices of cortical volumes extracted from a surface-based parcellation scheme containing 68 cortical regions. Differences between groups in closeness network centrality measures were evaluated using permutation testing. We identified several brain regions in the medial frontal, parietal and temporo-occipital cortices with reductions in closeness centrality in ASD compared to controls. We also found an association between an increased number of autistic traits and reduced centrality of visual nodes in neurotypicals. Our study shows that ASD are accompanied by atypical organization of structural covariance networks by means of a decreased centrality of regions relevant for social and sensorimotor processing. These findings provide further evidence for the altered network-level connectivity model of ASD.