Psychopathology and cognitive performance in individuals with membrane-associated guanylate kinase mutations: a functional network phenotyping study

[Formula: see text]FarmApp: a new assessment of cognitive control and memory for children and young people with neurodevelopmental difficulties

We introduce a new touchscreen-based method measuring aspects of cognitive control and memory, in children and young people with neurodevelopmental difficulties, including intellectual disability (ID). FarmApp is a gamified, tablet-based assessment tool measuring go/no-go response speed, response inhibition, visuospatial short-term memory span, and long-term memory. Here, we assessed the feasibility, validity, and utility of the method, including the benefits of measuring change in performance over two weeks. We observed that: 1) a higher proportion of participants completed FarmApp than traditional psychometric tests; 2) this proportion increased when participants had opportunity for two weeks of self-paced testing at home; 3) ADHD-relevant behavioral difficulties were associated with average go/no-go performance across all attempts, and change in go/no-go performance over time, indicating sensitivity of the method to cognitive differences with real-world relevance. We also addressed the potential utility of the FarmApp for exploring links between ID etiology and cognitive processes. We observed differences in go/no-go task between two groups of ID participants stratified by the physiological functions of associated genetic variants (chromatin-related and synaptic-related). Moreover, the synaptic group demonstrated higher degree of improvement in go/no-go performance over time. This outcome is potentially informative of dynamic mechanisms contributing to cognitive difficulties within this group. In sum, FarmApp is a feasible, valid, and useful tool increasing access to cognitive assessment for individuals with neurodevelopmental difficulties of variable severity, with an added opportunity to monitor variation in performance over time and determine capacity to acquire task competence.

Gene functional networks and autism spectrum characteristics in young people with intellectual disability: a dimensional phenotyping study

BACKGROUND

The relationships between specific genetic aetiology and phenotype in neurodevelopmental disorders are complex and hotly contested. Genes associated with intellectual disability (ID) can be grouped into networks according to gene function. This study explored whether individuals with ID show differences in autism spectrum characteristics (ASC), depending on the functional network membership of their rare, pathogenic de novo genetic variants.

METHODS

Children and young people with ID of known genetic origin were allocated to two broad functional network groups: synaptic physiology (n = 29) or chromatin regulation (n = 23). We applied principle components analysis to the Social Responsiveness Scale to map the structure of ASC in this population and identified three components-Inflexibility, Social Understanding and Social Motivation. We then used Akaike information criterion to test the best fitting models for predicting ASC components, including demographic factors (age, gender), non-ASC behavioural factors (global adaptive function, anxiety, hyperactivity, inattention), and gene functional networks.

RESULTS

We found that, when other factors are accounted for, the chromatin regulation group showed higher levels of Inflexibility. We also observed contrasting predictors of ASC within each network group. Within the chromatin regulation group, Social Understanding was associated with inattention, and Social Motivation was predicted by hyperactivity. Within the synaptic group, Social Understanding was associated with hyperactivity, and Social Motivation was linked to anxiety.

LIMITATIONS

Functional network definitions were manually curated based on multiple sources of evidence, but a data-driven approach to classification may be more robust. Sample sizes for rare genetic diagnoses remain small, mitigated by our network-based approach to group comparisons. This is a cross-sectional study across a wide age range, and longitudinal data within focused age groups will be informative of developmental trajectories across network groups.

CONCLUSION

We report that gene functional networks can predict Inflexibility, but not other ASC dimensions. Contrasting behavioural associations within each group suggest network-specific developmental pathways from genomic variation to autism. Simple classification of neurodevelopmental disorder genes as high risk or low risk for autism is unlikely to be valid or useful.

Transdiagnostic Brain Mapping in Developmental Disorders

Childhood learning difficulties and developmental disorders are common, but progress toward understanding their underlying brain mechanisms has been slow. Structural neuroimaging, cognitive, and learning data were collected from 479 children (299 boys, ranging in age from 62 to 223 months), 337 of whom had been referred to the study on the basis of learning-related cognitive problems. Machine learning identified different cognitive profiles within the sample, and hold-out cross-validation showed that these profiles were significantly associated with children's learning ability. The same machine learning approach was applied to cortical morphology data to identify different brain profiles. Hold-out cross-validation demonstrated that these were significantly associated with children's cognitive profiles. Crucially, these mappings were not one-to-one. The same neural profile could be associated with different cognitive impairments across different children. One possibility is that the organization of some children's brains is less susceptible to local deficits. This was tested by using diffusion-weighted imaging (DWI) to construct whole-brain white-matter connectomes. A simulated attack on each child's connectome revealed that some brain networks were strongly organized around highly connected hubs. Children with these networks had only selective cognitive impairments or no cognitive impairments at all. By contrast, the same attacks had a significantly different impact on some children's networks, because their brain efficiency was less critically dependent on hubs. These children had the most widespread and severe cognitive impairments. On this basis, we propose a new framework in which the nature and mechanisms of brain-to-cognition relationships are moderated by the organizational context of the overall network.

The attentive brain: insights from developmental cognitive neuroscience

Visual attention functions as a filter to select environmental information for learning and memory, making it the first step in the eventual cascade of thought and action systems. Here, we review studies of typical and atypical visual attention development and explain how they offer insights into the mechanisms of adult visual attention. We detail interactions between visual processing and visual attention, as well as the contribution of visual attention to memory. Finally, we discuss genetic mechanisms underlying attention disorders and how attention may be modified by training.