The formation of large-scale brain networks, and their continual refinement, represent crucial developmental processes that can drive individual differences in cognition and which are associated with multiple neurodevelopmental conditions. But how does this organization arise, and what mechanisms drive diversity in organization? We use generative network modeling to provide a computational framework for understanding neurodevelopmental diversity. Within this framework macroscopic brain organization, complete with spatial embedding of its organization, is an emergent property of a generative wiring equation that optimizes its connectivity by renegotiating its biological costs and topological values continuously over time. The rules that govern these iterative wiring properties are controlled by a set of tightly framed parameters, with subtle differences in these parameters steering network growth towards different neurodiverse outcomes. Regional expression of genes associated with the simulations converge on biological processes and cellular components predominantly involved in synaptic signaling, neuronal projection, catabolic intracellular processes and protein transport. Together, this provides a unifying computational framework for conceptualizing the mechanisms and diversity in neurodevelopment, capable of integrating different levels of analysis—from genes to cognition.

A data-driven, transdiagnostic approach was used to identify the cognitive dimensions linked with learning in a mixed group of 805 children aged 5 to 18 years recognized as having problems in attention, learning, and memory by a health or education practitioner. Assessments included phonological processing; information processing speed; short-term and working memory; executive functions; and attainments in word reading, spelling, and math. Data reduction methods identified 3 dimensions of phonological processing, processing speed, and executive function for the whole sample. This model was comparable for children with and without attention-deficit/hyperactivity disorder (ADHD). The severity of learning difficulties in literacy was linked with phonological processing skills, and in math with executive control. Associations between cognition and learning were similar across younger and older children and individuals with and without ADHD, although stronger links between learning-related problems and both executive skills and processing speed were observed in children with ADHD. These results establish clear domain-specific cognitive pathways to learning that distinguish individuals in the heterogeneous population of children struggling to learn.

The efficacy of attention training paradigms is influenced by many factors, including the specificity of targeted cognitive processes, accuracy of outcome measures, accessibility to specialized populations, and adaptability to user capability. These issues are increasingly significant when working with children diagnosed with neurodevelopmental conditions that are characterized by attentional difficulties. This study investigated the efficacy of training attention in students with neurodevelopmental conditions using a novel three-dimensional Multiple Object-Tracking (3D-MOT) task. All students (ages 6-18 years) performed the Conners Continuous Performance Task (CPT-3) as a baseline measure of attention. They were then equally and randomly assigned to one of three groups: a treatment group, (3D-MOT); an active control group (visual strategy/math-based game, 2048); and a treatment as usual group. Students were trained on their respective tasks for a total of 15 training sessions over a five-week period and then reassessed on the CPT-3. Results showed that post-training CPT-3 performance significantly improved from baseline for participants in the treatment group only. This improvement indicates that training with 3D-MOT increased attentional abilities in students with neurodevelopmental conditions. These results suggest that training attention with a non-verbal, visual-based task is feasible in a school setting and accessible to atypically developing students with attentional difficulties.

Autistics demonstrate superior performances on several visuo-spatial tasks where local or detailed information processing is advantageous. Altered spatial filtering properties at an early level of visuo-spatial analysis may be a plausible perceptual origin for such detailed perception in Autism Spectrum Disorder. In this study, contrast sensitivity for both luminance and texture-defined vertically-oriented sine-wave gratings were measured across a range of spatial frequencies (0.5, 1, 2, 4 & 8 cpd) for autistics and non-autistic participants. Contrast sensitivity functions and peak frequency ratios were plotted and compared across groups. Results demonstrated that autistic participants were more sensitivity to luminance-defined, high spatial frequency gratings (8 cpd). A group difference in peak distribution was also observed as 35% of autistic participants manifested peak sensitivity for luminance-defined gratings of 4 cpd, compared to only 7% for the comparison group. These findings support that locally-biased perception in Autism Spectrum Disorder originates, at least in part, from differences in response properties of early spatial mechanisms favouring detailed spatial information processing.