Developmental dyscalculia (DD) is a heterogenous mathematics learning difficulty, affecting approximately 4 to 7% of children. Despite its prevalence, our current understanding of the neural underpinnings of DD remains limited. This study probed DD’s neural heterogeneity through case study comparative analyses between dyscalculia-at-risk children (DR) with non-dyscalculia-at-risk (NDR) children. Utilizing functional near-infrared spectroscopy, brain data from resting states and a mathematical computation task (addition) were acquired and analysed, using Graph theory assessing brain global and nodal network indicators. By comparing DR cases’ network indicators and activation with NDR children’s data, three DR cases demonstrated lower nodal efficiency, providing insights into potential early biomarkers of DD. Moreover, the thorough investigation of single cases can offer valuable insights for devising personalized interventions for children with DD.Research HighlightsAlthough the behavioural and cognitive heterogeneity of developmental dyscalculia (DD) has been investigated, its neural heterogeneity is under-researched.Case-control design empowers researchers to probe individual idiosyncrasies, transcending the constraints imposed by summary statistics derived from group comparisons.Graph theory metrics provided insights into the topological organization of the brain areas that underpins mathematical tasks, extending researchers’ understandings of their brain activations.Three dyscalculia-at-risk cases not only demonstrated different behaviorual and neural profiles, but also showed similar neural deficits, providing insights into potential early biomarkers of DD.