Systems Neuroscience of Mathematical Cognition and Learning

Teresa Iuculano (1, 2, 3) , Aarthi Padmanabhan (2) , Vinod Menon (2)

1 UPD5 SHS - Université Paris Descartes - Faculté des Sciences humaines et sociales - Sorbonne
2 Stanford School of Medicine [Stanford]
3 CNRS - Centre National de la Recherche Scientifique

In this chapter, we take a systems neuroscience approach and review neurocognitive systems involved in mathematical cognition and learning, highlighting functional brain circuits that support these processes and sources of heterogeneity that influence their typical or atypical development. We first examine the core neural building blocks of numerical cognition anchored in posterior parietal and ventral temporal–occipital cortices and then describe how working memory, language, declarative memory, and cognitive control systems facilitate numerical problem-solving and help scaffold mathematical learning and skill acquisition. We then highlight the contribution of interactive functional circuits to mathematical cognition and learning at different stages of development and skill levels. We suggest that mathematical knowledge serves as a model domain for investigating the ontogenesis of human cognitive and problem-solving skills, and that a systems neuroscience framework can shed light on why some individuals excel and others struggle.

Mots clés: Associative learning; Building blocks; Cognitive control; Cognitive development; Functional brain circuits; Heterogeneity; Mathematical learning; Neurocognitive systems; Symbolic mapping; Systems neuroscience; Working memory

Domaines: Sciences de l'Homme et Société

Teresa Iuculano, Aarthi Padmanabhan, Vinod Menon. Systems Neuroscience of Mathematical Cognition and Learning. Heterogeneity of Function in Numerical Cognition, Elsevier, pp.287-336, 2018, ⟨10.1016/B978-0-12-811529-9.00015-7⟩. ⟨halshs-02960614⟩