bioRxivNeurosciencePreprint
A connectome-based neuromarker of the non-verbal number acuity and arithmetic skills
Dai ZhangiD, Liqin ZhouiD, Anmin YangiD, Shanshan LiiD, Chunqi ChangiD, Ke ZhouiD, Jia Liu BiD
Abstract
The approximate number system (ANS) is vital for survival and reproduction in animals and crucial in constructing abstract mathematical abilities in humans. Most previous neuroimaging studies focused on identifying discrete brain regions responsible for the ANS and characterizing their functions in numerosity perception. However, there lacks a neuromarker to characterize an individuals ANS acuity, especially one based on the whole-brain functional connectivity (FC). Here, we identified a distributed brain network (i.e., numerosity network) using a connectome-based predictive modeling (CPM) analysis on the resting-state functional magnetic resonance imaging (rs-fMRI) data based on a large sample size. The summed strength of all FCs within the numerosity network could reliably predict individual differences of the ANS acuity in behavior. Furthermore, in an independent dataset from the Human Connectome Project (HCP), we found that the summed FC strength within the numerosity network could also predict individual differences in arithmetic skills. Our findings illustrate that the numerosity network we identified could be an applicable neuromarker of the non-verbal number acuity and might serve as the neural basis underlying the known link between the non-verbal number acuity and mathematical abilities.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- research focus: spatial domain detection
- approach: statistical model
- Citations
- 0
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