The functional architectures of addition and subtraction: Network discovery using fMRI and DCM

Yang Yang, Ning Zhong*, Karl Friston, Kazuyuki Imamura, Shengfu Lu, Mi Li, Haiyan Zhou, Haiyuan Wang, Kuncheng Li, Bin Hu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)

Abstract

The neuronal mechanisms underlying arithmetic calculations are not well understood but the differences between mental addition and subtraction could be particularly revealing. Using fMRI and dynamic causal modeling (DCM), this study aimed to identify the distinct neuronal architectures engaged by the cognitive processes of simple addition and subtraction. Our results revealed significantly greater activation during subtraction in regions along the dorsal pathway, including the left inferior frontal gyrus (IFG), middle portion of dorsolateral prefrontal cortex (mDLPFC), and supplementary motor area (SMA), compared with addition. Subsequent analysis of the underlying changes in connectivity – with DCM – revealed a common circuit processing basic (numeric) attributes and the retrieval of arithmetic facts. However, DCM showed that addition was more likely to engage (numeric) retrieval-based circuits in the left hemisphere, while subtraction tended to draw on (magnitude) processing in bilateral parietal cortex, especially the right intraparietal sulcus (IPS). Our findings endorse previous hypotheses about the differences in strategic implementation, dominant hemisphere, and the neuronal circuits underlying addition and subtraction. Moreover, for simple arithmetic, our connectivity results suggest that subtraction calls on more complex processing than addition: auxiliary phonological, visual, and motor processes, for representing numbers, were engaged by subtraction, relative to addition. Hum Brain Mapp 38:3210–3225, 2017.

Original languageEnglish
Pages (from-to)3210-3225
Number of pages16
JournalHuman Brain Mapping
Volume38
Issue number6
DOIs
Publication statusPublished - Jun 2017
Externally publishedYes

Keywords

  • arithmetic processing
  • dynamic causal modeling
  • fMRI
  • network discovery

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