Twin studies have demonstrated that mathematical ability is a trait determined, at least partly, by genetic factors with estimated heritability for low mathematical performance of 0.65 (Haworth et al. 2009) and 0.69 (Oliver et al. 2004).
That is, our data in effect falsify claims about the importance of a modular number sense for mathematical performance, at least in 9-year-old children.
What we show in relation to proposed mathematics domain specific variables is that a proposed number sense (a non-symbolic magnitude representation or approximate number system) is not relevant (or it has negligible relevance) for mathematical performance in 9-year-old children.
The 10-SNP set has some predictive value for low mathematical performance in our sample (PPV = 0.46, NPV = 0.70).
(2012) reported a correlation of r = −0.16 between one number sense measure and standardized mathematical performance in 458 individuals while not controlling for other variables.
For instance, factors such as working memory have been shown to predict later mathematical performance in a longitudinal developmental study (Moeller, Pixner, Zuber, Kaufmann, & Nuerk, 2011).
Importantly, the first two studies also showed that maths anxiety was still associated with cognitive reflection once mathematical performance and test anxiety were controlled for.
Although many explanations could be given for potential transfer between music training and mathematical performance (e.g., musical rhythm is based on mathematical relations), little experimental evidence has shown that such transfer occurs.
Here, we present the mathematical analysis to compare the ARROW performance for different time frame sizes.
These fixed mathematical model based methods have shown good performance for the problems they were designed for (e.g. specific imaging modality, resolution, cone density, etc.).
Although this type of approximation has been adopted in analyzing the MAC throughput performance of individual networks (e.g. for 802.11 WLAN MAC in [16]), development of comprehensive mathematical models for performance analysis of the coexisting 802.15.4 ZigBee network and 802.11 WLAN is highly non-trivial.
