2016, a genome-wide association study (GWAS) of cognitive function found 36 genome-wide significant genetic variants associated with reaction time in a sample of around 95,000 individuals. These variants were found to span two regions on chromosome 2 and chromosome 12, which appear to be in or near genes involved in spermatogenesis and signaling activities by cytokine and growth factor receptors, respectively. This study additionally found significant genetic correlations between RT, memory, and verbal-numerical reasoning. Neurophysiological research using event-related potentials (ERPs) have used P3 latency as a correlate of the "decision" stage of a reaction time task. These studies have generally found that the magnitude of the association between g and P3 latency increases with more demanding task conditions. Measures of P3 latency have also been found to be consistent with the worst performance rule, wherein the correlation between P3 latency quantile mean and cognitive assessment scores becomes more strongly negative with increasing quantile. Other ERP studies have found consilience with the interpretation of the g-RT relationship residing chiefly in the "decision" component of a task, wherein most of the g-related brain activity occurs following stimulation evaluation but before motor response, while components involved in sensory processing change little across differences in g. Diffusion modeling of RT and cognitive ability Although a unified theory of reaction time and intelligence has yet to achieve consensus among psychologists, diffusion modeling provides one promising theoretical model. Diffusion modeling partitions RT into residual "non-decision" and stochastic "diffusion" stages, the latter of which represents the generation of a decision in a two-choice task. This model successfully integrates the roles of mean reaction time, response time variability, and accuracy in modeling the rate of diffusion as a variable representing the accumulated weight of evidence that generates a decision in an RT task. Under the diffusion model, this evidence accumulates by undertaking a continuous random walk between two boundaries that represent each response choice in the task. Applications of this model have shown that the basis of the g-RT relationship is specifically the relationship of g with the rate of the diffusion process, rather than with the non-decision residual time. Diffusion modeling can also successfully explain the worst performance rule by assuming that the same measure of ability (diffusion rate) mediates performance on both simple and complex cognitive tasks, which has been theoretically and empirically supported. Cognitive development There is extensive recent research using mental chronometry for the