Several previous studies reported relationships between speed of information processing as measured with the drift parameter of the diffusion model (Ratcliff, 1978) and general intelligence. Most of these studies utilized only few tasks and none of them used more complex tasks. In contrast, our study (N = 125) was based on a large battery of 18 different response time tasks that varied both in content (numeric, figural, and verbal) and complexity (fast tasks with mean RTs of ca. 600 ms vs. more complex tasks with mean RTs of ca. 3,000 ms). Structural equation models indicated a strong relationship between a domain-general drift factor and general intelligence. Beyond that, domain-specific speed of information processing factors were closely related to the respective domain scores of the intelligence test. Furthermore, speed of information processing in the more complex tasks explained additional variance in general intelligence. In addition to these theoretically relevant findings, our study also makes methodological contributions showing that there are meaningful interindividual differences in content specific drift rates and that not only fast tasks, but also more complex tasks can be modeled with the diffusion model.

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Investigating the interaction of human endometrium and trophoblast during implantation is difficult in vitro and impossible in vivo. This study was designed to analyze the effect of trophoblast on endometrial stromal cells during implantation by comprehensive gene profiling. An in vitro coculture system of endometrial stromal cells with first-trimester trophoblast explants was established. Trophoblast and endometrial stromal cells were separated after 24 h. Gene expression of endometrial stromal cells after coculture was compared with the gene expression of endometrial stromal cells cultured alone by microarray analysis. We confirmed the expression of distinct genes using real-time PCR. Genes up-regulated included those for inflammatory response, immune response, and chemotaxis (pentraxin-related gene 3, chemokine ligands, IL-8, IL-1 receptors, IL-18 receptor, IL-15, IL-15 receptor, TNF-alpha-induced protein 6, and IL-6 signal transducer), regulators of cell growth (IGF-binding proteins 1 and 2) and signal transduction. Also up-regulated were genes for growth and development, glucose metabolism, and lipid metabolism: DKK-1, WISP, IGF-II, hydroxysteroid 11beta-dehydrogenase 1, hydroxyprostaglandin dehydrogenase 15, prostaglandin E synthase, prostaglandin F receptor, aldehyde dehydrogenase 1 family, member A3 and phosphatidic acid phosphatase type 2B. Other genes included genes for cell-cell signaling (pre-B-cell colony-enhancing factor 1), proteolysis, calcium ion binding, regulation of transcription, and others. Down-regulated genes included genes for proteolysis (MMP-11 and mitochondrial intermediate peptidase), genes for cell death (caspase 6, death-associated protein kinase 1, and histone deacetylase 5), transcription factors (sex determining region Y-box 4, dachshund homolog 1, ets variant gene 1, and zinc finger protein 84 and 435), and genes for humoral immune response (CD24 antigen). Trophoblast has a significant impact on endometrial stromal cell gene expression. Some of the genes regulated by trophoblast in endometrial stromal cells are already known to be regulated by progesterone and show the endocrine function of trophoblast during pregnancy. Others are genes so far unknown to play a role in endometrial-trophoblast interaction and open a wide field of investigation.

Based on these findings and on the functional studies of other galectins, we suggest galectin-9 as a novel endometrial marker for the mid- and late-secretory and decidual phases.

Older adults typically show slower response times in basic cognitive tasks than younger adults. A diffusion model analysis allows the clarification of why older adults react more slowly by estimating parameters that map distinct cognitive components of decision making. The main components of the diffusion model are the speed of information uptake (drift rate), the degree of conservatism regarding the decision criterion (boundary separation), and the time taken up by non-decisional processes (i.e., encoding and motoric response execution; non-decision time). While the literature shows consistent results regarding higher boundary separation and longer non-decision time for older adults, results are more complex when it comes to age differences in drift rates. We conducted a multi-level meta-analysis to identify possible sources of this variance. As possible moderators, we included task difficulty and task type. We found that age differences in drift rate are moderated both by task type and task difficulty. Older adults were inferior in drift rate in perceptual and memory tasks, but information accumulation was even increased in lexical decision tasks for the older participants. Additionally, in perceptual and lexical decision tasks, older individuals benefitted from high task difficulty. In the memory tasks, task difficulty did not moderate the negative impact of age on drift. The finding of higher boundary separation and longer non-decision time in older than younger adults generalized over task type and task difficulty. The results of our meta-analysis are consistent with recent findings of a more pronounced age-related decline in memory than in vocabulary performance.