Within-person structures of daily cognitive performance cannot be inferred from between-person structures of cognitive abilities

First published online: 09 June 2020Over a century of research on between-person differences has resulted in the consensus that human cognitive abilities are hierarchically organized, with a general factor, termed general intelligence or "g," uppermost. Surprisingly, it is unknown whether this body of evidence is informative about how cognition is structured within individuals. Using data from 101 young adults performing nine cognitive tasks on 100 occasions distributed over six months, we find that the structures of individuals' cognitive abilities vary among each other, and deviate greatly from the modal between-person structure. Working memory contributes the largest share of common variance to both between- and within-person structures, but the g factor is much less prominent within than between persons. We conclude that between-person structures of cognitive abilities cannot serve as a surrogate for within-person structures. To reveal the development and organization of human intelligence, individuals need to be studied over time

Hippocampal subfields and limbic white matter jointly predict learning rate in older adults

First published online: 04 December 2019Age-related memory impairments have been linked to differences in structural brain parameters, including cerebral white matter (WM) microstructure and hippocampal (HC) volume, but their combined influences are rarely investigated. In a population-based sample of 337 older participants aged 61-82 years (Mage = 69.66, SDage = 3.92 years), we modeled the independent and joint effects of limbic WM microstructure and HC subfield volumes on verbal learning. Participants completed a verbal learning task of recall over five repeated trials and underwent magnetic resonance imaging (MRI), including structural and diffusion scans. We segmented three HC subregions on high-resolution MRI data and sampled mean fractional anisotropy (FA) from bilateral limbic WM tracts identified via deterministic fiber tractography. Using structural equation modeling, we evaluated the associations between learning rate and latent factors representing FA sampled from limbic WM tracts, and HC subfield volumes, and their latent interaction. Results showed limbic WM and the interaction of HC and WM-but not HC volume alone-predicted verbal learning rates. Model decomposition revealed HC volume is only positively associated with learning rate in individuals with higher WM anisotropy. We conclude that the structural characteristics of limbic WM regions and HC volume jointly contribute to verbal learning in older adults

Cost shares, output elasticities, and substitutability constraints

The equilibrium conditions for an economic system that produces output with several factors of production and which is subject to technological constraints are derived. Optimization of either output minus cost or integrated utility yields the conditions that output elasticities must be equal to a modification of the usual factor cost shares, where shadow prices due to the constraints add to factor prices. In a model, where capital, labor and energy (exergy) are the factors of production, the technological constraints are identified as limits to capacity utilization and automation. The shadow prices depend on the output elasticities. These elasticities are determined for Germany, Japan and the USA by econometric estimations of energy-dependent production functions that are derived from the twice differentiability requirement and the law of diminishing returns