Examined 6 graduate students' performance of simple arithmetic calculations to test predictions of digital (counting), analog, and network models. Pairs of single-digit integers were presented and RTs for adding, multiplying, and comparing the stimuli were collected. A high correlation between RTs for addition and multiplication of the same digits was obtained. This result is consistent with a network model but presents difficulties for both analog and counting models. A "ties" effect of no increase in RT, with increases in problem size for doubles such as 2 + 2, has been found in previous studies of addition using verification procedures, but was not found with the production task employed in the present study. Instead, a different kind of ties effect was found: RT for both addition and multiplication of ties increased more slowly with problem size than did RT for non-tie problems. Findings support a distinction between location and accessibility of information in a network. (21 ref)

In this international, longitudinal study, we explored gender differences in, and gendered relationships among, math-related motivations emphasized in the Eccles (Parsons) et al. (1983) expectancy-value framework, high school math participation, educational aspirations, and career plans. Participants were from Australia, Canada, and the United States (Ns = 358, 471, 418, respectively) in Grades 9/10 at Time 1 and Grades 11/12 at Time 2. The 3 samples came from suburban middle to upper-middle socioeconomic backgrounds, primarily of Anglo-European descent. Multivariate analyses of variance revealed stereotypic gender differences in educational and occupational outcomes only among the Australian sample. Multigroup structural equation models identified latent mean differences where male adolescents held higher intrinsic value for math in the Australian sample and higher ability/success expectancy in both North American samples. Ability/success expectancy was a key predictor in the North American samples, in contrast to intrinsic value in the Australian sample. Attainment/utility ("importance") values were more important for female adolescents' career choices, except in the Australian sample. Findings are interpreted in relation to gender socialization practices, degree and type of early choice, and specialization across settings. Implications are discussed for long-term math engagement and career selection for female and male adolescents. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

40 healthy, normal newborn infants were evaluated with reference to their ability to discriminate among visual stimulus arrays consisting of 2 versus 3 or 4 versus 6 black dots. Infants made this discrimination within a habituation/dishabituation paradigm for the small number sets (2 to 3 and 3 to 2) but not for the larger sets (4 to 6 and 6 to 4). We argue that this suggests the ability to abstract numerical invariance from small-set visual arrays and may be evidence for complex information processing during the first week of life.

The last decades of neuroscience research have produced immense progress in the methods available to understand brain structure and function. Social, cognitive, clinical, affective, economic, communication, and developmental neurosciences have begun to map the relationships between neuro-psychological processes and behavioral outcomes, yielding a new understanding of human behavior and promising interventions. However, a limitation of this fast moving research is that most findings are based on small samples of convenience. Furthermore, our understanding of individual differences may be distorted by unrepresentative samples, undermining findings regarding brain-behavior mechanisms. These limitations are issues that social demographers, epidemiologists, and other population scientists have tackled, with solutions that can be applied to neuroscience. By contrast, nearly all social science disciplines, including social demography, sociology, political science, economics, communication science, and psychology, make assumptions about processes that involve the brain, but have incorporated neural measures to differing, and often limited, degrees; many still treat the brain as a black box. In this article, we describe and promote a perspective-population neuroscience-that leverages interdisciplinary expertise to (i) emphasize the importance of sampling to more clearly define the relevant populations and sampling strategies needed when using neuroscience methods to address such questions; and (ii) deepen understanding of mechanisms within population science by providing insight regarding underlying neural mechanisms. Doing so will increase our confidence in the generalizability of the findings. We provide examples to illustrate the population neuroscience approach for specific types of research questions and discuss the potential for theoretical and applied advances from this approach across areas.neuroimaging | life course | statistics | survey methodology | physics Why Population Neuroscience? How do biology, social situations, and the broader environmental context interact to guide behavior, health, and development? This question is fundamental to most, if not all, social and behavioral sciences. We argue that to effectively address the many topics that stem from this larger question across disciplines, it is necessary to (i) bring a "population perspective" to neuroscience and (ii) leverage neuroscience tools within population sciences, which are subdisciplines of many fields, areas, and departments focused on documenting and understanding the dynamics of human populations, including outcomes such as health, well-being, behavior, etc.