Understanding how and when cognitive change occurs over the lifespan is a prerequisite for understanding normal and abnormal development and aging. Most studies of cognitive change are constrained, however, in their ability to detect subtle, but theoretically informative lifespan changes, as they rely on either comparing broad age groups or sparse sampling across the age range. Here, we present convergent evidence from 48,537 Web participants and a comprehensive analysis of normative data from standardized IQ and memory tests. Our results reveal considerable heterogeneity in when cognitive abilities peak: some abilities peak and begin to decline around high school graduation; some abilities plateau in early adulthood, beginning to decline in the 30s; still others do not peak until the 40s or later. These findings motivate a nuanced theory of maturation and age-related decline, where multiple, dissociable factors differentially affect different domains of cognition.

With the increasing sophistication and ubiquity of the Internet, behavioral research is on the cusp of a revolution that will do for population sampling what the computer did for stimulus control and measurement. It remains a common assumption, however, that data from self-selected Web samples must involve a trade-off between participant numbers and data quality. Concerns about data quality are heightened for performance-based cognitive and perceptual measures, particularly those that are timed or that involve complex stimuli. In experiments run with uncompensated, anonymous participants whose motivation for participation is unknown, reduced conscientiousness or lack of focus could produce results that would be difficult to interpret due to decreased overall performance, increased variability of performance, or increased measurement noise. Here, we addressed the question of data quality across a range of cognitive and perceptual tests. For three key performance metrics-mean performance, performance variance, and internal reliability-the results from selfselected Web samples did not differ systematically from those obtained from traditionally recruited and/or lab-tested samples. These findings demonstrate that collecting data from uncompensated, anonymous, unsupervised, self-selected participants need not reduce data quality, even for demanding cognitive and perceptual experiments.

It has been difficult to determine how cognitive systems change over the grand time scale of an entire life, as few cognitive systems are well enough understood; observable in infants, adolescents, and adults; and simple enough to measure to empower comparisons across vastly different ages. Here we address this challenge with data from more than 10,000 participants ranging from 11 to 85 years of age and investigate the precision of basic numerical intuitions and their relation to students' performance in school mathematics across the lifespan. We all share a foundational number sense that has been observed in adults, infants, and nonhuman animals, and that, in humans, is generated by neurons in the intraparietal sulcus. Individual differences in the precision of this evolutionarily ancient number sense may impact school mathematics performance in children; however, we know little of its role beyond childhood. Here we find that population trends suggest that the precision of one's number sense improves throughout the schoolage years, peaking quite late at ∼30 y. Despite this gradual developmental improvement, we find very large individual differences in number sense precision among people of the same age, and these differences relate to school mathematical performance throughout adolescence and the adult years. The large individual differences and prolonged development of number sense, paired with its consistent and specific link to mathematics ability across the age span, hold promise for the impact of educational interventions that target the number sense.aging | analog magnitude | approximate number system | cognitive development | ensemble representation A lthough the particulars of our minds may differ from person to person, some aspects of cognition are close to our corethey are universally shared, present in the young, and actively engaged throughout our lifetimes (1, 2). Investigating developmental changes in these core systems may present us with a picture of how the mind transforms from infancy to senescence. Here we investigated change in the approximate number system (ANS), the cognitive system that gives rise to our basic numerical intuitions (3). The ANS generates nonverbal representations of numerosity in nonhuman animals (4, 5), infants (6, 7), school-aged children (8-10), and adults from mathematically fluent cultures (11,12) as well as cultures that do not practice explicit mathematics (13,14). In humans, imaging results suggest that these basic intuitions are supported by neurons in the intraparietal sulcus (15-18), a role that can be observed shortly after birth (19). Given the phylogenetically widespread occurrence of this primitive cognitive resource, the ANS might make little or no contact with the formal mathematical abilities that humans struggle to master and that no other animals acquire (20). Alternatively, this system may be a critical foundation upon which formal mathematical abilities are constructed (21,22). Although some evidence suggests a link between the ANS and formal mathemat...

Compared with notable successes in the genetics of basic sensory transduction, progress on the genetics of higher level perception and cognition has been limited. We propose that investigating specific cognitive abilities with well-defined neural substrates, such as face recognition, may yield additional insights. In a twin study of face recognition, we found that the correlation of scores between monozygotic twins (0.70) was more than double the dizygotic twin correlation (0.29), evidence for a high genetic contribution to face recognition ability. Low correlations between face recognition scores and visual and verbal recognition scores indicate that both face recognition ability itself and its genetic basis are largely attributable to face-specific mechanisms. The present results therefore identify an unusual phenomenon: a highly specific cognitive ability that is highly heritable. Our results establish a clear genetic basis for face recognition, opening this intensively studied and socially advantageous cognitive trait to genetic investigation.behavioral genetic | face recognition | individual differences | specialist gene | generalist gene G eneral intelligence, or g, has received great attention in both quantitative genetic and molecular genetic studies of cognition (1). Strong heritability is shown by g, and neurobiological correlates of g have been identified (1-4). However, molecular studies searching for genetic correlates of g have only found chromosomal regions with very small effects (5), and studies identifying candidate genes often fail to replicate (6). On the other hand, recent studies investigating reading and spoken language, abilities that rely on more specific cognitive and neural mechanisms, have identified major contributing genes (7,8). Thus, at least some specific abilities appear relatively tractable to genetic investigation, and it is plausible that abilities involving fewer cognitive and neural mechanisms may generally depend on fewer genes. However, heritabilities of cognitive traits typically decrease as their relation to g decreases, and few highly heritable specific abilities have been identified (1, 9). We present here an exception to this trend by demonstrating both high heritability and face specificity of face recognition ability, whose well-defined neural basis and established animal models provide promising tools for investigating its genetic basis at the neural level (10).Face recognition is a paradigmatic example of a cognitively and neurally dissociable trait. Psychophysical studies suggest that the cognitive representation of faces relies on different computational processes than other stimuli (11), and neuroimaging has identified occipitotemporal areas in humans and macaques that respond much more strongly to faces than to other stimuli (12). Single-unit recording shows that macaque face patches consist of cells that respond exclusively to faces (13). Consistent with these findings, studies with patients and transcranial magnetic stimulation have demonstrated selective i...