Abstract: A consensus definition of intelligence remains elusive but there are many reasons to believe that the field of intelligence is entering a new era of significant progress. The convergence of recent advances in psychometrics, cognitive psychology, and neuroscience has set the stage for the development of stronger theories and more sophisticated models. The establishment of a new open access journal as an outlet for new intelligence research is evidence that the new era has begun.
Abstract: This brief commentary suggests that the usefulness of the concept of intelligence might depend on how one defines intelligence and on whether one is using it for scientificor practical purposes. Furthermore, it is suggested that the concept of working memory must not be overlooked when considering individual differences in intelligence.
Abstract: Here, I suggest we must invest our scientific resources in brain research. Scientists interested in human (and non-human) intelligence should frame their key questions regarding where to look and where to go around technical advances related to the fascinating, general purpose, highly dynamic device we call the ‘brain’.
Abstract: This brief commentary considers the potential for new directions in intelligence research, as well as possible pitfalls associated with these approaches. Specifically, this commentary focuses on the use of big data in intelligence research, the study of genes and gene-environment interactions, the interpretation of neuroscience evidence, and the effectiveness of intelligence interventions. The major pitfalls identified include methodological and data analytic limitations, as well as concerns regarding the communication of findings to other scientists and the lay public.
Abstract: The mutualism model, an alternative for the g-factor model of intelligence, implies a formative measurement model in which “g” is an index variable without a causal role. If this model is accurate, the search for a genetic of brain instantiation of “g” is deemed useless. This also implies that the (weighted) sum score of items of an intelligence test is just what it is: a weighted sum score. Preference for one index above the other is a pragmatic issue that rests mainly on predictive value.