Cronbach's (1957) famous division of scientific psychology into two disciplines is still actual for the fields of cognition (general mechanisms) and intelligence (dimensionality of individual differences). The welcome integration of the two fields requires the construction of mechanistic models of cognition and cognitive development that explain key phenomena in individual differences research. In this paper we argue that network modeling is a promising approach to integrate the processes of cognitive development and (developing) intelligence into one unified theory. Network models are defined mathematically, describe mechanisms on the level of the individual, and are able to explain positive correlations among intelligence subtest scores -the empirical basis for the well-known g-factor -as well as more complex factorial structures. Links between network modeling, factor modeling and item response theory allow for a common metric, encompassing both discrete and continuous characteristics, for cognitive development and intelligence.

Evidence accumulation models (EAMs) have become the dominant models of speeded decision making, which are able to decompose choices and response times into cognitive parameters that drive the decision process. Several models within the EAM framework contain fundamentally different ideas of how the decision making process operates, though previous assessments have found that these models display a high level of mimicry, which has hindered the ability of researchers to contrast these different theoretical viewpoints. Our study introduces a neglected phenomenon that we term “double responding”, which can help to further constrain these models. We show that double responding produces several interesting benchmarks, and that the predictions of different EAMs can be distinguished in standard experiment paradigms when they are constrained to account for the choice response time distributions and double responding behaviour in unison. Our findings suggest that lateral inhibition (e.g., the leaky-competing accumulator) provides models with a universal ability to make accurate predictions for these data, and that only models containing feed-forward inhibition (e.g., the diffusion model) provide poor predictions for these data regardless of the assumptions underlying how double responses are triggered. We believe that our study provides an important step forward in further constraining models of speeded decision making, though additional research on double responding is required before broad conclusions are made about which models provide the best explanation of the underlying decision-making process.

Despite decades of extensive research on creativity, the field still combats psychometric problems when measuring individual differences in creative ability. We think these seemingly technical issues have a conceptual origin. We therefore propose a minimal theory of creative ability (MTCA) to create a consistent conceptual theory to guide investigations of individual differences in creative ability. Our theory argues that creative ability, at a minimum, must include two facets: intelligence and expertise. So, the MTCA simply claims that whenever we do something creative, we use most of our cognitive abilities combined with relevant expertise to be creative. MTCA has important implications for creativity theory, measurement, and practice. But, the MTCA isn’t necessarily true, it is a minimal theory. We discuss and reject several objections to the MTCA and conclude with a falsification challenge.

Despite decades of extensive research on creativity, the field still combats psychometric problems when measuring individual differences in creative ability and people’s potential to achieve real-world outcomes that are both original and useful. We think these seemingly technical issues have a conceptual origin. We therefore propose a minimal theory of creative ability (MTCA) to create a consistent conceptual theory to guide investigations of individual differences in creative ability. Building on robust theories and findings in creativity and individual differences research, our theory argues that creative ability, at a minimum, must include two facets: intelligence and expertise. So, the MTCA simply claims that whenever we do something creative, we use most of our cognitive abilities combined with relevant expertise to be creative. MTCA has important implications for creativity theory, measurement, and practice. However, the MTCA isn’t necessarily true; it is a minimal theory. We discuss and reject several objections to the MTCA.

No abstract