Cumulative technological culture (CTC) refers to the increase in the efficiency and complexity of tools and techniques in human populations over generations. A fascinating question is to understand the cognitive origins of this phenomenon. Because CTC is definitely a social phenomenon, most accounts have suggested a series of cognitive mechanisms oriented toward the social dimension (e.g., teaching, imitation, theory of mind, and metacognition), thereby minimizing the technical dimension and the potential influence of non-social, cognitive skills. What if we have failed (...) to see the elephant in the room? What if social cognitive mechanisms were only catalyzing factors and not thesufficient and necessaryconditions for the emergence of CTC? In this article, we offer an alternative, unified cognitive approach to this phenomenon by assuming that CTC originates in non-social cognitive skills, namely technical-reasoning skills which enable humans to develop the technical potential necessary to constantly acquire and improve technical information. This leads us to discuss how theory of mind and metacognition, in concert with technical reasoning, can help boost CTC. The cognitive approach developed here opens up promising new avenues for reinterpreting classical issues (e.g., innovation, emulation vs. imitation, social vs. asocial learning, cooperation, teaching, and overimitation) in a field that has so far been largely dominated by other disciplines, such as evolutionary biology, mathematics, anthropology, archeology, economics, and philosophy. (shrink)

We meta-analytically investigated relations between the four-branch model of ability emotional intelligence with fluid and crystallized intelligence. We found that for each branch, the strength of relations with Gf and Gc were equivalent. Understanding emotions has the strongest relation with Gf/Gc combined, relative to facilitating thought using emotion, managing emotions, and perceiving emotion ; for the latter, relations were also moderated by stimulus type. We conclude with implications and recommendations for the study of ability EI.

Here we review 37 modern neuroimaging studies in an attempt to address this question posed by Halstead (1947) as he and other icons of the last century endeavored to understand how brain and behavior are linked through the expression of intelligence and reason. Reviewing studies from functional (i.e., functional magnetic resonance imaging, positron emission tomography) and structural (i.e., magnetic resonance spectroscopy, diffusion tensor imaging, voxel-based morphometry) neuroimaging paradigms, we report a striking consensus suggesting that variations in a distributed network predict (...) individual differences found on intelligence and reasoning tasks. We describe this network as the Parieto-Frontal Integration Theory (P-FIT). The P-FIT model includes, by Brodmann areas (BAs): the dorsolateral prefrontal cortex (BAs 6, 9, 10, 45, 46, 47), the inferior (BAs 39, 40) and superior (BA 7) parietal lobule, the anterior cingulate (BA 32), and regions within the temporal (BAs 21, 37) and occipital (BAs 18, 19) lobes. White matter regions (i.e., arcuate fasciculus) are also implicated. The P-FIT is examined in light of findings from human lesion studies, including missile wounds, frontal lobotomy/leukotomy, temporal lobectomy, and lesions resulting in damage to the language network (e.g., aphasia), as well as findings from imaging research identifying brain regions under significant genetic control. Overall, we conclude that modern neuroimaging techniques are beginning to articulate a biology of intelligence. We propose that the P-FIT provides a parsimonious account for many of the empirical observations, to date, which relate individual differences in intelligence test scores to variations in brain structure and function. Moreover, the model provides a framework for testing new hypotheses in future experimental designs. (shrink)

In this position statement it is argued that educational neuroscience must necessarily be relevant to, and therefore have implications for, both educational theory and practice. Consequently, educational neuroscientific research necessarily must embrace educational research questions in its remit.

Cumulative technological culture can be defined as the progressive diversification, complexification, and enhancement of technological traits through generations. An outstanding issue is to specify the cognitive bases of this phenomenon. Based on the literature, we identified four potential cognitive factors: namely, theory-of-mind, technical-reasoning, creativity, and fluid-cognitive skills. The goal of the present study was to test which of these factors—or a combination thereof—best predicted the cumulative performance in two experimental, micro-society conditions differing in the nature of the interaction allowed between (...) participants. The task was to build the highest possible tower. Participants were also assessed on the four aforementioned cognitive factors in order to predict cumulative performance and attractiveness. Our findings indicate that technical-reasoning skills are the best predictor of cumulative performance, even if their role may be restricted to the specific technological domain. Theory-of-mind skills may have a facilitator role, particularly in the Communication condition. Creativity can also help in the generation of novel ideas, but it is not sufficient to support innovation. Finally, fluid cognition is not involved in cumulative technological culture. Taken together, these findings suggest that domain-specific knowledge remains critical for explaining cumulative technological culture. (shrink)

The presence of general intelligence poses a major evolutionary puzzle, which has led to increased interest in its presence in nonhuman animals. The aim of this review is to critically evaluate this question and to explore the implications for current theories about the evolution of cognition. We first review domain-general and domain-specific accounts of human cognition in order to situate attempts to identify general intelligence in nonhuman animals. Recent studies are consistent with the presence of general intelligence in mammals. However, (...) the interpretation of a psychometricgfactor as general intelligence needs to be validated, in particular in primates, and we propose a range of such tests. We then evaluate the implications of general intelligence in nonhuman animals for current theories about its evolution and find support for the cultural intelligence approach, which stresses the critical importance of social inputs during the ontogenetic construction of survival-relevant skills. The presence of general intelligence in nonhumans implies that modular abilities can arise in two ways, primarily through automatic development with fixed content and secondarily through learning and automatization with more variable content. The currently best-supported model, for humans and nonhuman vertebrates alike, thus construes the mind as a mix of skills based on primary and secondary modules. The relative importance of these two components is expected to vary widely among species, and we formulate tests to quantify their strength. (shrink)