Bridge Over Troubled Water: Commenting on Kovacs and Conway's Process Overlap Theory

Cognitive Ability, Personality, and Psychopathology: A Stormy Relationship

Cognitive and non-cognitive traits are frequently analyzed in isolation. However, there is an increasing acknowledgment that their interplay should be considered for enhancing our understanding of human psychological differences. Testing both traits in the same sample of individuals is desirable when addressing their relationships. Here, for that purpose, 299 university students from Spain (mean age = 18.5 years., 83% female) completed a cognitive ability battery comprised by nine tests, the NEO-FFI for assessing the big five personality traits, and the SCL-90-R for evaluating a range of subjective psychopathological symptoms. This resulted in 23 cognitive and non-cognitive variables that were submitted to a data reduction providing four factors: (1) neuroticism/p, (2) cognitive ability/g, (3) agreeableness/A, and (4) introversion/I. Summary factor scores revealed a positive correlation between p and I (0.47), along with negative correlations of A with p (-0.26) and with g (-0.24), and a negative correlation between A and I (-0.16). These factors were related to some degree even when the assessment of the cognitive and non-cognitive variables cannot be considered straightforwardly comparable because the former was performance based, whereas the later was based on self-reports. Conceptual and methodological implications are discussed regarding the three-way relationship among cognitive ability, personality, and subjective psychopathological symptoms.

Overlapping and dissociable brain activations for fluid intelligence and executive functions

Cognitive enhancement interventions aimed at boosting human fluid intelligence (gf) have targeted executive functions (EFs), such as updating, inhibition, and switching, in the context of transfer-inducing cognitive training. However, even though the link between EFs and gf has been demonstrated at the psychometric level, their neurofunctional overlap has not been quantitatively investigated. Identifying whether and how EFs and gf might share neural activation patterns could provide important insights into the overall hierarchical organization of human higher-order cognition, as well as suggest specific targets for interventions aimed at maximizing cognitive transfer. We present the results of a quantitative meta-analysis of the available fMRI and PET literature on EFs and gf in humans, showing the similarity between gf and (i) the overall global EF network, as well as (ii) specific maps for updating, switching, and inhibition. Results highlight a higher degree of similarity between gf and updating (80% overlap) compared with gf and inhibition (34%), and gf and switching (17%). Moreover, three brain regions activated for both gf and each of the three EFs also were identified, located in the left middle frontal gyrus, left inferior parietal lobule, and anterior cingulate cortex. Finally, resting-state functional connectivity analysis on two independent fMRI datasets showed the preferential behavioural correlation and anatomical overlap between updating and gf. These findings confirm a close link between gf and EFs, with implications for brain stimulation and cognitive training interventions.

Linking brain network reconfiguration and intelligence: Are we there yet?

Recent applications of dynamic network analyses to functional neuroimaging data have revealed relationships between a number of cognition conditions and the dynamic reconfiguration of brain networks. Here we critically review such applications of network neuroscience to intelligence. After providing an overview of network neuroscience, we center our discussion around the recently proposed Network Neuroscience Theory of Intelligence (Barbey, 2017). We evaluate and review existing empirical support for the theses made by this theory and argue that while studies strongly suggest their plausibility, evidence to date has largely been indirect. We propose avenues for future research to directly evaluate these theses by overcoming the methodological and analytical shortcomings of previous studies. In doing so, our goal is to stimulate future empirical investigations and present valuable ways forward in the network neuroscience of intelligence.

Group analyses can hide heterogeneity effects when searching for a general model: Evidence based on a conflict monitoring task

In experimental psychology, a unique model of general processing is often sought to represent the behaviors of all individuals. We address the question of whether seeking this objective - a unique model - is the most fruitful scientific strategy by studying a specific case example. In order to approach an answer to such a question, we compared the conventional approach in experimental psychology with analyses at the individual level by applying a specific mathematical modeling approach. A sample of 1159 individuals completed an experimental task based on managing conflict (a type of Simon task). Key findings revealed that at least four models are required to properly account for individuals' performance. Interestingly, four out of ten participants failed to show stimulus-response congruency effects in the experimental task, whereas the remaining 60% followed distinguishable theoretical models (consistent with conflict-monitoring theory and/or priming and episodic memory effects). The reported findings suggest that individuals' psychological characteristics might help to explain some of the reproducibility issues that are currently of great concern in psychology. These findings, along with further recent research, support the view that general and differential psychological approaches work better together for addressing relevant theoretical issues in psychological research.

Effects of cognitive training on the structure of intelligence

Targeted cognitive training, such as n-back or speed of processing training, in the hopes of raising intelligence is of great theoretical and practical importance. The most important theoretical contribution, however, is not about the malleability of intelligence. Instead, I argue the most important and novel theoretical contribution is understanding the causal structure of intelligence. The structure of intelligence, most often taken as a hierarchical factor structure, necessarily prohibits transfer from subfactors back up to intelligence. If this is the true structure, targeted cognitive training interventions will fail to increase intelligence not because intelligence is immutable, but simply because there is no causal connection between, say, working memory and intelligence. Seeing the structure of intelligence for what it is, a causal measurement model, allows us to focus testing on the presence and absence of causal links. If we can increase subfactors without transfer to other facets, we may be confirming the correct causal structure more than testing malleability. Such a blending into experimental psychometrics is a strong theoretical pursuit.

Enhancing Intelligence: From the Group to the Individual

Research aimed at testing whether short-term training programs can enhance intelligence is mainly concentrated on behavior. Expected positive effects are found sometimes, but the evidence is far from conclusive. It is assumed that training must evoke changes in the brain for observing genuine improvements in behavior. However, behavioral and brain data are seldom combined in the same study. Here we present one example of this latter type of research summarizing, discussing, and integrating already published results. The training program was based on the adaptive dual n-back task, and participants completed a comprehensive battery measuring fluid and crystallized ability, along with working memory and attention control, before and after training. They were also submitted to MRI scanning at baseline and post-training. Behavioral results revealed positive effects for visuospatial processing across cognitive domains. Brain imaging data were analyzed by longitudinal voxel-based morphometry, tensor-based morphometry, surface-based morphometry, and structural connectivity. The integration of these multimodal brain results provides clues about those observed in behavior. Our findings, along with previous research and current technological advances, are considered from the perspective that we now live in ideal times for (a) moving from the group to the individual and (b) developing personalized training programs.

Advances in Intelligence Research: What Should be Expected in the XXI Century (Questions & Answers)

Here I briefly delineate my view about the main question of this International Seminar, namely, what should we expecting from the XXI Century regarding the advancements in intelligence research. This view can be summarized as 'The Brain Connection' (TBC), meaning that neuroscience will be of paramount relevance for increasing our current knowledge related to the key question: why are some people smarter than others? We need answers to the issue of what happens in our brains when the genotype and the environment are integrated. The scientific community has devoted great research efforts, ranging from observable behavior to hidden genetics, but we are still far from having a clear general picture of what it means to be more or less intelligent. After the discussion held with the panel of experts participating in the seminar, it is concluded that advancements will be more solid and safe increasing the collaboration of scientists with shared research interests worldwide. Paralleling current sophisticated analyses of how the brain computes, nowadays science may embrace a network approach.