This is the way: Network perspective on targets for spatial ability development programmes.

BACKGROUND: Spatial ability (SA) was shown to be important for success in different fields, including STEM. Recent research suggested that SA is a unitary construct, rather than a set of related skills. However, it is not clear how individual differences in different facets of SA emerge, and how they relate to variance in general cognitive ability. AIMS: The aim of the present study was threefold: 1) to examine the structure of SA testing nine theoretical models; 2) to explore the relation between 16 different facets of SA with general cognitive ability; and 3) to identify central facet(s) within the network of SA - with most links and/or strongest links to other facets. SAMPLE: The study participants were 958 university students from Russia. METHODS: The study used a comprehensive battery of 16 SA tests and a verbal ability measure. RESULTS: Results supported previous research, suggesting moderate overlap between all SA facets. Factor analysis suggested several potential structures, with similar fit indices for five different theoretically driven models, including split into small- and large scale; partially independent manipulation, visualization and navigation facets. Confirmatory factor analysis, mediation and network analyses showed spatial ability being largely independent from verbal ability. In addition, network analysis showed that navigation according to directions is in the centre of the network, potentially linking all SA facets. CONCLUSION: The results have potential implications for identifying the best targets for SA interventions. The next step in research is conducting experimental studies to evaluate effectiveness of interventions targeting navigation in comparison with other facets of SA.

Biomarkers in PTSD-susceptible and resistant veterans with war experience of more than ten years ago: FOCUS ON cortisol, thyroid hormones, testosterone and GABA.

In the present study we measured the concentrations of cortisol, thyroid hormones, testosterone, and GABA (gamma aminobutyric acid) in am blood plasma samples of combatants with an at least 10 year history of military psychological trauma (N = 74) divided in groups that either suffer from post-traumatic stress disorder (PTSD) (N = 37) or are resistant (N = 37) as well as in a control group without traumatic experience in the anamnesis, (N = 34). PTSD symptoms were assessed using the Clinician-Administered PTSD Scale (CAPS). The results show that the am blood cortisol levels of individuals that were exposed to war zone experiences irrespective susceptibility for or resistance to PTSD were significantly higher than the values observed in the controls. Testosterone levels in PTSD patients differed neither from that observed in PTSD resistant nor control groups. In the resistant group testosterone levels were however significantly higher than in controls. The level of all thyroid hormones did not differ between the study groups. GABA level was significantly lower in the PTSD group compared with healthy controls. In the resistant group blood GABA levels were not significantly different from either PTSD patients or controls. In conclusion, the current data show that cortisol and to some extent testosterone may serve as biomarker of war zone stress per se, even if trauma was experienced at least ten years before, rather than of only PTSD or resistance to PTSD. GABA, in contrast, can be considered a potential marker of the protracted nature of PTSD.

Assessing the Relationship between Verbal and Nonverbal Cognitive Abilities Using Resting-State EEG Functional Connectivity.

The present study investigates the relationship between individual differences in verbal and non-verbal cognitive abilities and resting-state EEG network characteristics. We used a network neuroscience approach to analyze both large-scale topological characteristics of the whole brain as well as local brain network characteristics. The characteristic path length, modularity, and cluster coefficient for different EEG frequency bands (alpha, high and low; beta1 and beta2, and theta) were calculated to estimate large-scale topological integration and segregation properties of the brain networks. Betweenness centrality, nodal clustering coefficient, and local connectivity strength were calculated as local network characteristics. We showed that global network integration measures in the alpha band were positively correlated with non-verbal intelligence, especially with the more difficult part of the test (Raven's total scores and E series), and the ability to operate with verbal information (the "Conclusions" verbal subtest). At the same time, individual differences in non-verbal intelligence (Raven's total score and C series), and vocabulary subtest of the verbal intelligence tests, were negatively correlated with the network segregation measures. Our results show that resting-state EEG functional connectivity can reveal the functional architecture associated with an individual difference in cognitive performance.