Intelligent problem-solvers externalize cognitive operations

The use of forward models (mechanisms that predict the future state of a system) is well established in cognitive and computational neuroscience. We compare and contrast two recent, but interestingly divergent, accounts of the place of forward models in the human cognitive architecture. On the Auxiliary Forward Model (AFM) account, forward models are special-purpose prediction mechanisms implemented by additional circuitry distinct from core mechanisms of perception and action. On the Integral Forward Model (IFM) account, forward models lie at the heart of all forms of perception and action. We compare these neighbouring but importantly different visions and consider their implications for the cognitive sciences. We end by asking what kinds of empirical research might offer evidence favouring one or the other of these approaches

Failure of Working Memory Training to Enhance Cognition or Intelligence

Fluid intelligence is important for successful functioning in the modern world, but much evidence suggests that fluid intelligence is largely immutable after childhood. Recently, however, researchers have reported gains in fluid intelligence after multiple sessions of adaptive working memory training in adults. The current study attempted to replicate and expand those results by administering a broad assessment of cognitive abilities and personality traits to young adults who underwent 20 sessions of an adaptive dual n-back working memory training program and comparing their post-training performance on those tests to a matched set of young adults who underwent 20 sessions of an adaptive attentional tracking program. Pre- and post-training measurements of fluid intelligence, standardized intelligence tests, speed of processing, reading skills, and other tests of working memory were assessed. Both training groups exhibited substantial and specific improvements on the trained tasks that persisted for at least 6 months post-training, but no transfer of improvement was observed to any of the non-trained measurements when compared to a third untrained group serving as a passive control. These findings fail to support the idea that adaptive working memory training in healthy young adults enhances working memory capacity in non-trained tasks, fluid intelligence, or other measures of cognitive abilities.National Institutes of Health (U.S.) (Blueprint for Neuroscience Research (T90DA022759/R90DA023427)United States. Defense Advanced Research Projects Agency (government contract no. NBCHC070105)United States. Dept. of Defense (National Defense Science and Engineering Fellowship)Massachusetts Institute of Technology (Sheldon Razin (1959) Fellowship

Attentional WM is not necessarily specifically related with fluid intelligence: the case of smart children with ADHD symptoms.

Executive functions and, in particular, Attentional (active) Working Memory (WM) have been associated with fluid intelligence. The association contrasts with the hypothesis that children with ADHD exhibit problems with WM tasks requiring controlled attention and may have a good fluid intelligence. This paper examines whether children who are intelligent but present ADHD symptoms fail in attentional WM tasks. The latter result would be problematic for theories assuming the generality of a strict relationship between intelligence and WM. To study these issues, a battery of tests was administered to a group of 58 children who all displayed symptoms of ADHD. All children were between the age of 8 and 11 years, and were described by their teachers as smart. Children were compared to a control group matched for age, schooling, and gender. The battery included a test of fluid intelligence (Raven's Coloured Matrices), and a series of visuospatial WM tasks. Results showed that children with ADHD were high in intelligence but significantly lower than the controls in WM tasks requiring high attentional control, whereas there was no difference in WM tasks requiring low attentional control. Furthermore, only high attentional control WM tasks were significantly related to Raven's performance in the control group, whereas all WM tasks were similarly related in the ADHD group. It is concluded that performance in high attentional control WM tasks may be related to fluid intelligence, but also to a specific control component that is independent of intelligence and is poor in children with ADHD

Exploring the relationship between video game expertise and fluid intelligence

Hundreds of millions of people play intellectually-demanding video games every day. What does individual performance on these games tell us about cognition? Here, we describe two studies that examine the potential link between intelligence and performance in one of the most popular video games genres in the world (Multiplayer Online Battle Arenas: MOBAs). In the first study, we show that performance in the popular MOBA League of Legends' correlates with fluid intelligence as measured under controlled laboratory conditions. In the second study, we also show that the age profile of performance in the two most widely-played MOBAs (League of Legends and DOTA II) matches that of raw fluid intelligence. We discuss and extend previous videogame literature on intelligence and videogames and suggest that commercial video games can be useful as 'proxy' tests of cognitive performance at a global population level

Intakes of fruits and vegetables, carotenoids and vitamins A, E, C in relation to the risk of bladder cancer in the ATBC cohort study

We examined the relation between dietary fruit and vegetables, carotenoids and vitamin intakes and the risk of bladder cancer among male smokers in a prospective cohort study. Over a median of 11 years, we followed 27 111 male smokers aged 50–69 years who were initially enrolled in the Alpha-Tocopherol Beta-Carotene Cancer Prevention Study. During this period, 344 men developed bladder cancer. All of these men had completed a 276-food item dietary questionnaire at baseline. Cox proportional hazards models were used to estimate the relative risks and 95% confidence intervals and to simultaneously adjust for age, smoking history, energy intake and intervention group. Consumption of fruits and vegetables was not associated with the risk of bladder cancer (relative risk=1.28; 95% confidence intervals CI: 0.89–1.84, for highest vs lowest quintile). Similarly, no associations were observed for groups of fruits or vegetables (berries and cruciferous vegetables), or for specific fruits and vegetables. Dietary intakes of alpha-carotene, beta-carotene, lycopene, lutein/zeaxanthin, beta-cryptoxanthin, vitamins A, E, and C, and folate were not related to the risk of bladder cancer. These findings suggest that fruit and vegetable intakes are not likely to be associated with bladder cancer risk. However, these results may not be generalisable to non-smokers

Regional brain morphometry in patients with traumatic brain injury based on acute- and chronic-phase magnetic resonance imaging

Traumatic brain injury (TBI) is caused by a sudden external force and can be very heterogeneous in its manifestation. In this work, we analyse T1-weighted magnetic resonance (MR) brain images that were prospectively acquired from patients who sustained mild to severe TBI. We investigate the potential of a recently proposed automatic segmentation method to support the outcome prediction of TBI. Specifically, we extract meaningful cross-sectional and longitudinal measurements from acute-and chronic-phase MR images. We calculate regional volume and asymmetry features at the acute/subacute stage of the injury (median: 19 days after injury), to predict the disability outcome of 67 patients at the chronic disease stage (median: 229 days after injury). Our results indicate that small structural volumes in the acute stage (e. g. of the hippocampus, accumbens, amygdala) can be strong predictors for unfavourable disease outcome. Further, group differences in atrophy are investigated. We find that patients with unfavourable outcome show increased atrophy. Among patients with severe disability outcome we observed a significantly higher mean reduction of cerebral white matter (3.1%) as compared to patients with low disability outcome (0.7%)

Characterizing the Atmospheric Mn Cycle and Its Impact on Terrestrial Biogeochemistry

The role of manganese (Mn) in ecosystem carbon (C) biogeochemical cycling is gaining increasing attention. While soil Mn is mainly derived from bedrock, atmospheric deposition could be a major source of Mn to surface soils, with implications for soil C cycling. However, quantification of the atmospheric Mn cycle, which comprises emissions from natural (desert dust, sea salts, volcanoes, primary biogenic particles, and wildfires) and anthropogenic sources (e.g., industrialization and land-use change due to agriculture), transport, and deposition, remains uncertain. Here, we use compiled emission data sets for each identified source to model and quantify the atmospheric Mn cycle by combining an atmospheric model and in situ atmospheric concentration measurements. We estimated global emissions of atmospheric Mn in aerosols (<10 mu m in aerodynamic diameter) to be 1,400 Gg Mn year(-1). Approximately 31% of the emissions come from anthropogenic sources. Deposition of the anthropogenic Mn shortened Mn "pseudo" turnover times in 1-m-thick surface soils (ranging from 1,000 to over 10,000,000 years) by 1-2 orders of magnitude in industrialized regions. Such anthropogenic Mn inputs boosted the Mn-to-N ratio of the atmospheric deposition in non-desert dominated regions (between 5 x 10(-5) and 0.02) across industrialized areas, but that was still lower than soil Mn-to-N ratio by 1-3 orders of magnitude. Correlation analysis revealed a negative relationship between Mn deposition and topsoil C density across temperate and (sub)tropical forests, consisting with atmospheric Mn deposition enhancing carbon respiration as seen in in situ biogeochemical studies

Constraining Present-Day Anthropogenic Total Iron Emissions Using Model and Observations

Iron emissions from human activities, such as oil combustion and smelting, affect the Earth's climate and marine ecosystems. These emissions are difficult to quantify accurately due to a lack of observations, particularly in remote ocean regions. In this study, we used long-term, near-source observations in areas with a dominance of anthropogenic iron emissions in various parts of the world to better estimate the total amount of anthropogenic iron emissions. We also used a statistical source apportionment method to identify the anthropogenic components and their sub-sources from bulk aerosol observations in the United States. We find that the estimates of anthropogenic iron emissions are within a factor of 3 in most regions compared to previous inventory estimates. Under- or overestimation varied by region and depended on the number of sites, interannual variability, and the statistical filter choice. Smelting-related iron emissions are overestimated by a factor of 1.5 in East Asia compared to previous estimates. More long-term iron observations and the consideration of the influence of dust and wildfires could help reduce the uncertainty in anthropogenic iron emissions estimates.Human activities, such as smelting and oil combustion, release smoke and particles into the atmosphere. These particles often contain iron, which not only absorbs sunlight, contributing to atmospheric warming, but also serves as a nutrient for phytoplankton in various ocean regions. However, the precise extent of human-induced iron emissions remains uncertain due to a lack of comprehensive monitoring data. In this study, we leverage a global data set of iron observations to refine our estimates of iron emissions attributed to human activities. Additionally, we examine other co-released substances, such as carbon and nickel, to identify specific emission sources of iron. We employ statistical techniques to distinguish human-caused iron emissions from those originating from natural sources like dust and wildfires. Moreover, we utilize iron oxide observations to constrain emissions originating from East Asia and Norway, which are estimated to originate largely from smelting emissions. Through the analysis of long-term data sets, we provide lower and upper bounds to human-caused iron emissions. Furthermore, we investigate the impact of reduced observation numbers and a sparse network on the range of estimated iron emissions. Our findings highlight the critical role of observation quality in accurately assessing iron emissions from human activities.Anthropogenic total iron emissions are constrained to a factor of 3 in most global regions using long-term aerosol observations The number of sites, interannual variability, and site selection filter can affect the model-observation comparison uncertainty by 15%-50% Smelting-related emissions are constrained to a factor of 1.5 using iron oxide observations from East Asi