An experimental approach to training mood for resilience

According to influential theories about mood, exposure to environments characterized by specific patterns of punishments and rewards could shape mood response to future stimuli. This raises the intriguing possibility that mood could be trained by exposure to controlled environments. The aim of the present study is to investigate experimental settings that increase resilience of mood to negative stimuli. For this study, a new task was developed where participants register their mood when rewards are added or subtracted from their score. The study was conducted online, using Amazon MTurk, and a total of N = 1287 participants were recruited for all three sets of experiments. In an exploratory experiment, sixteen different experimental task environments which are characterized by different mood-reward relationships, were tested. We identified six task environments that produce the greatest improvements in mood resilience to negative stimuli, as measured by decreased sensitivity to loss. In a next step, we isolated the two most effective task environments, from the previous set of experiments, and we replicated our results and tested mood’s resilience to negative stimuli over time, in a novel sample. We found that the effects of the task environments on mood are detectable and remain significant after multiple task rounds (approximately two minutes) for an environment where good mood yielded maximum reward. These findings are a first step in our effort to better understand the mechanisms behind mood training and its potential clinical utility

Nitrogen supply and cyanide concentration influence the enrichment of nitrogen from cyanide in wheat (Triticum aestivum L.) and sorghum (Sorghum bicolor L.)

Cyanide assimilation by the beta-cyanoalanine pathway produces asparagine, aspartate and ammonium, allowing cyanide to serve as alternate or supplemental source of nitrogen. Experiments with wheat and sorghum examined the enrichment of (15)N from cyanide as a function of external cyanide concentration in the presence or absence of nitrate and/or ammonium. Cyanogenic nitrogen became enriched in plant tissues following exposure to (15)N-cyanide concentrations from 5 to 200 microm, but when exposure occurred in the absence of nitrate and ammonium, (15)N enrichment increased significantly in sorghum shoots at solution cyanide concentrations of \u3e or =50 microm and in wheat roots at 200 microm cyanide. In an experiment with sorghum using (13)C(15)N, there was also a significant difference in the tissue (13)C:(15)N ratio, suggestive of differential metabolism and transport of carbon and nitrogen under nitrogen-free conditions. A reciprocal (15)N labelling study using KC(15)N and (15)NH(4)(+) and wheat demonstrated an interaction between cyanide and ammonium in roots in which increasing solution ammonium concentrations decreased the enrichment from 100 microm cyanide. In contrast, with increasing solution cyanide concentrations there was an increase in the enrichment from ammonium. The results suggest increased transport and assimilation of cyanide in response to decreased nitrogen supply and perhaps to ammonium supply

Expanded results of simulation Experiment A.

<p>This shows the performance of the three different methods (MELD, t+TFCE, and t-test) on simulated data using three metrics (MCC, TPR, and PPV). Each row shows the results for one signal pattern and the final row shows the results collapsed across all signal patterns. Slope refers to the level of contrast between conditions; higher values indicate a stronger signal. Error bars indicate the 95% confidence interval across the simulations run at those conditions. PPV is undefined if a method does not find any significant elements; consequently, PPV results are unreliable for points at which fewer than 5 simulations identified significant features, so these points are not shown. MELD has the clearest advantage for lower levels of signal and for the dispersed signal pattern.</p

Detailed results of simulation Experiment B.

<p>The results for MCC, TPR, and PPV from 500 simulations at 5 different slopes and 5 different centralities demonstrate the reduced impact of centrality on MELD when compared to t+TFCE. t-test was unaffected by centrality but was much less sensitive than the other two methods. MELD was stable across all levels of centrality at higher levels of slope while t+TFCE was sensitive to differences in centrality at all levels of slope. At a slope of 0.5, MELD was more sensitive to changes in centrality than at higher slopes, but at 10% centrality it still has an MCC of 0.72 ± 0.08 95%CI, compared to t+TFCE with an MCC of 0.12 ± 0.03 95%CI. The gain in overall performance and sensitivity for MELD is clearest at a slope of 0.5, but importantly, MELD is also able to detect some signal at a slope of 0.3, when the other methods are detecting very little.</p

Aggregated results of simulation Experiment A.

<p>This shows the performance of the three different methods (MELD, t+TFCER, and t-test) using three metrics (MCC,TPR, and PPV) for each of 300 simulations. Violin plots in A and B demonstrate the distributions of results for MCC and TPR respectively. The width of the colored section indicates the kernel density estimate. MELD has a greater density of values with high MCC and TPR than either of the two other methods. The colored lines connecting the points indicate results from the same simulation; lines are colored based on the method for which they had the highest value. Gray lines indicate equal values. The paucity of red lines between MELD and t+TFCE reflects very low number of simulations for which t+TFCE performed better than MELD. The distribution of PPV (C) was divided almost entirely between 0 and 1, resulting in a misleading violin plot, so instead we have just plotted a point for each simulation result. The width over which points are spread is indicative of the number of points present at that value. PPV is undefined when a method fails to identify any features as containing signal, so there are unequal numbers of points for each method.</p