Improving standards in brain-behavior correlation analyses

Associations between two variables, for instance between brain and behavioral measurements, are often studied using correlations, and in particular Pearson correlation. However, Pearson correlation is not robust: outliers can introduce false correlations or mask existing ones. These problems are exacerbated in brain imaging by a widespread lack of control for multiple comparisons, and several issues with data interpretations. We illustrate these important problems associated with brain-behavior correlations, drawing examples from published articles. We make several propositions to alleviate these problems

The percentile bootstrap: a primer with step-by-step instructions in R.

The percentile bootstrap is the Swiss Army knife of statistics: It is a nonparametric method based on data-driven simulations. It can be applied to many statistical problems, as a substitute to standard parametric approaches, or in situations for which parametric methods do not exist. In this Tutorial, we cover R code to implement the percentile bootstrap to make inferences about central tendency (e.g., means and trimmed means) and spread in a one-sample example and in an example comparing two independent groups. For each example, we explain how to derive a bootstrap distribution and how to get a confidence interval and a p value from that distribution. We also demonstrate how to run a simulation to assess the behavior of the bootstrap. For some purposes, such as making inferences about the mean, the bootstrap performs poorly. But for other purposes, it is the only known method that works well over a broad range of situations. More broadly, combining the percentile bootstrap with robust estimators (i.e., estimators that are not overly sensitive to outliers) can help users gain a deeper understanding of their data than they would using conventional methods

Genetic mapping of maize streak virus resistance from the Mascarene source. I. Resistance in line D211 and stability against different virus clones

Maize streak virus (MSV) disease may cause significant grain yield reductions in maize in Africa. Réunion island maize germplasm is a proven source of strong resistance. Its genetic control was investigated using 123 RFLP markers in an F2 population of D211 (resistant) × B73 (susceptible). This population of 165 F2:3 families was carefully evaluated in Harare (Zimbabwe) and in Réunion. Artificial infestation was done with viruliferous leafhoppers. Each plant was rated weekly six times after infestation on a 1–9 scale previously adjusted by image analysis. QTL analyses were conducted for each scoring date, and for the areas under the disease, incidence and severity progress curves. The composite interval mapping method used allowed the estimation of the additive and dominance effects and QTL × environment interactions. Heritabilities ranged from 73% to 98%, increasing with time after infestation. Resistance to streak virus in D211 was provided by one region on chromosome 1, with a major effect, and four other regions on chromosomes 2, 3 (two regions) and 10, with moderate or minor effects. Overall, they explained 48–62% of the phenotypic variation for the different variables. On chromosome 3, one of the two regions seemed to be more involved in early resistance, whereas the second was detected at the latest scoring date. Other QTLs were found to be stable over time and across environments. Mild QTL × environment interactions were detected. Global gene action appeared to be partially dominant, in favor of resistance, except at the earliest scoring dates, where it was additive. From this population, 32 families were chosen, representing the whole range of susceptibility to MSV. They were tested in Réunion against three MSV clones, along with a co-inoculation of two of them. Virulence differences between clones were significant. There were genotype × clone interactions, and these were more marked for disease incidence than for severity. Although these interactions were not significant for the mean disease scores, it is suggested that breeders should select for completely resistant genotypes

Genetic mapping of maize streak virus resistance from the Mascarene source. II. Resistance in line CIRAD390 and stability across germplasm

The streak disease has a major effect on maize in sub-Saharan Africa. Various genetic factors for resistance to the virus have been identified and mapped in several populations; these factors derive from different sources of resistance. We have focused on the Réunion island source and have recently identified several factors in the D211 line. A second very resistant line, CIRAD390, was crossed to the same susceptible parent, B73. The linkage map comprised 124 RFLP markers, of which 79 were common with the D211×B73 map. A row-column design was used to evaluate the resistance to maize streak virus (MSV) of 191 F2:3 families under artificial infestation at two locations: Harare (Zimbabwe) and in Réunion island. Weekly ratings of resistance were taken and disease incidence and severity calculated. QTL analyses were conducted for each scoring date and for the integration over time of the disease scores, of incidence, and of severity. Heritability estimates (71–98%) were as high as for the D211×B73 population. Eight QTLs were detected on chromosomes 1, 2, 3, 5 (two QTLs), 6, 8, and 10. The chr1-QTL explained the highest proportion of phenotypic variation, about 45%. The QTLs on chromosomes 1, 2, and 10 were located in the same chromosomal bin as QTLs for MSV resistance in the D211×B73 population. In a simultaneous fit, QTLs explained together 43–67% of the phenotypic variation. The QTLs on chromosomes 3, 5, and 6 appeared to be specific for one or the other component of the resistance. For the chr3-QTL, resistance was contributed by the susceptible parent. There were significant QTL × environment interactions for some of the variables studied, but QTLs were stable in the two environments. They also appeared to be stable over time. Global gene action ranged from partial dominance to overdominance, except for disease severity. Some additional putative QTLs were also detected. The major QTL on chromosome 1 seemed to be common to the other sources of resistance, namely Tzi4, a tolerant line from IITA, and CML202 from CIMMYT. However, the distribution of the other QTLs within the genome revealed differences in Réunion germplasm and across these other resistance sources. This diversity is of great importance when considering the durability of the resistance

Healthy Aging Delays Scalp EEG Sensitivity to Noise in a Face Discrimination Task

We used a single-trial ERP approach to quantify age-related changes in the time-course of noise sensitivity. A total of 62 healthy adults, aged between 19 and 98, performed a non-speeded discrimination task between two faces. Stimulus information was controlled by parametrically manipulating the phase spectrum of these faces. Behavioral 75% correct thresholds increased with age. This result may be explained by lower signal-to-noise ratios in older brains. ERP from each subject were entered into a single-trial general linear regression model to identify variations in neural activity statistically associated with changes in image structure. The fit of the model, indexed by R2, was computed at multiple post-stimulus time points. The time-course of the R2 function showed significantly delayed noise sensitivity in older observers. This age effect is reliable, as demonstrated by test–retest in 24 subjects, and started about 120 ms after stimulus onset. Our analyses suggest also a qualitative change from a young to an older pattern of brain activity at around 47 ± 4 years old

Mitochondrial cyclophilin D promotes disease tolerance by licensing NK cell development and IL-22 production against influenza virus

Severity of pulmonary viral infections, including influenza A virus (IAV), is linked to excessive immunopathology, which impairs lung function. Thus, the same immune responses that limit viral replication can concomitantly cause lung damage that must be countered by largely uncharacterized disease tolerance mechanisms. Here, we show that mitochondrial cyclophilin D (CypD) protects against IAV via disease tolerance. Cyp