Evaluating Acquisition Time of rfMRI in the Human Connectome Project for Early Psychosis. How Much Is Enough?

Resting-state functional MRI (rfMRI) correlates activity across brain regions to identify functional connectivity networks. The Human Connectome Project (HCP) for Early Psychosis has adopted the protocol of the HCP Lifespan Project, which collects 20 min of rfMRI data. However, because it is difficult for psychotic patients to remain in the scanner for long durations, we investigate here the reliability of collecting less than 20 min of rfMRI data. Varying durations of data were taken from the full datasets of 11 subjects. Correlation matrices derived from varying amounts of data were compared using the Bhattacharyya distance, and the reliability of functional network ranks was assessed using the Friedman test. We found that correlation matrix reliability improves steeply with longer windows of data up to 11–12 min, and ≥14 min of data produces correlation matrices within the variability of those produced by 18 min of data. The reliability of network connectivity rank increases with increasing durations of data, and qualitatively similar connectivity ranks for ≥10 min of data indicates that 10 min of data can still capture robust information about network connectivities

An Iterative Jackknife Approach for Assessing Reliability and Power of fMRI Group Analyses

For functional magnetic resonance imaging (fMRI) group activation maps, so-called second-level random effect approaches are commonly used, which are intended to be generalizable to the population as a whole. However, reliability of a certain activation focus as a function of group composition or group size cannot directly be deduced from such maps. This question is of particular relevance when examining smaller groups (<20–27 subjects). The approach presented here tries to address this issue by iteratively excluding each subject from a group study and presenting the overlap of the resulting (reduced) second-level maps in a group percent overlap map. This allows to judge where activation is reliable even upon excluding one, two, or three (or more) subjects, thereby also demonstrating the inherent variability that is still present in second-level analyses. Moreover, when progressively decreasing group size, foci of activation will become smaller and/or disappear; hence, the group size at which a given activation disappears can be considered to reflect the power necessary to detect this particular activation. Systematically exploiting this effect allows to rank clusters according to their observable effect size. The approach is tested using different scenarios from a recent fMRI study (children performing a “dual-use” fMRI task, n = 39), and the implications of this approach are discussed

Demyelination in mild cognitive impairment suggests progression path to Alzheimer's disease.

The preclinical Alzheimer's disease (AD) - amnestic mild cognitive impairment (MCI) - is manifested by phenotypes classified into exclusively memory (single-domain) MCI (sMCI) and multiple-domain MCI (mMCI). We suggest that typical MCI-to-AD progression occurs through the sMCI-to-mMCI sequence as a result of the extension of initial pathological processes. To support this hypothesis, we assess myelin content with a Magnetization Transfer Ratio (MTR) in 21 sMCI and 21 mMCI patients and in 42 age-, sex-, and education-matched controls. A conjunction analysis revealed MTR reduction shared by sMCI and mMCI groups in the medial temporal lobe and posterior structures including white matter (WM: splenium, posterior corona radiata) and gray matter (GM: hippocampus; parahippocampal and lingual gyri). A disjunction analysis showed the spread of demyelination to prefrontal WM and insula GM in executive mMCI. Our findings suggest that demyelination starts in the structures affected by neurofibrillary pathology; its presence correlates with the clinical picture and indicates the method of MCI-to-AD progression. In vivo staging of preclinical AD can be developed in terms of WM/GM demyelination

Variable salinity responses of 12 alfalfa genotypes and comparative expression analyses of salt-response genes

Twelve alfalfa genotypes that were selected for biomass under salinity, differences in Na and Cl concentrations in shoots and K/Na ratio were evaluated in this long-term salinity experiment. The selected plants were cloned to reduce genetic variability within each genotype. Salt tolerance (ST) index of the genotypes ranged from 0.39 to 1. The most salt-tolerant genotypes SISA14-1 (G03) and AZ-90ST (G10), the top performers for biomass, exhibited the least effect on shoot number and height. SISA14-1 (G03) accumulated low Na and Cl under salinity. Most genotypes exhibited a net reduction in shoot Ca, Mg, P, Fe, and Cu, while Mn and Zn increased under salinity. Salinity reduced foliar area and stomatal conductance; while net photosynthetic rate and transpiration were not affected. Interestingly, salinity increased chlorophyll and antioxidant capacity in most genotypes; however neither parameter correlated well to ST index. Salt-tolerant genotypes showed upregulation of the SOS1, SOS2, SOS3, HKT1, AKT1, NHX1, P5CS1, HSP90.7, HSP81.2, HSP71.1, HSPC025, OTS1, SGF29 and SAL1 genes. Gene expression analyses allowed us to classify genotypes based on their ability to regulate different components of the salt tolerance mechanism. Pyramiding different components of the salt tolerance mechanism may lead to superior salt-tolerant alfalfa genotypes