Evaluation of Theta EEG Neurofeedback Procedure for Cognitive Training Using Simultaneous fMRI in Counterbalanced Active-Sham Study Design.

Evaluation of mechanisms of action of EEG neurofeedback (EEG-nf) using simultaneous fMRI is highly desirable to ensure its effective application for clinical rehabilitation and therapy. Counterbalancing training runs with active neurofeedback and sham (neuro)feedback for each participant is a promising approach to demonstrate specificity of training effects to the active neurofeedback. We report the first study in which EEG-nf procedure is both evaluated using simultaneous fMRI and controlled via the counterbalanced active-sham study design.

Diffusion magnetic resonance spectroscopy captures microglial reactivity related to gut-derived systemic lipopolysaccharide: A preliminary study.

Neuroinflammation is a key component underlying multiple neurological disorders, yet non-invasive and cost-effective assessment of in vivo neuroinflammatory processes in the central nervous system remains challenging. Diffusion weighted magnetic resonance spectroscopy (dMRS) has shown promise in addressing these challenges by measuring diffusivity properties of different neurometabolites, which can reflect cell-specific morphologies. Prior work has demonstrated dMRS utility in capturing microglial reactivity in the context of lipopolysaccharide (LPS) challenges and serious neurological disorders, detected as changes of microglial metabolite diffusivity properties.

Risk factors and predictors of prolonged hospital stay in the clinical course of major amputations of the upper and lower extremity a retrospective analysis of a level 1-trauma center.

Purpose: The objective was to analyze the treatment and complications of the patients after a major amputation of the upper and lower extremities. Risk factors and predictors of a prolonged hospital stay should be outlined.

Methods: This is a retrospective study of a national Level-1 Trauma center in Germany.

A cautionary tale on the effects of different covariance structures in linear mixed effects modeling of fMRI data.

With the steadily increasing abundance of longitudinal neuroimaging studies with large sample sizes and multiple repeated measures, questions arise regarding the appropriate modeling of variance and covariance. The current study examined the influence of standard classes of variance-covariance structures in linear mixed effects (LME) modeling of fMRI data from patients with pediatric mild traumatic brain injury (pmTBI; N = 181) and healthy controls (N = 162). During two visits, participants performed a cognitive control fMRI paradigm that compared congruent and incongruent stimuli.