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Editorial on the topical issue of charged species in bulk and at interfaces
No full textThe topical issue titled “Charged Species in Bulk and at Interfaces: Interaction, Mobility, Transport, and Regulation” is based on contributions from speakers at three CECAM workshops held in 2016,2018, and 2022. In addition, this editorial is also intended to express our sincere appreciation to our seniorco-organizers, Prof. Jan K. G. Dhont (FZJ, Germany) and Prof. Gerhard Kahl (TU Wien, Austria), fortheir invaluable contributions
Transient Recurrent Dynamics Shape Representations in Mice
No full textDifferent stimuli evoke transient neural responses, but how is stimulus information represented and reshaped by local recurrent circuits? We address this question using Neuropixels recordings from awake mice and recurrent network models, inferring stimulus classes (e.g., visual or tactile) from activity. A two-replica mean-field theory reduces complex network dynamics to three key quantities: the mean population activity () and overlaps (, ), reflecting response variability within and across stimulus classes. The theory predicts the time evolution of , , and . Validated in experiments, it reveals how inhibitory balancing governs the dynamics of , while chaotic dynamics shape overlaps, providing insights into the mechanisms underlying transient stimulus separation. The analysis of mutual information of an optimally trained population activity readout reveals that sparse coding (small ) allows the optimal information representation of multiple stimuli
Validation process against late phase conditions of the passive autocatalytic recombiner simulation code PARUPM as a standalone tool using experimental data from REKO-3 and THAI facilities
No full textAssociation between night shift work and markers of metabolism, cardiovascular and immune system in a population-based German cohort
No full textFunctional connectivity between tumor region and resting-state networks as imaging biomarker for overall survival in recurrent gliomas diagnosed by O -(2-[18F]fluoroethyl)- l -tyrosine PET
No full textBackgroundAmino acid PET using the tracer O-(2-[18F]fluoroethyl)-l-tyrosine (FET) is one of the most reliable imaging methods for detecting glioma recurrence. Here, we hypothesized that functional MR connectivity between the metabolic active recurrent tumor region and resting-state networks of the brain could serve as a prognostic imaging biomarker for overall survival (OS).MethodsThe study included 82 patients (26–81 years; median Eastern Cooperative Oncology Group performance score, 0) with recurrent gliomas following therapy (WHO-CNS 2021 grade 4 glioblastoma, n = 57; grade 3 or 4 astrocytoma, n = 12; grade 2 or 3 oligodendroglioma, n = 13) diagnosed by FET PET simultaneously acquired with functional resting-state MR. Functional connectivity (FC) was assessed between tumor regions and 7 canonical resting-state networks.ResultsWHO tumor grade and IDH mutation status were strong predictors of OS after recurrence (P < .001). Overall FC between tumor regions and networks was highest in oligodendrogliomas and was inversely related to tumor grade (P = .031). FC between the tumor region and the dorsal attention network was associated with longer OS (HR, 0.88; 95%CI, 0.80–0.97; P = .007), and showed an independent association with OS (HR, 0.90; 95%CI, 0.81–0.99; P = .033) in a model including clinical factors, tumor volume and MGMT. In the glioblastoma subgroup, tumor volume and FC between the tumor and the visual network (HR, 0.90; 95%CI, 0.82–0.99, P = .031) were independent predictors of survival.ConclusionsRecurrent gliomas exhibit significant FC to resting-state networks of the brain. Besides tumor type and grade, high FC between the tumor and distinct networks could serve as independent prognostic factors for improved OS in these patients
Weak and Unstable Prediction of Personality from the Structural Connectome
No full textPersonality neuroscience aims to discover links between personality traits and features of the brain. Previous neuroimaging studies have investigated the connection between the brain structure, microstructural properties of brain tissue, or the functional connectivity (FC) and these personality traits. Analyses relating personality to diffusion-weighted MRI measures were limited to investigating the voxel-wise or tract-wise association of microstructural properties with trait scores. The main goal of our study was to determine whether there is an individual predictive relationship between the structural connectome (SC) and the big five personality traits. To that end, we expanded past work in two ways: First, by focusing on the entire structural connectome (SC) instead of separate voxels and tracts; and second, by predicting personality trait scores instead of performing a statistical correlation analysis to assess an out-of-sample performance. Prediction of personality from the SC is, however, not yet as established as prediction of behavior from the FC, and sparse studies in this field so far delivered rather heterogeneous results. We, therefore, further dedicated our study to investigate whether and how different pipeline settings influence prediction performance. In a sample of 426 unrelated subjects with high-quality MRI acquisitions from the Human Connectome Project, we analyzed 19 different brain parcellations, 3 SC weightings, 3 groups of subjects, and 4 feature classes for the prediction of the 5 personality traits using a ridge regression. From the large number of evaluated pipelines, only very few lead to promising results of prediction accuracyr> 0.2, while the vast majority lead to a small prediction accuracy centered around zero. A markedly better prediction was observed for a cognition target confirming the chosen methods for SC calculation and prediction and indicating limitations of the personality trait scores and their relation to the SC. We therefore report that, for methods evaluated here, the SC cannot predict personality trait scores. Overall, we found that all considered pipeline conditions influence the predictive performance of both cognition and personality trait scores. The strongest differences were found for the trait openness and the SC weighting by number of streamlines which outperformed the other traits and weightings, respectively. As there is a substantial variation in prediction accuracy across pipelines even for the same subjects and the same target, these findings highlight the crucial importance of pipeline settings for predicting individual traits from the SC.Keywords: big five personality traits; cognition; diffusion-weighted MRI; individual differences; machine learning prediction analysis; structural connectome
To intubate or not? Balancing anesthesia in rodent fMRI: strategies to mitigate confounding effects
No full textMore than a decade ago, the introduction of intubation and mechanical ventilation for performing blood oxygen level–dependent functional MRI studies in the rodent brain allowed an improved control over the physiological conditions during scanning sessions. An accurate understanding of respiratory parameters permits to respect the 3Rs in animal research, improves significantly the fMRI outcome, and promises improved translational studies. Developments also prompted a better comprehension on anesthetics and their impact on rodent brain physiology and function, bringing new insights on the buildup of carbon dioxide, interhemispheric connectivity, or arousal, which understanding are paramount for maturing better fMRI protocols in awake rodents. Despite many arguments in favor of intubation and subsequent mechanical ventilation, there are also many valid against it. Most importantly, the choice to intubate depends on the anesthesia protocol, where in some cases intubation is essential and impractical in others. This review does not advocate for one approach over the other. Instead, by examining the literature from the past two decades, we aim to provide a comprehensive review of the pros and cons of intubation and mechanical ventilation in fMRI studies, offering arguments for an informed decision tailored to the respective research question
