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Weber-Fahr, W.

Publications and source records attributed to Weber-Fahr, W..

2 recordsLinked to original sources

Grey matter volume changes and corresponding cellular metrics identified in a longitudinal in vivo imaging approach

Magnetic resonance imaging (MRI) of the brain combined with voxel-based morphometry (VBM) has revealed structural changes of grey and white matter in a range of neurological and psychiatric disorders. However, the cellular basis of volume changes observed with VBM has remained unclear. We devised an approach to systematically correlate changes in grey matter volume (GMV) with cellular composition. Mice were alternately examined with structural MRI and two-photon in vivo microscopy at three time points, taking advantage of age-dependent changes in brain structure. We chose to image fluorescently labelled cell nuclei, because these can be readily imaged in large tissue volumes and allow inferences on several structural parameters: (1) the physical volume as determined from a subset of nuclei used to generate a geometrically defined space, (2) the number of cells, (3) the nearest neighbour distance measured between all nuclei as an indicator of cell clustering, and (4) the volume of the cell nuclei. Using this approach, we found that physical volume did not significantly correlate with GMV change, whereas mean nuclear volume was inversely correlated. When focusing on layers within the imaging volume, positive correlations of GMV were found with cell number near the cortical surface and nearest neighbour distance in deeper layers. Thus, the novel approach introduced here provided new insights into the factors underlying grey matter volume changes.

neuroscience

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories world-wide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a murine default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

neuroscience