Identifying good practices for detecting inter-regional linear functional connectivity from EEG. NeuroImage Aggregating voxel-level statistical dependencies between multivariate time series is an important intermediate step when characterising functional connectivity (FC) between larger brain regions. However, there are numerous ways in which voxel-level data can be aggregated into inter-regional FC, and the advantages of each of these approaches are currently unclear. In this study we generate ground-truth data and compare the performances of various pipelines that estimate directed and undirected linear phase-to-phase FC between regions. We test the ability of several existing and novel FC analysis pipelines to identify the true regions within which connectivity was simulated. We test various inverse modelling algorithms, strategies to aggregate time series within regions, and connectivity metrics. Furthermore, we investigate the influence of the number of interactions, the signal-to-noise ratio, the noise mix, the interaction time delay, and the number of active sources per region on the ability of detecting phase-to-phase FC. Throughout all simulated scenarios, lowest performance is obtained with pipelines involving the absolute value of coherency. Further, the combination of dynamic imaging of coherent sources (DICS) beamforming with directed FC metrics that aggregate information across multiple frequencies leads to unsatisfactory results. Pipelines that show promising results with our simulated pseudo-EEG data involve the following steps: (1) Source projection using the linearly-constrained minimum variance (LCMV) beamformer. (2) Principal component analysis (PCA) using the same fixed number of components within every region. (3) Calculation of the multivariate interaction measure (MIM) for every region pair to assess undirected phase-to-phase FC, or calculation of time-reversed Granger Causality (TRGC) to assess directed phase-to-phase FC. We formulate recommendations based on these results that may increase the validity of future experimental connectivity studies. We further introduce the free ROIconnect plugin for the EEGLAB toolbox that includes the recommended methods and pipelines that are presented here. We show an exemplary application of the best performing pipeline to the analysis of EEG data recorded during motor imagery. 10.1016/j.neuroimage.2023.120218

Meta-analysis of human prefrontal cortex reveals activation of GFAP and decline of synaptic transmission in the aging brain. Wruck Wasco,Adjaye James Acta neuropathologica communications Despite ongoing research efforts, mechanisms of brain aging are still enigmatic and need to be elucidated for a better understanding of age-associated cognitive decline. The aim of this study is to investigate aging in the prefrontal cortex region of human brain in a meta-analysis of transcriptome datasets. We analyzed 591 gene expression datasets pertaining to female and male human prefrontal cortex biopsies of distinct ages. We used hierarchical clustering and principal component analysis (PCA) to determine the influence of sex and age on global transcriptome levels. In sex-specific analysis we identified genes correlating with age and differentially expressed between groups of young, middle-aged and aged. Pathways and gene ontologies (GOs) over-represented in the resulting gene sets were calculated. Potential causal relationships between genes and between GOs were explored employing the Granger test of gene expression time series over the range of ages. The most outstanding results were the age-related decline of synaptic transmission and activated expression of glial fibrillary acidic protein (GFAP) in both sexes. We found an antagonistic relationship between calcium/calmodulin dependent protein kinase IV (CAMK4) and GFAP which may include regulatory mechanisms involving cAMP responsive element binding protein (CREB) and mitogen-activated protein kinase (MAPK, alias ERK). Common to both sexes was a decline in synaptic transmission, neurogenesis and an increased base-level of inflammatory and immune-related processes. Furthermore, we detected differences in dendritic spine morphogenesis, catecholamine signaling and cellular responses to external stimuli, particularly to metal (Zinc and cadmium) ions which were higher in female brains. 10.1186/s40478-020-00907-8