Global Signal Regression Strengthens Association between Resting-State Functional Connectivity and Behavior, bioRxiv, 2019-02-14

Global signal regression (GSR) is one of the most debated preprocessing strategies for resting-state functional MRI. GSR effectively removes global artifacts driven by motion and respiration, but also discards globally distributed neural information and introduces negative correlations between certain brain regions. The vast majority of previous studies have focused on the effectiveness of GSR in removing imaging artifacts, as well as its potential biases. Given the growing interest in functional connectivity fingerprinting, here we considered the utilitarian question of whether GSR strengthens or weakens associations between resting-state functional connectivity (RSFC) and multiple behavioral measures across cognition, personality and emotion. By applying the variance component model to the Brain Genomics Superstruct Project (GSP), we found that behavioral variance explained by whole-brain RSFC increased by an average of 47% across 23 behavioral measures after GSR. In the Human Connectome Project (HCP), we found that behavioral variance explained by whole-brain RSFC increased by an average of 40% across 58 behavioral measures, when GSR was applied after ICA-FIX de-noising. To ensure generalizability, we repeated our analyses using kernel regression. GSR improved behavioral prediction accuracies by an average of 64% and 12% in the GSP and HCP datasets respectively. Importantly, the results were consistent across methods. A behavioral measure with greater RSFC-explained variance (using the variance component model) also exhibited greater prediction accuracy (using kernel regression). A behavioral measure with greater improvement in behavioral variance explained after GSR (using the variance component model) also enjoyed greater improvement in prediction accuracy after GSR (using kernel regression). Furthermore, GSR appeared to benefit task performance measures more than self-reported measures. Since GSR was more effective at removing motion-related and respiratory-related artifacts, GSR-related increases in variance explained and prediction accuracies were unlikely the result of motion-related or respiratory-related artifacts. However, it is worth emphasizing that the current study focused on whole-brain RSFC, so it remains unclear whether GSR improves RSFC-behavioral associations for specific connections or networks. Overall, our results suggest that at least in the case for young healthy adults, GSR strengthens the associations between RSFC and most (although not all) behavioral measures. Code for the variance component model and ridge regression can be found here httpsgithub.comThomasYeoLabCBIGtreemasterstable_projectspreprocessingLi2019_GSR.

biorxiv neuroscience 100-200-users 2019

Resting-state cross-frequency coupling networks in human electrophysiological recordings, bioRxiv, 2019-02-13

Neuronal oscillations underlie temporal coordination of neuronal processing and their synchronization enables neuronal communication across distributed brain areas to serve a variety of sensory, motor, and cognitive functions. The regulation and integration of neuronal processing between oscillating assemblies at distinct frequencies, and thereby the coordination of distinct computational functions, is thought to be achieved via cross-frequency coupling (CFC). Although many studies have observed CFC locally within a brain region during cognitive processing, the large-scale networks of CFC have remained largely uncharted. Critically, also the validity of prior CFC observations and the presence of true neuronal CFC has been recently questioned because non-sinusoidal or non-zero-mean waveforms that are commonplace in electrophysiological data cause filtering artefacts that lead to false positive CFC findings. We used a unique dataset of stereo-electroencephalography (SEEG) and source-reconstructed magnetoencephalography (MEG) data to chart whole-brain CFC networks from human resting-state brain dynamics. Using a novel graph theoretical method to distinguish true inter-areal CFC from potentially false positive CFC, we show that the resting state is characterized by two separable forms of true inter-areal CFC phase-amplitude coupling (PAC) and nm-cross-frequency phase synchrony (CFS). PAC and CFS large-scale networks coupled prefrontal, visual and sensorimotor cortices, but with opposing anatomical architectures. Crucially also directionalities between low- and high-frequency oscillations were opposite between CFS and PAC. We also found CFC to decay as a function of distance and to be stronger in the superficial than deep layers of the cortex. In conclusion, these results provide conclusive evidence for the presence of two forms of genuine inter-areal CFC and elucidate the large-scale organization of CFC resting-state networks.

biorxiv neuroscience 0-100-users 2019

Exercise twice-a-day potentiates skeletal muscle signalling responses associated with mitochondrial biogenesis in humans, which are independent of lowered muscle glycogen content, bioRxiv, 2019-02-12

Endurance exercise begun with reduced muscle glycogen stores seems to potentiate skeletal muscle protein abundance and gene expression. However, it is unknown whether this greater signalling responses is due to low muscle glycogen per se or to performing two exercise sessions in close proximity - as a first exercise session is necessary to reduce the muscle glycogen stores. In the present study, we manipulated the recovery duration between a first muscle glycogen-depleting exercise and a second exercise session, such that the second exercise session started with reduced muscle glycogen in both approaches but was performed either two or 15 h after the first exercise session (so-called twice-a-day and once-daily approaches, respectively). We found that exercise twice-a-day increased the nuclear abundance of transcription factor EB (TFEB) and nuclear factor of activated T cells (NFAT) and potentiated the transcription of peroxisome proliferator-activated receptor-ɣ coactivator 1 alpha (PGC-1a), peroxisome proliferator-activated receptor alpha (PPARa;) and peroxisome proliferator-activated receptor betadelta (PPARbd) genes, in comparison with the once-daily exercise. These results suggest that the elevated molecular signalling reported with previous train-low approaches can be attributed to performing two exercise sessions in close proximity rather than the reduced muscle glycogen content per se. The twice-a-day approach might be an effective strategy to induce adaptations related to mitochondrial biogenesis and fat oxidation.

biorxiv molecular-biology 100-200-users 2019

 

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