Measuring the average power of neural oscillations, bioRxiv, 2018-10-13
AbstractBackgroundNeural oscillations are often quantified as average power relative to a cognitive, perceptual, andor behavioral task. This is commonly done using Fourier-based techniques, such as Welch’s method for estimating the power spectral density, andor by estimating narrowband oscillatory power across trials, conditions, andor groups. The core assumption underlying these approaches is that the mean is an appropriate measure of central tendency. Despite the importance of this assumption, it has not been rigorously tested.New methodWe introduce extensions of common approaches that are better suited for the physiological reality of how neural oscillations often manifest as nonstationary, high-power bursts, rather than sustained rhythms. Log-transforming, or taking the median power, significantly reduces erroneously inflated power estimates.ResultsAnalyzing 101 participants’ worth of human electrophysiology, totaling 3,560 channels and over 40 hours data, we show that, in all cases examined, spectral power is not Gaussian distributed. This is true even when oscillations are prominent and sustained, such as visual cortical alpha. Power across time, at every frequency, is characterized by a substantial long tail, which implies that estimates of average power are skewed toward large, infrequent high-power oscillatory bursts.Comparison with existing methodsIn a simulated event-related experiment we show how introducing just a few high-power oscillatory bursts, as seen in real data, can, perhaps erroneously, cause significant differences between conditions using traditional methods. These erroneous effects are substantially reduced with our new methods.ConclusionsThese results call into question the validity of common statistical practices in neural oscillation research.Highlights<jatslist list-type=bullet><jatslist-item>Analyses of oscillatory power often assume power is normally distributed.<jatslist-item><jatslist-item>Analyzing >40 hours of human MEEG and ECoG, we show that in all cases it is not.<jatslist-item><jatslist-item>This effect is demonstrated in simple simulation of an event-related task.<jatslist-item><jatslist-item>Overinflated power estimates are reduced via log-transformation or median power.<jatslist-item>
biorxiv neuroscience 0-100-users 2018Principles of Meiotic Chromosome Assembly, bioRxiv, 2018-10-13
During meiotic prophase, chromosomes organise into a series of chromatin loops emanating from a proteinaceous axis, but the mechanisms of assembly remain unclear. Here we elucidate how this elaborate three-dimensional chromosome organisation is underpinned by genomic sequence in Saccharomyces cerevisiae. Entering meiosis, strong cohesin-dependent grid-like Hi-C interaction patterns emerge, reminiscent of mammalian interphase organisation, but with distinct regulation. Meiotic patterns agree with simulations of loop extrusion limited by barriers, yet are patterned by convergent transcription rather than binding of the mammalian interphase factor, CTCF, which is absent in S. cerevisiae - thereby both challenging and extending current paradigms of local chromosome organisation. While grid-like interactions emerge independently of meiotic chromosome synapsis, synapsis itself generates additional compaction that matures differentially according to telomere proximity and chromosome size. Collectively, our results elucidate fundamental principles of chromosome assembly and demonstrate the essential role of cohesin within this evolutionarily conserved process.
biorxiv molecular-biology 0-100-users 2018The Dynamic Conformational Landscapes of the Protein Methyltransferase SETD8, bioRxiv, 2018-10-13
Elucidating conformational heterogeneity of proteins is essential for understanding protein functions and developing exogenous ligands for chemical perturbation. While structural biology methods can provide atomic details of static protein structures, these approaches cannot in general resolve less populated, functionally relevant conformations and uncover conformational kinetics. Here we demonstrate a new paradigm for illuminating dynamic conformational landscapes of target proteins. SETD8 (Pr-SET7SET8KMT5A) is a biologically relevant protein lysine methyltransferase for in vivo monomethylation of histone H4 lysine 20 and nonhistone targets. Utilizing covalent chemical inhibitors and depleting native ligands to trap hidden high-energy conformational states, we obtained diverse novel X-ray structures of SETD8. These structures were used to seed massively distributed molecular simulations that generated six milliseconds of trajectory data of SETD8 in the presence or absence of its cofactor. We used an automated machine learning approach to reveal slow conformational motions and thus distinct conformational states of SETD8, and validated the resulting dynamic conformational landscapes with multiple biophysical methods. The resulting models provide unprecedented mechanistic insight into how protein dynamics plays a role in SAM binding and thus catalysis, and how this function can be modulated by diverse cancer-associated mutants. These findings set up the foundation for revealing enzymatic mechanisms and developing inhibitors in the context of conformational landscapes of target proteins.
biorxiv biophysics 200-500-users 2018The Flexiscope a Low Cost, Flexible, Convertible, and Modular Microscope with Automated Scanning and Micromanipulation, bioRxiv, 2018-10-13
AbstractWith technologies rapidly evolving, many research institutions are now opting to invest in costly, high-quality, specialised microscopes which are shared by many researchers. As a consequence, the user does not have the ability to adapt a microscope to their specific needs and limitations in experimental design are introduced. A flexible work-horse microscopy system is a valuable tool in any laboratory to meet the diverse needs of a research team and promote innovation in experimental design. We have developed the Flexiscope; a multi-functional, adaptable, efficient and high performance microscopyelectrophysiology system for everyday applications in a neurobiology laboratory. The core optical components are relatively constant in the three configurations described here; an upright configuration, an inverted configuration and an uprightelectrophysiology configuration. We have provided a comprehensive description of the Flexiscope. We show that this method is capable of oblique infrared illumination imaging, multi-channel fluorescent imaging, and automated 3D scanning of larger specimens. Image quality is conserved across the three configurations of the microscope, and conversion between configurations is possible quickly and easily, while the motion control system can be repurposed to allow sub-micron computer-controlled micromanipulation. The Flexiscope provides similar performance and usability to commercially available systems. However, as it can be easily reconfigured for multiple roles, it can remove the need to purchase multiple microscopes, giving significant cost savings. The modular re-configurable nature allows the user to customise the system to their specific needs and adaptupgrade the system as challenges arise.
biorxiv neuroscience 0-100-users 2018Measures of neural similarity, bioRxiv, 2018-10-12
One fundamental question is what makes two brain states similar. For example, what makes the activity in visual cortex elicited from viewing a robin similar to a sparrow? One common assumption in fMRI analysis is that neural similarity is described by Pearson correlation. However, there are a host of other possibilities, including Minkowski and Mahalanobis measures, with each differing in its mathematical, theoretical, neural computational assumptions. Moreover, the operable measures may vary across brain regions and tasks. Here, we evaluated which of several competing similarity measures best captured neural similarity. Our technique uses a decoding approach to assess the information present in a brain region and the similarity measures that best correspond to the classifier's confusion matrix are preferred. Across two published fMRI datasets, we found the preferred neural similarity measures were common across brain regions, but differed across tasks. Moreover, Pearson correlation was consistently surpassed by alternatives.
biorxiv neuroscience 100-200-users 2018A Multi-State Birth-Death model for Bayesian inference of lineage-specific birth and death rates, bioRxiv, 2018-10-11
AbstractHeterogeneous populations can lead to important differences in birth and death rates across a phylogeny Taking this heterogeneity into account is thus critical to obtain accurate estimates of the underlying population dynamics. We present a new multi-state birth-death model (MSBD) that can estimate lineage-specific birth and death rates. For species phylogenies, this corresponds to estimating lineage-dependent speciation and extinction rates. Contrary to existing models, we do not require a prior hypothesis on a trait driving the rate differences and we allow the same rates to be present in different parts of the phylogeny. Using simulated datasets, we show that the MSBD model can reliably infer the presence of multiple evolutionary regimes, their positions in the tree, and the birth and death rates associated with each. We also present a re-analysis of two empirical datasets and compare the results obtained by MSBD and by the existing software BAMM. The MSBD model is implemented as a package in the Bayesian inference software BEAST2, which allows joint inference of the phylogeny and the model parameters.Significance statementPhylogenetic trees can inform about the underlying speciation and extinction processes within a species clade. Many different factors, for instance environmental changes or morphological changes, can lead to differences in macroevolutionary dynamics within a clade. We present here a new multi-state birth-death (MSBD) model that can detect these differences and estimate both the position of changes in the tree and the associated macroevolutionary parameters. The MSBD model does not require a prior hypothesis on which trait is driving the changes in dynamics and is thus applicable to a wide range of datasets. It is implemented as an extension to the existing framework BEAST2.
biorxiv evolutionary-biology 0-100-users 2018