Extracting dynamical understanding from neural-mass models of mouse cortex

New brain atlases with high spatial resolution and whole-brain coverage have rapidly advanced our knowledge of the brain's neural architecture, including the systematic variation of excitatory and inhibitory cell densities across the mammalian cortex. But understanding how the brain's microscale physiology shapes brain dynamics at the macroscale has remained a challenge. While physiologically based mathematical models of brain dynamics are well placed to bridge this explanatory gap, their complexity can form a barrier to providing clear mechanistic interpretation of the dynamics they generate. In this work we develop a neural-mass model of the mouse cortex and show how bifurcation diagrams, which capture local dynamical responses to inputs and their variation across brain regions, can be used to understand the resulting whole-brain dynamics. We show that strong fits to resting-state functional magnetic resonance imaging (fMRI) data can be found in surprisingly simple dynamical regimes (including where all brain regions are confined to a stable fixed point) where regions are able to respond strongly to variations in their inputs, consistent with direct structural connections providing a strong constraint on functional connectivity in the anesthetized mouse. We also use bifurcation diagrams to show how perturbations to local excitatory and inhibitory coupling strengths across the cortex, constrained by cell-density data, provide spatially dependent constraints on resulting cortical activity, and support a greater diversity of coincident dynamical regimes. Our work illustrates methods for visualizing and interpreting model performance in terms of underlying dynamical mechanisms, an approach that is crucial for building explanatory and physiologically grounded models of the dynamical principles that underpin large-scale brain activity.

A method to build extended sequence context models of point mutations and indels

The mutation rate of a specific position in the human genome depends on the sequence context surrounding it. Modeling the mutation rate by estimating a rate for each possible k-mer, however, only works for small values of k since the data becomes too sparse for larger values of k. Here we propose a new method that solves this problem by grouping similar k-mers using IUPAC patterns. We refer to the method as k-mer pattern partition and have implemented it in a software package called kmerPaPa. We use a large set of human de novo mutations to show that this new method leads to improved prediction of mutation rates and makes it possible to create models using wider sequence contexts than previous studies. Revealing that for some mutation types, the mutation rate of a position is significantly affected by nucleotides that are up to four base pairs away. As the first method of its kind, it does not only predict rates for point mutations but also indels. We have additionally created a software package called Genovo that, given a k-mer pattern partition model, predicts the expected number of synonymous, missense, and other functional mutation types for each gene. Using this software, we show that the created mutation rate models increase the statistical power to detect genes containing disease-causing variants and to identify genes under strong constraint, e.g. haploinsufficient genes.

Revisiting CMB constraints on dark matter annihilation

The precision measurements of the cosmic microwave background power spectrum put a strong constraint on the dark matter annihilation cross section since the electromagnetic energy injection by the dark matter annihilation affects the ionization history of the universe. In this paper, we update our previous simulation code for calculating the ionization history with the effect of dark matter annihilation by including Helium interactions and improving the precision of calculations. We give an updated constraint on the annihilation cross section and mass of dark matter using the modified RECFAST code with the Planck 2018 datasets.

Epistasis is not a strong constraint on the recurrent evolution of toxin-resistant Na+,K+-ATPases among tetrapods

Comparative genomic studies reveal a global decline in rates of convergent amino acid substitution as a function of evolutionary distance. This pattern has been attributed to epistatic constraints on protein evolution, the idea being that mutations tend to confer the same fitness effects on more similar genetic backgrounds, so convergent substitutions are more likely to occur in closely related species. However, this hypothesis lacks experimental validation. We tested this model in the context of the recurrent evolution of resistance to cardiotonic steroids (CTS) across diverse groups of tetrapods, which occurs via specific amino acid substitutions to the α-subunit family of Na+,K+-ATPases (ATP1A). After identifying a series of recurrent substitutions at two key sites of ATP1A1 predicted to confer CTS resistance, we performed protein engineering experiments to test the functional consequences of introducing these substitutions onto divergent species backgrounds. While we find that substitutions at these sites can have substantial background-dependent effects on CTS resistance, we also find no evidence for background-dependent effects on protein activity. We further show that the magnitude of a substitution's effect on activity does not depend on the overall extent of ATP1A1 sequence divergence between species. More generally, a global analysis of substitution patterns across ATP1A orthologs and paralogs reveals that the probability of convergent substitution protein-wide is not predicted by sequence divergence. Together, these findings suggest that intramolecular epistasis is not an important constraint on the evolution of ATP1A CTS resistance in tetrapods.

Gamma-ray line from electroweakly interacting non-abelian spin-1 dark matter

We study gamma-ray line signatures from electroweakly interacting non-abelian spin-1 dark matter (DM). In this model, Z2-odd spin-1 particles including a DM candidate have the SU(2)L triplet-like features, and the Sommerfeld enhancement is relevant in the annihilation processes. We derive the annihilation cross sections contributing to the photon emission and compare with the SU(2)L triplet fermions, such as Wino DM in the supersymmetric Standard Model. The Sommerfeld enhancement factor is approximately the same in both systems, while our spin-1 DM predicts the larger annihilation cross sections into γγ/Zγ modes than those of the Wino by $$ \frac{38}{9} $$ 38 9 . This is because a spin-1 DM pair forms not only J = 0 but also J = 2 partial wave states where J denotes the total spin angular momentum. Our spin-1 DM also has a new annihilation mode into Z2-even extra heavy vector and photon, Z′γ. For this mode, the photon energy depends on the masses of DM and the heavy vector, and thus we have a chance to probe the mass spectrum. The latest gamma-ray line search in the Galactic Center region gives a strong constraint on our spin-1 DM. We can probe the DM mass for ≲ 25.3 TeV by the Cherenkov Telescope Array experiment even if we assume a conservative DM density profile.

Correspondence between isoscalar monopole strengths and α inelastic cross sections on 24Mg

The correspondence between the isoscalar monopole (IS0) transition strengths and α inelastic cross sections, the B(IS0)-(α,α′) correspondence, is investigated for 24Mg(α,α′) at 130 and 386 MeV. We adopt a microscopic coupled-channel reaction framework to link structural inputs, diagonal and transition densities, for 24Mg obtained with antisymmetrized molecular dynamics to the (α,α′) cross sections. We aim at clarifying how the B(IS0)-(α,α′) correspondence is affected by the nuclear distortion, the in-medium modification to the nucleon-nucleon effective interaction in the scattering process, and the coupled-channels effect. It is found that these effects are significant and the explanation of the B(IS0)-(α,α′) correspondence in the plane wave limit with the long-wavelength approximation, which is often used, makes no sense. Nevertheless, the B(IS0)-(α,α′) correspondence tends to remain because of a strong constraint on the transition densities between the ground state and the 0+ excited states. The correspondence is found to hold at 386 MeV with an error of about 20%–30%, while it is seriously stained at 130 MeV mainly by the strong nuclear distortion. It is also found that when a 0+ state that has a different structure from a simple α cluster state is considered, the B(IS0)-(α,α′) correspondence becomes less valid. For a quantitative discussion on the α clustering in 0+ excited states of nuclei, a microscopic description of both the structure and reaction parts will be necessary.

Empirical evidence of a fluctuation theorem for the wind mechanical power input into the ocean

Ocean dynamics is predominantly driven by the shear stress between the atmospheric winds and ocean currents. The mechanical power input to the ocean is fluctuating in space and time and the atmospheric wind sometimes decelerates the ocean currents. Building on 24 years of global satellite observations, the input of mechanical power to the ocean is analysed. A fluctuation theorem (FT) holds when the logarithm of the ratio between the occurrence of positive and negative events, of a certain magnitude of the power input, is a linear function of this magnitude and the averaging period. The flux of mechanical power to the ocean shows evidence of a FT for regions within the recirculation area of the subtropical gyre but not over extensions of western boundary currents. A FT puts a strong constraint on the temporal distribution of fluctuations of power input, connects variables obtained with different lengths of temporal averaging, guides the temporal down- and up-scaling and constrains the episodes of improbable events.

Characterizing model errors in chemical transport modeling of methane: using GOSAT XCH₄ data with weak-constraint four-dimensional variational data assimilation

We examined biases in the global GEOS-Chem chemical transport model for the period of February–May 2010 using weak-constraint (WC) four-dimensional variational (4D-Var) data assimilation and dry-air mole fractions of CH4 (XCH4) from the Greenhouse gases Observing SATellite (GOSAT). The ability of the observations and the WC 4D-Var method to mitigate model errors in CH4 concentrations was first investigated in a set of observing system simulation experiments (OSSEs). We then assimilated the GOSAT XCH4 retrievals and found that they were capable of providing information on the vertical structure of model errors and of removing a significant portion of biases in the modeled CH4 state. In the WC 4D-Var assimilation, corrections were added to the modeled CH4 state at each model time step to account for model errors and improve the model fit to the assimilated observations. Compared to the conventional strong-constraint (SC) 4D-Var assimilation, the WC method was able to significantly improve the model fit to independent observations. Examination of the WC state corrections suggested that a significant source of model errors was associated with discrepancies in the model CH4 in the stratosphere. The WC state corrections also suggested that the model vertical transport in the troposphere at middle and high latitudes is too weak. The problem was traced back to biases in the uplift of CH4 over the source regions in eastern China and North America. In the tropics, the WC assimilation pointed to the possibility of biased CH4 outflow from the African continent to the Atlantic in the mid-troposphere. The WC assimilation in this region would greatly benefit from glint observations over the ocean to provide additional constraints on the vertical structure of the model errors in the tropics. We also compared the WC assimilation at 4∘ × 5∘ and 2∘ × 2.5∘ horizontal resolutions and found that the WC corrections to mitigate the model errors were significantly larger at 4∘ × 5∘ than at 2∘ × 2.5∘ resolution, indicating the presence of resolution-dependent model errors. Our results illustrate the potential utility of the WC 4D-Var approach for characterizing model errors. However, a major limitation of this approach is the need to better characterize the specified model error covariance in the assimilation scheme.

Closed-loop surface-related multiple estimation with full-wavefield migration-reconstructed near-offsets for shallow water

Reliably separating primary and multiple reflections in a shallow water environment (i.e., 50 m to 200 m water depth) still remains a challenge. The success of previously published closed-loop surface-related multiple estimation (CL-SRME) depends heavily on the data coverage, i.e., the near-offset reconstruction. Therefore, we propose the integrated framework of CL-SRME and full-wavefield migration (FWM). Multiples recorded in the data are capable of helping infill the acquisition imprint of the FWM image. With this image as a strong constraint, we are able to reconstruct the data at near-offsets, which is essential for better primary and multiple estimation during CL-SRME. FWM applied in a non-linear way can avoid the negative influences from the missing data, and at the same time bring in more physics between primaries and multiples. The FWM image of the top part of the subsurface is also used to back-project the information from multiples to primaries with the physical constraint of all this information belongs to the same earth model, provided that a good description of the source wavefield and a reasonable velocity model are available. The proposed integrated framework first reconstructs near-offsets via the closed-loop imaging process of FWM and then feeds the complete reconstructed data to CL-SRME for better primary and multiple estimation. A good performance is demonstrated on both 2D synthetic and field data examples in a challenging shallow water environment.

Supergravity solution-generating techniques and canonical transformations of σ-models from O(D, D)

Within the framework of the flux formulation of Double Field Theory (DFT) we employ a generalised Scherk-Schwarz ansatz and discuss the classification of the twists that in the presence of the strong constraint give rise to constant generalised fluxes interpreted as gaugings. We analyse the various possibilities of turning on the fluxes Hijk, Fijk, Qijk and Rijk, and the solutions for the twists allowed in each case. While we do not impose the DFT (or equivalently supergravity) equations of motion, our results provide solution-generating techniques in supergravity when applied to a background that does solve the DFT equations. At the same time, our results give rise also to canonical transformations of 2-dimensional σ-models, a fact which is interesting especially because these are integrability-preserving transformations on the worldsheet. Both the solution-generating techniques of supergravity and the canonical transformations of 2-dimensional σ-models arise as maps that leave the generalised fluxes of DFT and their flat derivatives invariant. These maps include the known abelian/non-abelian/Poisson-Lie T-duality transformations, Yang-Baxter deformations, as well as novel generalisations of them.