MEG Source Localization via Deep Learning

We present a deep learning solution to the problem of localization of magnetoencephalography (MEG) brain signals. The proposed deep model architectures are tuned for single and multiple time point MEG data, and can estimate varying numbers of dipole sources. Results from simulated MEG data on the cortical surface of a real human subject demonstrated improvements against the popular RAP-MUSIC localization algorithm in specific scenarios with varying SNR levels, inter-source correlation values, and number of sources. Importantly, the deep learning models had robust performance to forward model errors and a significant reduction in computation time, to a fraction of 1 ms, paving the way to real-time MEG source localization

Geometries of third-row transition-metal complexes from density-functional theory

A set of 41 metal-ligand bond distances in 25 third-row transition-metal complexes, for which precise structural data are known in the gas phase, is used to assess optimized and zero-point averaged geometries obtained from DFT computations with various exchange-correlation functionals and basis sets. For a given functional (except LSDA) Stuttgart-type quasi-relativistic effective core potentials and an all-electron scalar relativistic approach (ZORA) tend to produce very similar geometries. In contrast to the lighter congeners, LSDA affords reasonably accurate geometries of 5d-metal complexes, as it is among the functionals with the lowest mean and standard deviations from experiment. For this set the ranking of some other popular density functionals, ordered according to decreasing standard deviation, is BLYP > VSXC > BP86 approximate to BPW91 approximate to TPSS approximate to B3LYP approximate to PBE > TPSSh > B3PW91 approximate to B3P86 approximate to PBE hybrid. In this case hybrid functionals are superior to their nonhybrid variants. In addition, we have reinvestigated the previous test sets for 3d- (Buhl M.; Kabrede, H. J. Chem. Theory Comput. 2006, 2, 1282-1290) and 4d- (Waller, M. P.; Buhl, M. J. Comput. Chem. 2007,28,1531-1537) transition-metal complexes using all-electron scalar relativistic DFT calculations in addition to the published nonrelativistic and ECP results. For this combined test set comprising first-, second-, and third-row metal complexes, B3P86 and PBE hybrid are indicated to perform best. A remarkably consistent standard deviation of around 2 pm in metal-ligand bond distances is achieved over the entire set of d-block elements.PostprintPeer reviewe

Health and Migration: Health Securitization and Policy-Making Perspectives in the Post-Pandemic Era

It is not to deny that the up-to-date literature has already discussed the emergence of forced human mobility due to the outbreak of health crises, owing to the latter’s adverse socio-political effects on the intrastate or regional systems. However, the ongoing COVID-19 pandemic has been playing a crucial role in enhancing the research upon health crises and health securitization, hence, further recognizing their multidimensional character. Under these circumstances, this text attempts to estimate whether and to what extent the states will reconsider their agendas –in the post-pandemic era– in terms of more successfully managing health crises and associated migration, so as to respectively reduce the potential negative consequences in their internal systems

Ultra-Rapid serial visual presentation reveals dynamics of feedforward and feedback processes in the ventral visual pathway

Human visual recognition activates a dense network of overlapping feedforward and recurrent neuronal processes, making it hard to disentangle processing in the feedforward from the feedback direction. Here, we used ultra-rapid serial visual presentation to suppress sustained activity that blurs the boundaries of processing steps, enabling us to resolve two distinct stages of processing with MEG multivariate pattern classification. The first processing stage was the rapid activation cascade of the bottom-up sweep, which terminated early as visual stimuli were presented at progressively faster rates. The second stage was the emergence of categorical information with peak latency that shifted later in time with progressively faster stimulus presentations, indexing time-consuming recurrent processing. Using MEG-fMRI fusion with representational similarity, we localized recurrent signals in early visual cortex. Together, our findings segregated an initial bottom-up sweep from subsequent feedback processing, and revealed the neural signature of increased recurrent processing demands for challenging viewing conditions

Accurate computed spin-state energetics for Co(iii) complexes:implications for modelling homogeneous catalysis

Co(III) complexes are increasingly prevalent in homogeneous catalysis. Catalytic cycles involve multiple intermediates, many of which will feature unsaturated metal centres. This raises the possibility of multistate character along reaction pathways and so requires an accurate approach to calculating spin-state energetics. Here we report an assessment of the performance of DLPNO-CCSD(T) (domain-based local pair natural orbital approximation to coupled cluster theory) against experimental Co-1 to Co-3 spin splitting energies for a series of pseudo-octahedral Co(III) complexes. The alternative NEVPT2 (strongly-contracted n-electron valence perturbation theory) and a range of density functionals are also assessed. DLPNO-CCSD(T) is identified as a highly promising method, with mean absolute deviations (MADs) as small as 1.3 kcal mol(-1) when Kohn-Sham reference orbitals are used. DLPNO-CCSD(T) out-performs NEVPT2 for which a MAD of 3.5 kcal mol(-)(1 )can be achieved when a (10,12) active space is employed. Of the nine DFT methods investigated TPSS is the leading functional, with a MAD of 1.9 kcal mol(-1). Our results show how DLPNO-CCSD(T) can provide accurate spin state energetics for Co(III) species in particular and first row transition metal systems in general. DLPNO-CCSD(T) is therefore a promising method for applications in the burgeoning field of homogeneous catalysis based on Co(III) species

Detailed ab initio first-Principles study of the magnetic anisotropy in a family of trigonal pyramidal iron(II) pyrrolide complexes

A theoretical, computational, and conceptual framework for the interpretation and prediction of the magnetic anisotropy of transition metal complexes with orbitally degenerate or orbitally nearly degenerate ground states is explored. The treatment is based on complete active space self-consistent field (CASSCF) wave functions in conjunction with N-electron valence perturbation theory (NEVPT2) and quasidegenerate perturbation theory (QDPT) for treatment of magnetic field- and spin-dependent relativistic effects. The methodology is applied to a series of Fe(II) complexes in ligand fields of almost trigonal pyramidal symmetry as provided by several variants of the tris-pyrrolylmethyl amine ligand (tpa). These systems have recently attracted much attention as mononuclear single-molecule magnet (SMM) complexes. This study aims to establish how the ligand field can be fine tuned in order to maximize the magnetic anisotropy barrier. In trigonal ligand fields high-spin Fe(II) complexes adopt an orbitally degenerate ⁵E ground state with strong in-state spin–orbit coupling (SOC). We study the competing effects of SOC and the ⁵E⊗ε multimode Jahn–Teller effect as a function of the peripheral substituents on the tpa ligand. These subtle distortions were found to have a significant effect on the magnetic anisotropy. Using a rigorous treatment of all spin multiplets arising from the triplet and quintet states in the d⁶ configuration the parameters of the effective spin-Hamiltonian (SH) approach were predicted from first principles. Being based on a nonperturbative approach we investigate under which conditions the SH approach is valid and what terms need to be retained. It is demonstrated that already tiny geometric distortions observed in the crystal structures of four structurally and magnetically well-documented systems, reported recently, i.e., [Fe(tpa®)]⁻ (R = tert-butyl, Tbu (1), mesityl, Mes (2), phenyl, Ph (3), and 2,6-difluorophenyl, Dfp (4), are enough to lead to five lowest and thermally accessible spin sublevels described sufficiently well by S = 2 SH provided that it is extended with one fourth order anisotropy term. Using this most elementary parametrization that is consistent with the actual physics, the reported magnetization data for the target systems were reinterpreted and found to be in good agreement with the ab initio results. The multiplet energies from the ab initio calculations have been fitted with remarkable consistency using a ligand field (angular overlap) model (ab initio ligand field, AILFT). This allows for determination of bonding parameters and quantitatively demonstrates the correlation between increasingly negative D values and changes in the σ-bond strength induced by the peripheral ligands. In fact, the sigma-bonding capacity (and hence the Lewis basicity) of the ligand decreases along the series 1 > 2 > 3 > 4