Basis profile curve identification to understand electrical stimulation effects in human brain networks

Brain networks can be explored by delivering brief pulses of electrical current in one area while measuring voltage responses in other areas. We propose a convergent paradigm to study brain dynamics, focusing on a single brain site to observe the average effect of stimulating each of many other brain sites. Viewed in this manner, visually-apparent motifs in the temporal response shape emerge from adjacent stimulation sites. This work constructs and illustrates a data-driven approach to determine characteristic spatiotemporal structure in these response shapes, summarized by a set of unique “basis profile curves” (BPCs). Each BPC may be mapped back to underlying anatomy in a natural way, quantifying projection strength from each stimulation site using simple metrics. Our technique is demonstrated for an array of implanted brain surface electrodes in a human patient. This framework enables straightforward interpretation of single-pulse brain stimulation data, and can be applied generically to explore the diverse milieu of interactions that comprise the connectome.

Knowability Without Rigidity

The most straightforward interpretation of the principle of knowability is that every true proposition may be known. This, taken together with some intuitively appealing ideas, raises a problem known as the Church–Fitch paradox. There is a wide variety of alternative interpretations of the principle of knowability that have been offered to avoid the paradox. Some of them are based on rigidification of certain aspects of what is knowable. I examine three proposals representing this strategy, those by Edgington, Rückert and Jenkins. Edgington defines what is knowable as a proposition prefixed by the actuality operator. Rückert and Jenkins maintain that what makes a proposition knowable is the possibility of knowing de re (Rückert) or recognizing (Jenkins) the state of affairs that renders the proposition actually true. In both cases, the link to the actual world (or situation) rigidifies what is knowable in some aspect or other. I argue that all three theories have strongly counterintuitive consequences, and I offer an interpretation of the principle of knowability that is both free from rigidity and immune to the Church–Fitch argument.

A unified perturbative approach to electrocaloric effects

The electrocaloric effect, that is, the temperature change experienced by an insulator upon application of an electric field, offers promising ecofriendly alternatives to refrigeration. However, the theoretical treatments of this response are mostly case specific and lack a unified picture revealing the similarities and differences among the various known effects. Here, we show that the electrocaloric effect lends itself to a straightforward interpretation when expressed as a Taylor series in the external field. Our formalism explains in a unified and simple way the most notable small-field effects reported in the literature, namely the so-called normal and inverse electrocaloric responses, corresponding to an increase or decrease of temperature under applied field, as usually found in ferroelectrics or antiferroelectrics, respectively. This helps us to clarify their physical interpretation. We then discuss in detail atomistic simulations for the prototype ferroelectric PbTiO3, explicitly evaluating subtle predictions of the theory, such as the occurrence of competing contributions to the electrocaloric response.

Tris-{Hydridotris(1-pyrazolyl)borato}lanthanide Complexes: Synthesis, Spectroscopy, Crystal Structure and Bonding Properties

Complexes of trivalent lanthanides (Ln) with the hydridotris(1-pyrazolyl)borato (Tp) ligand Ln[η3-HB(N2C3H3)3]3 (LnTp3) were subjected to a joint experimental–theoretical analysis. X-ray diffraction experiments have been performed on CeTp3, NdTp3, SmTp3, GdTp3, and TbTp3 in the nine-fold coordination and on DyTp3, HoTp3, ErTp3, TmTp3, YbTp3, and LuTp3 in the eight-fold coordination form. Density functional theory (DFT) calculations were carried out for all 15 LnTp3 complexes. They extended the X-ray diffraction data available on the LnTp3 compounds and facilitated a straightforward interpretation of trends in the structural parameters. As a result of the joint analysis, significant steric strain in the equatorial coordination sites of the nine-coordinate structures was recognized. Trends in the bonding properties were elucidated by energy decomposition and quantum theory of atoms in molecules (QTAIM) analysis of the electron density distribution. These results revealed the major electrostatic character of the Ln…Tp bonding and fine variation of charge transfer effects across the Ln row.

A Revised Phylogeny of the Mentha spicata Clade Reveals Cryptic Species

The genus Mentha is taxonomically and phylogenetically challenging due to complex genomes, polyploidization and an extensive historical nomenclature, potentially hiding cryptic taxa. A straightforward interpretation of phylogenetic relationships within the section Mentha is further hindered by dominant but outdated concepts on historically identified hybrid taxa. Mentha spicata is traditionally considered to be of hybrid origin, but the evidence for this is weak. Here, we aim to understand the phylogenetic relationships within the section Mentha using large sample sizes and to revisit the hybrid status and identity of M. spicata. We show that two of three traditional species in the subsection Spicatae are polyphyletic, as is the subsection as a whole, while the real number of cryptic species was underestimated. Compared to previous studies we present a fundamentally different phylogeny, with a basal split between M. spicata s.s. and M. longifolia s.s. Cluster analyses of morphological and genotypic data demonstrate that there is a dissociation between morphologically and genotypically defined groups of samples. We did not find any evidence that M. spicata is of hybrid origin, and we conclude its taxonomic status should be revised. The combination of genetic and phenotypic information is essential when evaluating hyperdiverse taxonomic groups.

Using Normalized Entropy to Measure Uncertainty of Rankings for Network Meta-analyses

Ranking of treatments offers a straightforward interpretation of results derived from network meta-analysis. However, some published network meta-analyses have overemphasized treatment ranking without paying attention to its uncertainty. According to a review of 91 network meta-analyses, 52 reported treatment ranking, but 43 of them did not report the uncertainty of ranking. Without reporting the uncertainty, small differences in the ranking of treatments may be overinterpreted. Rankograms, cumulative rankograms, the credible/confidence interval of mean rank, the surface under the cumulative ranking curve (SUCRA), and the interquartile range of median rank have been used to show the uncertainty of rankings. However, it is not always straightforward to compare the differences in the distribution of probabilities by inspecting rankograms or to compare the intervals or ranges of treatment ranks. We therefore proposed normalized entropy, which transforms the distribution of ranking probabilities into a single quantitative measure, to facilitate a refined interpretation of uncertainty of treatment ranking. We used 4 real examples to demonstrate the uncertainty of ranking quantified by ranking probabilities, 95% confidence interval of SUCRA, and normalized entropy. We showed that as normalized entropy ranges from 0 to 1 and is independent of the number of treatments, it can be used to compare the uncertainty of treatment ranking within a network meta-analysis (NMA) and between different NMAs. Normalized entropy is an alternative tool for measuring the uncertainty of treatment ranking by improving the translation of results from NMAs to clinical practice and avoiding naïve interpretation of treatment ranking. We therefore recommend normalized entropy to be included in the presentation and interpretation of results from NMAs.

Technologies for Pharmacogenomics: A Review

The continuous development of new genotyping technologies requires awareness of their potential advantages and limitations concerning utility for pharmacogenomics (PGx). In this review, we provide an overview of technologies that can be applied in PGx research and clinical practice. Most commonly used are single nucleotide variant (SNV) panels which contain a pre-selected panel of genetic variants. SNV panels offer a short turnaround time and straightforward interpretation, making them suitable for clinical practice. However, they are limited in their ability to assess rare and structural variants. Next-generation sequencing (NGS) and long-read sequencing are promising technologies for the field of PGx research. Both NGS and long-read sequencing often provide more data and more options with regard to deciphering structural and rare variants compared to SNV panels—in particular, in regard to the number of variants that can be identified, as well as the option for haplotype phasing. Nonetheless, while useful for research, not all sequencing data can be applied to clinical practice yet. Ultimately, selecting the right technology is not a matter of fact but a matter of choosing the right technique for the right problem.

An estimator of the Opportunity for Selection that is independent of mean fitness

Variation among individuals in number of offspring (fitness, k) sets an upper limit to the evolutionary response to selection. This constraint is quantified by Crow’s Opportunity for Selection (I), which is the variance in relative fitness . Crow’s I has been widely used but remains controversial because it depends on mean offspring number in a sample . Here I used a generalized Wright-Fisher model that allows for unequal probabilities of producing offspring to evaluate behavior of Crow’s I and related indices under a wide range of sampling scenarios. Analytical and numerical results are congruent and show that rescaling the sample variance to its expected value at a fixed removes dependence of I on mean offspring number, but the result still depends on choice of . A new index is introduced, , which makes Î independent of sample without the need for variance rescaling. ΔI has a straightforward interpretation as the component of variance in relative fitness that exceeds that expected under a null model of random reproductive success. ΔI can be used to directly compare estimates of the Opportunity for Selection for samples from different studies, different sexes, and different life stages.