A framework for leveraging multi-rater data in brain decoding analysis: Prediction of evaluation drawn from population data using sparse probit regression

Introduction: Using stimuli (e.g., images, videos, products) labeled by a number of raters has recently become common in brain decoding analysis, where subjective emotion/impression for stimuli felt by the population is predicted from brain responses. However, there remains no established method for constructing a decoder using such multi-rater labels. In previous studies, the variability across multiple raters was assumed to reflect noise, and the answers for a binary judgment were averaged across raters. Then, the average scores (i.e., empirical probabilities) for individual stimuli were predicted using standard regression methods. While this procedure is a simple and popular approach, it is not appropriate because most of these regression methods ignore the fact that probability is the variable to be predicted. To address this in an appropriate manner, we present a new framework in this study.Methods: Here, we assume that individual answers for a binary judgment about a stimulus follow a Bernoulli distribution. We then predicted the probability of positive answers from the human functional magnetic resonance imaging (fMRI) response to the stimulus using probit regression. We also introduced sparse regularization into probit regression (sparse probit regression) to prevent overfitting.Results: In both simulation and real fMRI data analysis, sparse probit regression more accurately predicted the probabilities of positive answers for individual stimuli than probit regression without sparse regularization, indicating that sparseness results in better decoding performance. Sparse probit regression also outperformed linear regression using the same type of sparse regularization, reflecting the advantage of our appropriate treatment of probability.Discussion & Conclusion: Our results suggest that our framework using sparse probit regression provides an effective method for the population prediction of emotion/impression assessment based on brain activity.第5回ヒト脳イメージング研究

A Novel Methodology to Evaluate Health Impacts Caused by VOC Exposures Using Real-Time VOC and Holter Monitors

While various volatile organic compounds (VOCs) are known to show neurotoxic effects, the detailed mechanisms of the action of VOCs on the autonomic nervous system are not fully understood, partially because objective and quantitative measures to indicate neural abnormalities are still under development. Nevertheless, heart rate variability (HRV) has been recently proposed as an indicative measure of the autonomic effects. In this study, we used HRV as an indicative measure of the autonomic effrects to relate their values to the personal concentrations of VOCs measured by a real-time VOC monitor. The measurements were conducted for 24 hours on seven healthy subjects under usual daily life conditions. The results showed HF powers were significantly decreased for six subjects when the changes of total volatile organic compound (TVOC) concentrations were large, indicating a suppression of parasympathetic nervous activity induced by the exposure to VOCs. The present study indicated these real-time monitoring was useful to characterize the trends of VOC exposures and their effects on autonomic nervous system

TTC26/DYF13 is an intraflagellar transport protein required for transport of motility-related proteins into flagella

Cilia/flagella are assembled and maintained by the process of intraflagellar transport (IFT), a highly conserved mechanism involving more than 20 IFT proteins. However, the functions of individual IFT proteins are mostly unclear. To help address this issue, we focused on a putative IFT protein TTC26/DYF13. Using live imaging and biochemical approaches we show that TTC26/DYF13 is an IFT complex B protein in mammalian cells and Chlamydomonas reinhardtii. Knockdown of TTC26/DYF13 in zebrafish embryos or mutation of TTC26/DYF13 in C. reinhardtii, produced short cilia with abnormal motility. Surprisingly, IFT particle assembly and speed were normal in dyf13 mutant flagella, unlike in other IFT complex B mutants. Proteomic and biochemical analyses indicated a particular set of proteins involved in motility was specifically depleted in the dyf13 mutant. These results support the concept that different IFT proteins are responsible for different cargo subsets, providing a possible explanation for the complexity of the IFT machinery. DOI: http://dx.doi.org/10.7554/eLife.01566.00

Fundamental electron-transfer and proton-coupled electron-transfer properties of Ru(iv)-oxo complexes

Isolation and characterisation of Ru-IV(O) complexes were accomplished to investigate their fundamental electron transfer (ET) and proton-coupled ET (PCET) properties. Reorganisation energies (lambda) in electron transfer (ET) and proton-coupled ET (PCET) from electron donors to the isolated Ru-IV(O) complexes have been determined for the first time to be in the range of 1.70-1.88 eV (ET) and 1.20-1.26 eV (PCET). It was suggested that the reduction of the lambda values of PCET in comparison with those of ET should be due to the smaller structural change in PCET than that in ET on the basis of DFT calculations on 1 and 1e(-)-reduced 1 in the absence and presence of TFA, respectively. In addition, the smaller lambda values for the Ru-IV(O) complexes than those reported for Fe-IV(O) and Mn-IV(O) complexes should be due to the lack of participation of d(sigma) orbitals in the ET and PCET reactions. This is the first example to evaluate fundamental ET and PCET properties of Ru-IV(O) complexes leading to further understanding of their reactivity in oxidation reactions

Small Molecules with Similar Structures Exhibit Agonist, Neutral Antagonist or Inverse Agonist Activity toward Angiotensin II Type 1 Receptor

Small differences in the chemical structures of ligands can be responsible for agonism, neutral antagonism or inverse agonism toward a G-protein-coupled receptor (GPCR). Although each ligand may stabilize the receptor conformation in a different way, little is known about the precise conformational differences. We synthesized the angiotensin II type 1 receptor blocker (ARB) olmesartan, R239470 and R794847, which induced inverse agonism, antagonism and agonism, respectively, and then investigated the ligand-specific changes in the receptor conformation with respect to stabilization around transmembrane (TM)3. The results of substituted cysteine accessibility mapping studies support the novel concept that ligand-induced changes in the conformation of TM3 play a role in stabilizing GPCR. Although the agonist-, neutral antagonist and inverse agonist-binding sites in the AT1 receptor are similar, each ligand induced specific conformational changes in TM3. In addition, all of the experimental data were obtained with functional receptors in a native membrane environment (in situ)

Emergence of a thread-like pattern with charged phospholipids on an oil∕water interface.

The spontaneous formation of a thread-like pattern with negatively charged lipids on an oil∕water interface is reported. An analysis of the time-dependent change at the interface observed by fluorescence microscopy revealed that the thread-like pattern is generated through a two-step mechanism. First, inverted lipid micelles in the bulk-oil phase gradually diffuse onto the oil∕water interface. Next, the micelles are adsorbed on the interface and self-assemble to form the thread-like pattern. The essential characteristics of this pattern formation are theoretically reproduced by a simple Monte Carlo simulation that takes into account the kinetics in the coalescence of charged micelles on a 2D interface