Development of a variational scheme for model inversion of multi-area model of brain. Part II: VBEM method

In Part I and Part II of these two companion papers (henceforth called Part I and Part II), we develop and evaluate a variational Bayesian expectation maximization (VBEM) method for model inversion of our multi-area extended neural mass model (MEN). In this paper, we develop the VBEM method to estimate posterior distributions of parameters of MEN. We choose suitable prior distributions for the model parameters in order to use properties of a conjugate-exponential model in implementing VBEM. Consequently, VBEM leads to analytically tractable forms. The proposed VBEM algorithm starts with initialization and consists of repeated iterations of a variational Bayesian expectation step (VB E-step) and a variational Bayesian maximization step (VB M-step). Posterior distributions of the model parameters are updated in the VB M-step. Distribution of the hidden state is updated in the VB E-step. We develop a variational extended Kalman smoother (VEKS) to infer the distribution of the hidden state in the VB E-step and derive the forward and backward passes of VEKS, analogous to the Kalman smoother. In Part I, we evaluate and validate the VBEM method using simulation studies.     

Timing in reward and decision processes

Sensitivity to time, including the time of reward, guides the behaviour of all organisms. Recent research suggests that all major reward structures of the brain process the time of reward occurrence, including midbrain dopamine neurons, striatum, frontal cortex and amygdala. Neuronal reward responses in dopamine neurons, striatum and frontal cortex show temporal discounting of reward value. The prediction error signal of dopamine neurons includes the predicted time of rewards. Neurons in the striatum, frontal cortex and amygdala show responses to reward delivery and activities anticipating rewards that are sensitive to the predicted time of reward and the instantaneous reward probability. Together these data suggest that internal timing processes have several well characterized effects on neuronal reward processing.     

Antidepressants versus placebo in major depression: an overview

Although the early antidepressant trials which included severely ill and hospitalized patients showed substantial drug‐placebo differences, these robust differences have not held up in the trials of the past couple of decades, whether sponsored by pharmaceutical companies or non‐profit agencies. This narrowing of the drug‐placebo difference has been attributed to a number of changes in the conduct of clinical trials. First, the advent of DSM‐III and the broadening of the definition of major depression have led to the inclusion of mildly to moderately ill patients into antidepressant trials. These patients may experience a smaller magnitude of antidepressant‐placebo differences. Second, drug development regulators, such as the U.S. Food and Drug Administration and the European Medicines Agency, have had a significant, albeit underappreciated, role in determining how modern antidepressant clinical trials are designed and conducted. Their concerns about possible false positive results have led to trial designs that are poor, difficult to conduct, and complicated to analyze. Attempts at better design and patient selection for antidepressant trials have not yielded the expected results. As of now, antidepressant clinical trials have an effect size of 0.30, which, although similar to the effects of treatments for many other chronic illnesses, such as hypertension, asthma and diabetes, is less than impressive.     

A quantitative approach for polymerase chain reactions based on a hidden Markov model

Polymerase chain reaction (PCR) is a major DNA amplification technology from molecular biology. The quantitative analysis of PCR aims at determining the initial amount of the DNA molecules from the observation of typically several PCR amplifications curves. The mainstream observation scheme of the DNA amplification during PCR involves fluorescence intensity measurements. Under the classical assumption that the measured fluorescence intensity is proportional to the amount of present DNA molecules, and under the assumption that these measurements are corrupted by an additive Gaussian noise, we analyze a single amplification curve using a hidden Markov model(HMM). The unknown parameters of the HMM may be separated into two parts. On the one hand, the parameters from the amplification process are the initial number of the DNA molecules and the replication efficiency, which is the probability of one molecule to be duplicated. On the other hand, the parameters from the observational scheme are the scale parameter allowing to convert the fluorescence intensity into the number of DNA molecules and the mean and variance characterizing the Gaussian noise. We use the maximum likelihood estimation procedure to infer the unknown parameters of the model from the exponential phase of a single amplification curve, the main parameter of interest for quantitative PCR being the initial amount of the DNA molecules. An illustrative example is provided. This research was financed by the Swedish foundation for Strategic Research through the Gothenburg Mathematical Modelling Centre.     

Complexity of a complex trait locus: HP, HPR, haemoglobin and cholesterol

HP and HPR are related and contiguous genes in strong linkage disequilibrium (LD), encoding haptoglobin and haptoglobin-related protein. These bind and chaperone free Hb for recycling, protecting against oxidation. A copy number variation (CNV) within HP (Hp1/Hp2) results in different possible haptoglobin complexes which have differing properties. HPR rs2000999 (G/A), identified in meta-GWAS, influences total cholesterol (TC) and LDL-cholesterol (LDL-C). We examined the relationship between HP CNV, HPR rs2000999, Hb, red cell count (RCC), LDL-C and TC in the British Women's Heart and Health Study (n=2779 for samples having CNV, rs2000999, and phenotypes). Analysing single markers by linear regression, rs2000999 was associated with LDL-C (β=0.040 mmol/L, p=0.023), TC (β=-0.040 mmol/L, p=0.019), Hb (β=-0.044 g/dL, p=0.028) and borderline with RCC (β=-0.032 × 10(12)/L, p=0.066). Analysis of CNV by linear regression revealed an association with Hb (Hp1 vs Hp2, β=0.057 g/dL, p=0.004), RCC (β=0.045 × 10(12)/L, p=0.014), and showed a trend with LDL-C and TC. There were 3 principal haplotypes (Hp1-G 36%; Hp2-G 45%; Hp2-A 18%). Haplotype comparisons showed that LDL-C and TC associations were from rs2000999; Hb and RCC associations derived largely from the CNV. Distinct genotype-phenotype effects are evident at the genetic epidemiological level once LD has been analysed, perhaps reflecting HP-HPR functional biology and evolutionary history. The derived Hp2 allele of the HP gene has apparently been subject to malaria-driven positive selection. Haptoglobin-related protein binds Hb and apolipoprotein-L, i.e. linking HPR to the cholesterol system; and the HPR/apo-L complex is specifically trypanolytic. Our analysis illustrates the complex interplay between functions and haplotypes of adjacent genes, environmental context and natural selection, and offers insights into potential use of haptoglobin or haptoglobin-related protein as therapeutic agents.     

《广西植物》创办十八年:回顾与展望

科技期刊是传播科技信息与知识的载体,是外界观察和了解科技进步的重要窗口,是科技文献的宝库,是百家争鸣的论坛,是发现和培育人才的大学,是开展学术交流的工具,是评价作者学术水平的依据,也是实施国家科技政策、法规的具体体现。《广西植物》是植物学综合性学术期刊,创办１８年来,始终体现了科技期刊的这一共性。至今,已出版发行了１８卷７２期（含试刊４期）,刊出研究报告及各种论文１１１５篇,发表植物新种（含新变种、新变型）５３４种,与世界上１５个国家３６个研究单位以及国内２９个省（自治区）６０多个科研机构、大中专院校等进行了交换。为发现人才、培养人才作出了应有的贡献。