Do cortical midline variability and low frequency fluctuations mediate William James’ “Stream of Consciousness”? “Neurophenomenal Balance Hypothesis” of “Inner Time Consciousness”

William James famously characterized consciousness by ‘stream of consciousness’ which describes the temporal continuity and flow of the contents of consciousness in our ‘inner time consciousness’. More specifically he distinguished between “substantive parts”, the contents of consciousness, and “transitive parts”, the linkages between different contents. While much research has recently focused on the substantive parts, the neural mechanisms underlying the transitive parts and their characterization by the balance between ‘sensible continuity’ and ‘continuous change’ remain unclear. The aim of this paper is to develop so-called neuro-phenomenal hypothesis about specifically the transitive parts and their two phenomenal hallmark features, sensible continuity and continuous change in ‘inner time consciousness’. Based on recent findings, I hypothesize that the cortical midline structures and their high degree of variability and strong low frequency fluctuations play an essential role in mediating the phenomenal balance between sensible continuity and continuous change.     

Acquiring and processing verb argument structure: distributional learning in a miniature language

Adult knowledge of a language involves correctly balancing lexically-based and more language-general patterns. For example, verb argument structures may sometimes readily generalize to new verbs, yet with particular verbs may resist generalization. From the perspective of acquisition, this creates significant learnability problems, with some researchers claiming a crucial role for verb semantics in the determination of when generalization may and may not occur. Similarly, there has been debate regarding how verb-specific and more generalized constraints interact in sentence processing and on the role of semantics in this process. The current work explores these issues using artificial language learning. In three experiments using languages without semantic cues to verb distribution, we demonstrate that learners can acquire both verb-specific and verb-general patterns, based on distributional information in the linguistic input regarding each of the verbs as well as across the language as a whole. As with natural languages, these factors are shown to affect production, judgments and real-time processing. We demonstrate that learners apply a rational procedure in determining their usage of these different input statistics and conclude by suggesting that a Bayesian perspective on statistical learning may be an appropriate framework for capturing our findings.     

画概念图对高中二年级学生认知结构形成的影响

运用联想测试方法探索高二学生学习新陈代谢一章后的认知结构。运用相关系数值绘制出了学生的认知结构图。结果显示,运用概念图策略进行教学的实验班学生更容易形成认知结构。实验班学生所形成的认知结构更良好、更合理。     

An EM algorithm for fitting two-level structural equation models

Maximum likelihood is an important approach to analysis of two-level structural equation models. Different algorithms for this purpose have been available in the literature. In this paper, we present a new formulation of two-level structural equation models and develop an EM algorithm for fitting this formulation. This new formulation covers a variety of two-level structural equation models. As a result, the proposed EM algorithm is widely applicable in practice. A practical example illustrates the performance of the EM algorithm and the maximum likelihood statistic.We are thankful to the reviewers for their constructive comments that have led to significant improvement on the first version of this paper. Special thanks are due to the reviewer who suggested a comparison with the LISREL program in the saturated means model, and provided its setup and output. This work was supported by National Institute on Drug Abuse grants DA01070, DA00017, and a UNH 2002 Summer Faculty Fellowship.     

Power and Sample Size Calculations for Contrast Analysis in ANCOVA

Analysis of covariance (ANCOVA) is commonly used in behavioral and educational research to reduce the error variance and improve the power of analysis of variance by adjusting the covariate effects. For planning and evaluating randomized ANCOVA designs, a simple sample-size formula has been proposed to account for the variance deflation factor in the comparison of two treatment groups. The objective of this article is to highlight an overlooked and potential problem of the exiting approximation and to provide an alternative and exact solution of power and sample size assessments for testing treatment contrasts. Numerical investigations are conducted to reveal the relative performance of the two procedures as a reliable technique to accommodate the covariate features that make ANCOVA design particularly distinctive. The described approach has important advantages over the current method in general applicability, methodological justification, and overall accuracy. To enhance the practical usefulness, computer algorithms are presented to implement the recommended power calculations and sample-size determinations.     

The “Hero‐Protector Narrative”: Manufacturing Emotional Consent for the Use of Force

How do political leaders manufacture collective emotions to justify the use of force? This article introduces the “hero‐protector narrative” as a conceptual model to analyze how political leaders try to manufacture specific collective emotions to encourage their audience to perceive violence as the only morally acceptable course of action. In our model, we formalize a set of distinctive narrative structures (roles and sequences), which are combined to activate compassion and moral anger as well as identification with “heroic” behavior. Furthermore, we argue that the resonance of this narrative draws on values of hyper‐masculinity in patriarchal societies. As such this narrative is to be found across different types of actors (state/nonstate) and culturally diverse settings. To test our model, we use a computer‐assisted QDA approach. We compare systematically discourses produced by political actors legitimizing the use of force versus actors opposing the use of force. We find that discourses supporting the use of force, such as those produced by George W. Bush and Osama bin Laden in the context of the Iraq war, share the structural characteristics of the hero‐protector narrative. In this regard, they differ remarkably from violence‐opposing discourses, regardless of their cultural background.     

Cooperative strain accommodation over grains in martensitic transformation from Fe-Ni nanocrystalline austenite

This paper reports an investigation of martensitic transformation behaviour from austenite with various grain sizes ranging from 290 nm to 34 μm in an Fe–Ni alloy fabricated by electrodeposition and subsequent heat treatment. We confirmed that martensite morphology changed from lath to thin plate with decreasing the austenite grain size. Crystallographic orientation analysis revealed that the variants of thin plate martensite formed in the austenite with relatively coarse grains achieved self-accommodation of the transformation strain inside one austenite grain. In contrast, the transformation strain accompanying martensitic transformation from the ultrafine-grained or nanocrystalline austenite was not accommodated by the martensite variants formed in one austenite grain but accommodated cooperatively by those formed in the several adjacent austenite grains.     

Academic Cheating in Disliked Classes

Academic dishonesty occurs at alarming rates in higher education. In the present study, we examined predictors of academic cheating behaviors, and beliefs in the acceptability of cheating, in disliked courses at two large universities, using structural equation modeling. Perceived mastery and extrinsic goal structures were related to beliefs about cheating but not cheating behaviors. Beliefs in the acceptability of cheating were more likely to be endorsed in math and science courses. College students were more likely to cheat and to believe in the acceptability of cheating when they reported a high need for sensation.     

When does measurement error in covariates impact causal effect estimates? Analytic derivations of different scenarios and an empirical illustration

The average causal treatment effect (ATE) can be estimated from observational data based on covariate adjustment. Even if all confounding covariates are observed, they might not necessarily be reliably measured and may fail to obtain an unbiased ATE estimate. Instead of fallible covariates, the respective latent covariates can be used for covariate adjustment. But is it always necessary to use latent covariates? How well do analysis of covariance (ANCOVA) or propensity score (PS) methods estimate the ATE when latent covariates are used? We first analytically delineate the conditions under which latent instead of fallible covariates are necessary to obtain the ATE. Then we empirically examine the difference between ATE estimates when adjusting for fallible or latent covariates in an applied example. We discuss the issue of fallible covariates within a stochastic theory of causal effects and analyse data of a within-study comparison with recently developed ANCOVA and PS procedures that allow for latent covariates. We show that fallible covariates do not necessarily bias ATE estimates, but point out different scenarios in which adjusting for latent covariates is required. In our empirical application, we demonstrate how latent covariates can be incorporated for ATE estimation in ANCOVA and in PS analysis.     

Integrating covariates into circumplex structures: an extension procedure for Browne’s circular stochastic process model

Circumplex structures are elements of various psychological domains. Most work focuses on assessing the circular ordering of circumplex indicators and their relationships with covariates. In this article, an extension procedure for Browne’s circumplex model is presented. Our approach models the relationships among circumplex indicators and the relationships of covariates with a latent circumplex simultaneously without affecting the circumplex indicators’ positions on the circumplex. The approach builds upon Browne’s Fourier series parameterization of a correlation function, which is used to model the latent circumplex correlation structure. It extends the shape of the correlation function to the profile of each covariate’s correlations with the circumplex. The model is specified in the framework of structural equation modeling, thereby making it possible to test various hypotheses. Procedures are presented for deriving interval estimates for the parameters that relate the covariates to the circumplex. The model is compared to other approaches for assessing the relationships of a circumplex with covariates. The results of the exemplary applications and a simulation study were in favor of the suggested model. The approach is furthermore illustrated with a real-data example, focusing on the relationships between the interpersonal circumplex and the rivalry and admiration aspects of narcissism.