Variation in verbal fluency: A latent variable analysis of clustering,switching, and overall performance

Verbal fluency tasks have long been used to assess and estimate group and individual differences in executive functioning in both cognitive and neuropsychological research domains. Despite their ubiquity, however, the specific component processes important for success in these tasks have remained elusive. The current work sought to reveal these various components and their respective roles in determining performance in fluency tasks using latent variable analysis. Two types of verbal fluency (semantic and letter) were compared along with several cognitive constructs of interest (working memory capacity, inhibition, vocabulary size, and processing speed) in order to determine which constructs are necessary for performance in these tasks. The results are discussed within the context of a two-stage cyclical search process in which participants first search for higher order categories and then search for specific items within these categories.     

Differential impacts of age of acquisition on letter and semantic fluency in Alzheimer's disease patients and healthy older adults

The degree to which the typical age of acquisition (AoA) of words and word frequency have separable influences on verbal production tasks has been strongly debated. To examine the overlap between these factors in verbal fluency tasks, the performance of Alzheimer's disease (AD) patients (N?=?34) and normal elderly controls (N?=?36) was compared on semantic (e.g., vegetables) and letter (e.g., words that begin with F) fluency tasks. These comparisons revealed that words generated for the semantic fluency task had an earlier AoA while words generated for the letter fluency task had a higher word frequency. Differences in AoA between AD patients and controls were larger for semantic than letter fluency. These results suggest that AoA has an effect on verbal production that is independent of word frequency and that AoA has a semantic locus.     

Visual working memory is enhanced by mixed strategy use and semantic coding

Visual working memory is enhanced by processes related to verbalisation. However, the mechanism underlying this enhancement is unclear. Experiment 1 investigated the potential contribution of the phonological loop of working memory, by assessing the effects of articulatory suppression on two versions of the Visual Patterns Test—one low and one high in availability of verbal coding. The lack of interaction suggested that the phonological loop is not responsible; however, active use of combined verbal and visual strategies, as well as activated semantic knowledge, both appear to be related to increased capacity. Experiment 2 assessed the role of central executive resources. Because central executive suppression removed the benefit of the high verbal coding task version, central executive resources, assumed to relate to the temporary maintenance of multimodal codes in the episodic buffer, appear to underlie the benefit associated with verbalisation.     

Blood flow velocity changes in anterior cerebral arteries during cognitive tasks performance

Objective

Transcranial Doppler sonography (TCD) enables monitoring of blood flow velocities (BFVs) in basal cerebral arteries during different cognitive tasks performance with great temporal resolution. So far, BFVs changes during mental activity were monitored primarily in middle cerebral arteries (MCAs) and little is known about these changes in anterior cerebral arteries (ACAs).

Aim

To determine the effect of different cognitive tasks performance on BFV changes and hemispheric dominance in ACAs and to assess the most suitable activation test for monitoring of BFV changes in ACAs.

Methods

Fourteen right-handed, healthy subjects aged 20–26 were included in the study. BFVs in both ACAs were recorded simultaneously during performance of cognitive tasks designed to activate frontal lobes: phonemic verbal fluency test (pVFT), Stroop tests and Trail Making Tests (TMTs).

Results

A statistically significant BFV increase was recorded in both ACAs during performance of all cognitive tasks. Statistically significant right ACA dominance was found during performance of pVFT and TMTB. The most significant BFV increase was obtained during performance of TMTB.

Conclusion

Our result addressed cognitive tests with great activation potential for monitoring of ACAs that might be used in distinguishing of healthy individuals and patients with neurovascular or neurodegenerative diseases.     

A Thurstonian Analysis of Preference Change

This paper presents a Thurstonian model for the analysis of preference change. Preferences are expressed in the form of rankings, possibly with ties. A vector-autoregression framework is used to investigate relationships between past and current rankings. It is shown that this approach yields a parsimonious and easily interpretable representation of individual preference differences in time-dependent ranking data. A detailed analysis of the 1992 National Election Study illustrates the proposed approach.     

Identification and Testing of Modes in Beliefs

Characterizing diversity in beliefs is of paramount importance in empirical research on human behavior. In game theory, the focus is on the hypothesis formation. We present a data set with ideal properties for characterizing such diversity. The data consist of hypotheses on the empirical distribution of opponent choices. Using nonparametric techniques, we identify modes in the data corresponding to subpopulations of behavioral types and find the statistical significance of these modes in the underlying population distribution.     

大学生实时距、空时距估计的比较研究

本研究采用2(空时距、实时距)×8(1秒～8秒)的实验设计,以224名大学生为被试,考察了不同类型、不同长度的时距估计特点,结果发现;(1)时距类型在时距估计中存在主效应,在本实验中,1秒～8秒条件下实时距估计比空时距准确;(2)时距长度在时距估计中存在主效应,时距估计所产生的误差随时距长度的增加而增大;(3)时距类型与时距长度之间存在交互作用,对实时距、空时距估计进行曲线估计及预测,发现两类时距估计呈现动态特征,1845052秒之前实时距估计比空时距准确,之后空时距估计比实时距准确,两类时距估计曲线的变化速度也呈交替上升趋势。     

个人目标相关性对非临床抑郁者未来想象的影响

通过两个实验考查了非临床抑郁者未来想象的异常是否受到个人目标相关性的调节。实验1采用未来想象任务, 实验2采用可能性评估范式, 两个实验一致发现, 抑郁倾向者想象未来积极事件的异常, 受到了与个人目标相关性的调节：相对于非抑郁倾向者, 抑郁倾向者对未来与个人目标相关的积极事件的预期减弱, 而对未来与个人目标无关的积极事件的预期则没有表现出异常; 同时还发现, 抑郁倾向者表现出了对未来消极预期的普遍增强, 不受与个人目标相关性的影响。     

Efficient nonparametric approaches for estimating the operating characteristics of discrete item responses

Rationale and the actual procedures of two nonparametric approaches, called Bivariate P.D.F. Approach and Conditional P.D.F. Approach, for estimating the operating characteristic of a discrete item response, or the conditional probability, given latent trait, that the examinee's response be that specific response, are introduced and discussed. These methods are featured by the facts that: (a) estimation is made without assuming any mathematical forms, and (b) it is based upon a relatively small sample of several hundred to a few thousand examinees.Some examples of the results obtained by the Simple Sum Procedure and the Differential Weight Procedure of the Conditional P.D.F. Approach are given, using simulated data. The usefulness of these nonparametric methods is also discussed.This research was mostly supported by the Office of Naval Research (N00014-77-C-0360, N00014-81-C-0569, N00014-87-K-0320, N00014-90-J-1456).     

Dealing with Multiple Solutions in Structural Vector Autoregressive Models

Structural vector autoregressive models (VARs) hold great potential for psychological science, particularly for time series data analysis. They capture the magnitude, direction of influence, and temporal (lagged and contemporaneous) nature of relations among variables. Unified structural equation modeling (uSEM) is an optimal structural VAR instantiation, according to large-scale simulation studies, and it is implemented within an SEM framework. However, little is known about the uniqueness of uSEM results. Thus, the goal of this study was to investigate whether multiple solutions result from uSEM analysis and, if so, to demonstrate ways to select an optimal solution. This was accomplished with two simulated data sets, an empirical data set concerning children's dyadic play, and modifications to the group iterative multiple model estimation (GIMME) program, which implements uSEMs with group- and individual-level relations in a data-driven manner. Results revealed multiple solutions when there were large contemporaneous relations among variables. Results also verified several ways to select the correct solution when the complete solution set was generated, such as the use of cross-validation, maximum standardized residuals, and information criteria. This work has immediate and direct implications for the analysis of time series data and for the inferences drawn from those data concerning human behavior.