The Discriminating Properties of an Optoelectronic Movement Analysis Method in Patients With Parkinsonism

Several partly overlapping diseases have Parkinsonism as a symptom and tools that may differentiate between these disorders would be helpful. The authors evaluated the discriminating properties of the objective automated posturo-locomotor-manual (PLM) L-DOPA test in regard to health, and the movement disorders Parkinson's disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). A PLM test–retest procedure was performed in healthy controls (n = 37) and results were compared with PLM L-DOPA tests performed by 132 patients with Parkinsonism in intermediate to advanced stages (56 PD, 53 MSA, 23 PSP). The movement time (MT) for the standardized movement and its different components was measured. The discriminating abilities of individual, or combinations of, test variables were determined by forward stepwise multiple logistic regression and evaluated with receiver-operating characteristic (ROC) analysis. Each PLM variable separated healthy persons from patients with Parkinsonism before administration of L-DOPA (area under the curve (AUC) = 0.94–0.99, p <.001 for any separate variable). A combination of (MT_off – MT_on)/MT_off and MT_on had the highest ability to separate patients with PD from patients with atypical Parkinsonism (area under the curve = 0.91, p <.001). The PLM test discriminates between healthy controls and patients with Parkinsonism, and between patients with Parkinson's disease and patients with atypical Parkinsonism.

[Supplementary material is available for this article. Go to the publisher's online edition of Journal of Motor Behavior for the following free supplemental resource: supplementary data.]     

Heterogeneity in generalized reinforcement learning and its relation to cognitive ability

In this paper, we study the connections between working memory capacity (WMC) and learning in the context of economic guessing games. We apply a generalized version of reinforcement learning, popularly known as the experience-weighted attraction (EWA) learning model, which has a connection to specific cognitive constructs, such as memory decay, the depreciation of past experience, counterfactual thinking, and choice intensity. Through the estimates of the model, we examine behavioral differences among individuals due to different levels of WMC. In accordance with ‘Miller’s magic number’, which is the constraint of working memory capacity, we consider two different sizes (granularities) of strategy space: one is larger (finer) and one is smaller (coarser). We find that constraining the EWA models by using levels (granules) within the limits of working memory allows for a better characterization of the data based on individual differences in WMC. Using this level-reinforcement version of EWA learning, also referred to as the EWA rule learning model, we find that working memory capacity can significantly affect learning behavior. Our likelihood ratio test rejects the null that subjects with high WMC and subjects with low WMC follow the same EWA learning model. In addition, the parameter corresponding to ‘counterfactual thinking ability’ is found to be reduced when working memory capacity is low.     

A pilot randomized trial of metacognitive therapy vs applied relaxation in the treatment of adults with generalized anxiety disorder

Metacognitive Therapy (MCT) and Applied Relaxation (AR) were compared in a pilot treatment trial of generalized anxiety disorder (GAD). Twenty outpatients meeting criteria for DSM-IV-TR GAD were assessed before treatment, after treatment and at 6 m and 12 m follow-up. The patients were randomized and treated individually for 8-12 weekly sessions. There was no drop-out from MCT and 10% at 6 m follow-up from AR. At post-treatment and at both follow-up points MCT was superior to AR. Standardized recovery rates for MCT at post-treatment were 80% on measures of worry and trait-anxiety compared with 10% following AR. At 6 m follow-up recovery rates for MCT were 70% on both measures compared with 10% and 20% for AR. At 12 m follow-up recovery rates for MCT were 80% (worry) and 60% (trait-anxiety) compared with 10% and 20% following AR. The recovery rates for MCT are similar to those obtained in an earlier uncontrolled trial (Wells & King, 2006). The effect sizes and standardized recovery rates for MCT suggest that it is a highly effective treatment.     

Emotion Regulation Therapy: An Integrative Approach to Treatment-Resistant Anxiety Disorders

Cognitive-behavioral, psychodynamic, and experiential approaches have historically been characterized by differing definitions of emotions and beliefs concerning their role in psychopathological process and treatment. However, given recent advances in the basic psychological sciences of emotion and emotion regulation, theoretical orientations are converging on similar viewpoints as to the functional role of emotions in conceptualizing and treating of a variety of disorders. One such area where emotions and their regulation may play a significant role is in chronic, complex, and treatment-resistant forms of anxiety disorders such as generalized anxiety disorder (GAD). A review of the historical approaches to emotions in the major theoretical orientations is presented. Following this, a model of emotion disruption and dysregulation is presented as it relates to anxiety disorders and GAD, in particular. Finally, a new treatment for GAD, emotion regulation therapy, aimed at ameliorating dysfunctional affective processes, is described.     

Exemplars, prototypes, similarities, and rules in category representation: an example of hierarchical bayesian analysis

This article demonstrates the potential of using hierarchical Bayesian methods to relate models and data in the cognitive sciences. This is done using a worked example that considers an existing model of category representation, the Varying Abstraction Model (VAM), which attempts to infer the representations people use from their behavior in category learning tasks. The VAM allows for a wide variety of category representations to be inferred, but this article shows how a hierarchical Bayesian analysis can provide a unifying explanation of the representational possibilities using 2 parameters. One parameter controls the emphasis on abstraction in category representations, and the other controls the emphasis on similarity. Using 30 previously published data sets, this work shows how inferences about these parameters, and about the category representations they generate, can be used to evaluate data in terms of the ongoing exemplar versus prototype and similarity versus rules debates in the literature. Using this concrete example, this article emphasizes the advantages of hierarchical Bayesian models in converting model selection problems to parameter estimation problems, and providing one way of specifying theoretically based priors for competing models.     

Generalized Pexider equation on a restricted domain

Let X be a normed space and D be a nonempty, open and connected subset of X×X. Inspired by a problem of J. Aczél, we study the functional equation

     

Quine on Quantification and Existence

Quine's justly famous paper "On What There Is" introduced a criterion of ontological commitment which has been almost universally accepted by analytic philosophers ever since.In this paper I try to unpack some of the substantive and controversial philosophical commitments that are presupposed by this criterion.The aim is not to show that the criterion is incorrect,but merely that it is not as obvious as it is taken to be by many,and that we might have reasons to explore alternative ways of thinking about ontological commitments.     

The aggression test as a possible taxonomic tool in the Formica rufa group

The intra- and interspecific aggressive behavior of Formica polyctena, a species of the Formica rufa group, was analyzed and quantified both in the laboratory and in the field. This behavior was used as a potential taxonomic tool for gaining a better understanding of the phyletic relationships among the species within the group. No overt aggression was recorded toward members of the same species. To examine interspecific relationships, F. polyctena was first confronted with F. cunicularia, to ascertain its aggressiveness toward a distantly related species. All such encounters led immediately to overt and prolonged attacks with virtually no initial mutual inspection. This suggests that recognition of strangeness of the unrelated species is almost immediate in F. polyctena, as previously observed in F. lugubris and F. rufa toward the same antagonist. Subsequently, F. polyctena was contrasted with F. lugubris and F. rufa (also belonging to the F. rufa group) in order to compare these related species. Fierce attacks accompanied by all the elements of conflict behavior were observed in all encounters. Moreover, the degree of aggression in the field was higher than in laboratory-paired ants, possibly because of a territorial effect. These data and our previous and similar research indicate that the relationships between F. lugubris and F. rufa are closer than between these two species and F. polyctena. In considering different viewpoints on this problem, the validity of the aggression test is discussed and the opportunity to compare levels of aggressiveness among strictly sympatric samples of red wood ant species gathered from the same ecological environment are considered.     

Nonmetric individual differences multidimensional scaling: An alternating least squares method with optimal scaling features

A new procedure is discussed which fits either the weighted or simple Euclidian model to data that may (a) be defined at either the nominal, ordinal, interval or ratio levels of measurement; (b) have missing observations; (c) be symmetric or asymmetric; (d) be conditional or unconditional; (e) be replicated or unreplicated; and (f) be continuous or discrete. Various special cases of the procedure include the most commonly used individual differences multidimensional scaling models, the familiar nonmetric multidimensional scaling model, and several other previously undiscussed variants.The procedure optimizes the fit of the model directly to the data (not to scalar products determined from the data) by an alternating least squares procedure which is convergent, very quick, and relatively free from local minimum problems.The procedure is evaluated via both Monte Carlo and empirical data. It is found to be robust in the face of measurement error, capable of recovering the true underlying configuration in the Monte Carlo situation, and capable of obtaining structures equivalent to those obtained by other less general procedures in the empirical situation.This project was supported in part by Research Grant No. MH10006 and Research Grant No. MH26504, awarded by the National Institute of Mental Health, DHEW. We wish to thank Robert F. Baker, J. Douglas Carroll, Joseph Kruskal, and Amnon Rapoport for comments on an earlier draft of this paper. Portions of the research reported here were presented to the spring meeting of the Psychometric Society, 1975. ALSCAL, a program to perform the computations discussed in this paper, may be obtained from any of the authors.Jan de Leeuw is currently at Datatheorie, Central Rekeninstituut, Wassenaarseweg 80, Leiden, The Netherlands. Yoshio Takane can be reached at the Department of Psychology, University of Tokyo, Tokyo, Japan.     

Three notes on ALSCAL

It is reported that (1) a new coordinate estimation routine is superior to that originally proposed for ALSCAL; (2) an oversight in the interval measurement level case has been found and corrected; and (3) a new initial configuration routine is superior to the original.