Patterns of neuropsychological performance in multiple system atrophy compared to sporadic and hereditary olivopontocerebellar atrophy

Although neuropsychological symptoms are associated with multiple system atrophy (MSA), sporadic olivopontocerebellar atrophy (sOPCA), and dominantly inherited olivopontocerebellar atrophy (dOPCA), the differences between these groups have not been explored. We compared 28 MSA patients on psychiatric rating scales and neuropsychological measures to 67 sOPCA patients, 42 dOPCA patients, and 30 normal controls. Patients with dOPCA, sOPCA, and MSA all exhibited significant deficits on motor-related tasks, as well as relatively mild deficits in cognitive functioning. Patients with MSA had greater neuropsychological dysfunction, particularly in memory and other "higher order" cognitive processes, than patients with either sOPCA or dOPCA.     

On the factivity of implicit intersubjective knowledge

The concept of knowledge can be modelled in epistemic modal logic and, if modelled by using a standard modal operator, it is subject to the problem of logical omniscience. The classical solution to this problem is to distinguish between implicit and explicit knowledge and to construe the knowledge operator as capturing the concept of implicit knowledge. In addition, since a proposition is said to be implicitly known just in case it is derivable from the set of propositions that are explicitly known by using a certain set of logical rules, the concept of implicit knowledge is definable on the basis of the concept of explicit knowledge. In any case, both implicit and explicit knowledge are typically characterized as factive, i.e. such that it is always the case that what is known is also true. The aim of the present paper is twofold: first, we will develop a dynamic system of explicit intersubjective knowledge that allows us to introduce the operator of implicit knowledge by definition; secondly, we will show that it is not possible to hold together the following two theses: (1) the concept of implicit knowledge is definable along the lines indicated above and (2) the concept of implicit knowledge is factive.     

Outline of a general model of measurement

Measurement is a process aimed at acquiring and codifying information about properties of empirical entities. In this paper we provide an interpretation of such a process comparing it with what is nowadays considered the standard measurement theory, i.e., representational theory of measurement. It is maintained here that this theory has its own merits but it is incomplete and too abstract, its main weakness being the scant attention reserved to the empirical side of measurement, i.e., to measurement systems and to the ways in which the interactions of such systems with the entities under measurement provide a structure to an empirical domain. In particular it is claimed that (1) it is on the ground of the interaction with a measurement system that a partition can be induced on the domain of entities under measurement and that relations among such entities can be established, and that (2) it is the usage of measurement systems that guarantees a degree of objectivity and intersubjectivity to measurement results. As modeled in this paper, measurement systems link the abstract theory of measuring, as developed in representational terms, and the practice of measuring, as coded in standard documents such as the International Vocabulary of Metrology.     

Component Models for Fuzzy Data

The fuzzy perspective in statistical analysis is first illustrated with reference to the “Informational Paradigm” allowing us to deal with different types of uncertainties related to the various informational ingredients (data, model, assumptions). The fuzzy empirical data are then introduced, referring to J LR fuzzy variables as observed on I observation units. Each observation is characterized by its center and its left and right spreads (LR₁ fuzzy number) or by its left and right “centers” and its left and right spreads (LR₂ fuzzy number). Two types of component models for LR₁ and LR₂ fuzzy data are proposed. The estimation of the parameters of these models is based on a Least Squares approach, exploiting an appropriately introduced distance measure for fuzzy data. A simulation study is carried out in order to assess the efficacy of the suggested models as compared with traditional Principal Component Analysis on the centers and with existing methods for fuzzy and interval valued data. An application to real fuzzy data is finally performed. We would like to express our gratitude to the Editor, the Associate Editor, and the Referees whose comments and suggestions improved significantly the quality of the paper.     

Computerized cognitive training during physical inactivity improves executive functioning in older adults

The hippocampus is closely tied to spatial navigation, a central component in cognitive functioning, and critically involved in age-associated cognitive decline and dementia. This study evaluated a novel, cognitive computerized spatial navigation training (CSNT) program targeting the hippocampus, with expectation of mitigating possible cognitive decline with bed rest (BR). During a 14-day BR study with 16 healthy, older men (mean age = 60 ± 3, range = 55–65 years), half received CSNT for 12 days in 50-min sessions and half were controls (watching documentaries). This design uniquely controlled diet, sleep, and other personal and environmental activities. Although there were no cognitive declines in controls post-BR, CSNT participants demonstrated significant increases in executive/attention ability and processing speed, and continued spatial navigation testing showed improvement to 400 days post-BR. This intervention may prove useful to mitigate cognitive declines known to occur in long periods of immobilization and could have broader implications in protecting against age-related cognitive decline.     

Constrained Candecomp/Parafac via the Lasso

The Candecomp/Parafac (CP) model is a well-known tool for summarizing a three-way array by extracting a limited number of components. Unfortunately, in some cases, the model suffers from the so-called degeneracy, that is a solution with diverging and uninterpretable components. To avoid degeneracy, orthogonality constraints are usually applied to one of the component matrices. This solves the problem only from a technical point of view because the existence of orthogonal components underlying the data is not guaranteed. For this purpose, we consider some variants of the CP model where the orthogonality constraints are relaxed either by constraining only a pair, or a subset, of components or by stimulating the CP solution to be possibly orthogonal. We theoretically clarify that only the latter approach, based on the least absolute shrinkage and selection operator and named the CP-Lasso, is helpful in solving the degeneracy problem. The results of the application of CP-Lasso on simulated and real life data show its effectiveness.     

A New Semantics for Systems of Logic of Essence

The purpose of the present paper is to provide a way of understanding systems of logic of essence by introducing a new semantic framework for them. Three central results are achieved: first, the now standard Fitting semantics for the propositional logic of evidence is adapted in order to provide a new, simplified semantics for the propositional logic of essence; secondly, we show how it is possible to construe the concept of necessary truth explicitly by using the concept of essential truth; finally, Fitting semantics is adapted in order to present a simplified semantics for the quantified logic of essence.     

Bootstrap confidence intervals for principal covariates regression

Principal covariate regression (PCOVR) is a method for regressing a set of criterion variables with respect to a set of predictor variables when the latter are many in number and/or collinear. This is done by extracting a limited number of components that simultaneously synthesize the predictor variables and predict the criterion ones. So far, no procedure has been offered for estimating statistical uncertainties of the obtained PCOVR parameter estimates. The present paper shows how this goal can be achieved, conditionally on the model specification, by means of the bootstrap approach. Four strategies for estimating bootstrap confidence intervals are derived and their statistical behaviour in terms of coverage is assessed by means of a simulation experiment. Such strategies are distinguished by the use of the varimax and quartimin procedures and by the use of Procrustes rotations of bootstrap solutions towards the sample solution. In general, the four strategies showed appropriate statistical behaviour, with coverage tending to the desired level for increasing sample sizes. The main exception involved strategies based on the quartimin procedure in cases characterized by complex underlying structures of the components. The appropriateness of the statistical behaviour was higher when the proper number of components were extracted.     

The role of a lifetime history of oppositional defiant and conduct disorders in adults with ADHD: implications for clinical practice

IntroductionAttention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and conduct disorder (CD) are frequently co-occurring disorders in children and adolescents. However, their clinical status among adults is still under discussion. This study analyzes how the current clinical presentation of adult ADHD might be influenced by a lifetime history of CD and ODD. METHODS: We compared three groups of patients: ADHD without history of CD/ODD (n = 178), ADHD + history of ODD (n = 184), and ADHD + history of CD (n = 96). RESULTS: A history of CD (and to a lower extent ODD) is associated with a more severe and externalizing profile.ConclusionPast CD and ODD entail a significant negative mental health impact on persistent ADHD, reinforcing the importance of actively assessing the developmental history of adult ADHD patients.     

Using Pictures to Evoke Spiritual feelings in Breast Cancer Patients: Development of a New Paradigm for Neuroimaging Studies

This study was designed to develop and validate a method for enhancing spiritual feelings, particularly in women who have received a diagnosis of breast cancer. The protocol specifically was developed to be used in functional magnetic resonance imaging (fMRI) studies. Eighteen breast cancer survivors rated pictures for their ability to enhance feelings of spirituality, happiness, and sadness. Results indicate that presenting carefully selected pictures with spiritual content (e.g., nature scenes, people engaged in contemplative behaviors) can effectively enhance spiritual feelings among breast cancer survivors. Future fMRI studies will explore the use of the protocol developed in this study for investigating neural activity during spiritual feelings and states.