Semantic Fluency Performance of Patients with Cortical and Subcortical Neurodegenerative Diseases

Previous studies using the Animals Fluency Test have shown that dementia patients with Alzheimer's disease (AD), Huntington's disease (HD), or Parkinson's disease (PD) produce fewer correct words and have smaller semantic cluster sizes than controls or PD patients without dementia (PDND). Although the number of correct words generated by the patients with AD was positively correlated with mental status, cluster size, surprisingly, was not. To increase word output and increase the reliability of estimates of cluster size, semantic fluency was reexamined using the Supermarket Fluency Task. Overall, patients with HD or PD with dementia (PDD) exhibited reduced cluster sizes compared to older controls or PDND patients, but cluster sizes were only marginally reduced for patients with AD. These effects were evident only for female participants, because the cluster sizes for elderly control men were substantially smaller than those of elderly women. For the female patients with AD, cluster size was correlated with mental status, but the relationship was nonlinear. Cluster size was normal for mildly demented patients with AD, but much reduced for moderately or severely demented participants. In contrast to a previous report, in the present study the proportion of category labels generated was increased for patients with HD with dementia but not for patients with AD. This finding questions one line of evidence that semantic memory stores undergo “bottom-up” degradation in AD. Together with previous results, these findings indicate that semantic cluster size reflects efficiency of access to semantic knowledge which is similarly compromised in subcortical and cortical diseases.     

What clocks tell us about the neural correlates of spatial imagery

We review a series of experimental studies aimed at answering some critical questions about the neural basis of spatial imagery. Our group used functional magnetic resonance imaging (fMRI) to explore the neural correlates of an online behaviourally controlled spatial imagery task without need for visual presentation—the mental clock task. Subjects are asked to imagine pairs of times that are presented acoustically and to judge at which of the two times the clock hands form the greater angle. The cortical activation elicited by this task was contrasted with that obtained during other visual, perceptual, verbal, and spatial imagery tasks in several block design studies. Moreover, our group performed an event‐related fMRI study on the clock task to investigate the representation of component cognitive processes in spatial imagery. The bulk of our findings demonstrates that cortical areas in the posterior parietal cortex (PPC), along the intraparietal sulcus, are robustly involved in spatial mental imagery and in other tasks requiring spatial transformations. PPC is bilaterally involved in different kinds of spatial judgement. Yet the degree to which right and left PPC are activated in different tasks is a function of task requirements. From event‐related fMRI data we obtained evidence that left and right PPC are activated asynchronously during the clock task and this could reflect their different functional role in subserving cognitive components of visuospatial imagery.     

Presurgical Coping, Depression, and Quality of Life in Persons with Parkinson's Disease

This study describes utilization of coping strategies and evaluates the interaction between coping strategies, depression, and quality of life (QOL) in patients with Parkinson's disease (PD) who are being considered for neurosurgical intervention. Eighty patients (mean age 61.7 years) with PD being evaluated for possible deep brain stimulation completed self-report instruments of coping strategies (Coping Responses Inventory), depression (Beck Depression Inventory), and disease-specific QOL (Parkinson's Disease Questionnaire-39). Analyses showed that patients with PD cope with the acute stressor of approaching neurosurgery through a variety of strategies, but particularly avoidant and behavioral strategies. When the correlated but apparently opposing effects of cognitive and behavioral strategies were teased apart, greater use of cognitive strategies was associated with more severe depressive symptomatology (and poorer QOL), while greater use of behavioral strategies appeared to be associated with less depression. Depressive symptomatology, in turn, was associated with poorer QOL. However, coping had minimal direct association with QOL. From this it was concluded that patients with advanced PD generate a variety of coping responses to an acute stressor such as surgery, and the use of behavioral strategies, in particular seeking of alternative enjoyable activities, may be associated with better mood if salutary effects are not overwhelmed by less helpful cognitive coping techniques. The minimization of depressive symptomatology, in turn, is associated with better QOL.     

Configural Frequency Analysis in Applied Psychological Research

L'Analyse de Fréquence des Configurations (AFC) est une méthode de recherche des classes et anticlasses dans les classifications croisées de catégories de variables. Les classes sont des modèles de catégories de variables qui apparaissent plus souvent que le hasard ne le laisse supposes. Les anticlasses sont des modèles de catégorie de variables qui apparaissent moins souvent que le hasard ne le laisse supposes. On présente quatre applications d'AFC: l'AFC de premier ordre, l'AFC prédictive, l'AFC de symétrie axiale, et un modèle d'AFC longitudinale. On examine les caractéristiques de l'AFC en insistant sur les contraintes et l'applicabilité. On compare aussi l'AFC avec d'autres méthodes permettant l'analyse multivariée de catégories de données, en particulier la modèlisation log-linéaire. Des sorties informatiques sont traitées.
Configural Frequency Analysis (CFA) is a method for the search for types and antitypes in cross-classifications of categorical variables. Types are patterns of variable categories that occur more often than expected from chance. Antitypes are patterns of variable categories that occur less often than expected from chance. Four applications of CFA are reviewed: the First Order CFA, the Prediction CFA, Axial Symmetry CFA, and one model of Longitudinal CFA. Characteristics of CFA are discussed, focusing on constraints posed and applicability. Comparisons are made of CFA with other methods for multivariate analysis of categorical data, in particular, log-linear modelling. Computational issues are discussed.