Age-related changes in working and reference memory performance and locomotor activity in the Wistar rat

Wistar rats of three age groups were tested in an automated tunnel-maze system of variable geometry to investigate whether changes in spontaneous locomotor activity and in learning and memory develop differentially or in a correlated fashion as a function of age. Senescent (30 months) as well as mature-adult (17 months) rats showed an age-correlated decline of locomotor activity as compared to the mature-young (5 months) group. Both working-memory (measured as within-trial arm discrimination performance) and reference-memory (measured as avoidance of "blind alley" visits) were severely affected in the senescent group, whereas the middle-aged animals suffered only from a working-memory deficit. The findings provide evidence that locomotor deficits do not necessarily interfere in the assessment of age-related changes in cognitive performance. Furthermore the results support the hypothesis that working and reference memory have different underlying physiological correlates and that these neuronal systems are differentially affected by the aging process.     

Listeriosis of the central nervous system in children beyond the neonatal period

Observations on three children with neurolisteriosis (one case of meningitis, two cases of meningoencephalitis, each Serovar 4 b), show that even after the neonatal period, listeriosis must not be ignored in the process of diagnosis and therapy. It is the bacteriological examination of the cerebrospinal fluid, together with the blood culture, and not clinical symptoms and serology that guarantee a timely diagnosis and therapy (ampicillin and gentamicin).     

Hierarchical classes: Model and data analysis

A discrete, categorical model and a corresponding data-analysis method are presented for two-way two-mode (objects × attributes) data arrays with 0, 1 entries. The model contains the following two basic components: a set-theoretical formulation of the relations among objects and attributes; a Boolean decomposition of the matrix. The set-theoretical formulation defines a subset of the possible decompositions as consistent with it. A general method for graphically representing the set-theoretical decomposition is described. The data-analysis algorithm, dubbed HICLAS, aims at recovering the underlying structure in a data matrix by minimizing the discrepancies between the data and the recovered structure. HICLAS is evaluated with a simulation study and two empirical applications.This research was supported in part by a grant from the Belgian NSF (NFWO) to Paul De Boeck and in part by NSF Grant BNS-83-01027 to Seymour Rosenberg. We thank Iven Van Mechelen for clarifying several aspects of the Boolean algebraic formulation of the model and Phipps Arabie for his comments on an earlier draft.