Profiles of ageing in the South of Portugal: education and cognitive functioning in elderly persons living in institutionalized and community contexts

The region of the Algarve shows huge differences between the coastline where population in the urban areas grows, and the inland rural areas, in some cases very isolated, which frequently have high ageing indexes. This general scenario, with an elderly population with very different economic and social conditions, frames the ongoing PhD research designed as a cross-sectional study of an intentional sample of elderly persons. The basic theoretical framework departs from the perspective of developmental psychology of life-span and the model of selection, optimisation and compensation for optimal ageing (Baltes & Baltes, 1990; Freund & Baltes, 2002). The present study is a first step in the analysis of empirical data collected in the PhD sample (N=156; age range 65 to 97 years; M = 80.4 years; SD = 7.2 years). Its purpose is to assess the cognitive functioning of participants, screening for cognitive impairment and examine the relations between the cognitive status of the subjects and a number of selected variables including educational level, age, physical activity and living contexts of the subjects. We accessed the cognitive status of the participants with the Portuguese version of Mini Mental State Examination (MMSE) finding a 10.3% prevalence of positive cases with cognitive impairment. The results also show significant relationships between the cognitive status accessed by the MMSE and educational level, professional qualification, age, living arrangement and activity level of the participants. The relationship verified between educational level and cognitive status of the participants was the largest correlation found in the study with the variability in educational level accounting for 44.8% of the variability in MMSE score. This results points in the same direction of several lines of research that corroborate the strong intercorrelation between education and cognitive functioning in old age.

Supervised training approach using spiking neural networks

One of the basic aspects of some neural networks is their attempt to approximate as much as possible their biological counterparts. The goal is to achieve a simple and robust network, easy to understand and able of simulating the human brain at a computational level. Recently a third generation of neural networks (NN) [1], called Spiking Neural Networks(SNN) was appeared. This new kind of networks use the time of a electrical pulse, or spike, to encode the information. In the first and second generation of NN analog values are used in the communication between neurons.