RESUMO
The aging population is growing rapidly. Proposing interventions that enhance the cognitive functions or strategies that delay the onset of disabilities associated with age is a topic of capital interest for the biopsychosocial health of our species. In this work, we employed musical improvisation as a focal environmental activity to explore its ability to improve memory in older adults. We present two studies: the first one evaluated neutral memory using the Rey Complex Figure (RCF) and the second one evaluated emotional memory using International Affective Picture System (IAPS). A group of 132 volunteers, between the ages of 60 and 90, participated in this investigation. Fifty-one of them were musicians with more than 5 years of formal musical training. After acquisition of neutral (Study 1) or emotional (Study 2) information, the groups of older adults were exposed to music improvisation (experimental intervention) or music imitation (control intervention) for 3 min. We then evaluated memory through two tasks (free recall and recognition), by means of immediate and deferred measures (after a week). We found a significant improvement in memory among participants involved in music improvisation, who remembered more items of the RCF and images from IAPS than the imitation group, both in the immediate and deferred evaluation. On the other hand, participants who had musical knowledge had a better performance in neutral visual memory than non-musicians. Our results suggest that a focal musical activity can be a useful intervention in older adults to promote an enhancement in memory.
RESUMO
The brain processes temporal statistics to predict future events and to categorize perceptual objects. These statistics, called expectancies, are found in music perception, and they span a variety of different features and time scales. Specifically, there is evidence that music perception involves strong expectancies regarding the distribution of a melodic interval, namely, the distance between two consecutive notes within the context of another. The recent availability of a large Western music dataset, consisting of the historical record condensed as melodic interval counts, has opened new possibilities for data-driven analysis of musical perception. In this context, we present an analytical approach that, based on cognitive theories of music expectation and machine learning techniques, recovers a set of factors that accurately identifies historical trends and stylistic transitions between the Baroque, Classical, Romantic, and Post-Romantic periods. We also offer a plausible musicological and cognitive interpretation of these factors, allowing us to propose them as data-driven principles of melodic expectation.