Cognitive performance of young and elderly subjects on the free word recall memory test: effect of presentation order on recall order

The influence of aging on memory has been extensively studied, but the importance of short-term memory and recall sequence has not. The objective of the current study was to examine the recall order of words presented on lists and to determine if age affects recall sequence. Physically and psychologically healthy male subjects were divided into two groups according to age, i.e., 23 young subjects (20 to 30 years) and 50 elderly subjects (60 to 70 years) submitted to the Wechsler Adult Intelligence Scale-Revised and the free word recall test. The order of word presentation significantly affected the 3rd and 4th words recalled (P < 0.01; F = 14.6). In addition, there was interaction between the presentation order and the type of list presented (P < 0.05; F = 9.7). Also, both groups recalled the last words presented from each list (words 13-15) significantly more times 3rd and 4th than words presented in all remaining positions (P < 0.01). The order of word presentation also significantly affected the 5th and 6th words recalled (P = 0.05; F = 7.5) and there was a significant interaction between the order of presentation and the type of list presented (P < 0.01; F = 20.8). The more developed the cognitive functions, resulting mainly from formal education, the greater the cognitive reserve, helping to minimize the effects of aging on the long-term memory (episodic declarative).

Brain tissue segmentation using q-entropy in multiple sclerosis magnetic resonance images

The loss of brain volume has been used as a marker of tissue destruction and can be used as an index of the progression of neurodegenerative diseases, such as multiple sclerosis. In the present study, we tested a new method for tissue segmentation based on pixel intensity threshold using generalized Tsallis entropy to determine a statistical segmentation parameter for each single class of brain tissue. We compared the performance of this method using a range of different q parameters and found a different optimal q parameter for white matter, gray matter, and cerebrospinal fluid. Our results support the conclusion that the differences in structural correlations and scale invariant similarities present in each tissue class can be accessed by generalized Tsallis entropy, obtaining the intensity limits for these tissue class separations. In order to test this method, we used it for analysis of brain magnetic resonance images of 43 patients and 10 healthy controls matched for gender and age. The values found for the entropic q index were 0.2 for cerebrospinal fluid, 0.1 for white matter and 1.5 for gray matter. With this algorithm, we could detect an annual loss of 0.98% for the patients, in agreement with literature data. Thus, we can conclude that the entropy of Tsallis adds advantages to the process of automatic target segmentation of tissue classes, which had not been demonstrated previously.