Cognitive Plasticity in Young-Old Adults and Old-Old Adults and Its Relationship with Successful Aging

The general objective of this study was to analyze cognitive plasticity as a variable related to successful aging in a group of young-old adults and old-old adults using the Auditory Verbal Learning Test—Learning Potential (AVLT-LP). Method: A total of 569 persons, with mean age 76.67 years (379 between the ages of 65 and 80 years, and 190 older than age 80). They were assessed with a socio-health questionnaire, with the AVLT-LP, and with the Spanish version of the Mini Mental State Examination. Results: The results showed significant differences on the test, in favor of the younger group, while the over 80 group gave poorer performance and showed less cognitive plasticity. With relation to gender, slight differences appeared in favor of the women, on the first four test trials, but not on the last two, nor in delayed recall or cognitive plasticity. As for cognitive status, the results showed significantly better task performance levels in healthy elders, as well as greater plasticity. Nonetheless, certain persons with high plasticity were also found among those with cognitive impairment. Conclusions: The data obtained here offers evidence for the importance of cognitive plasticity in elders and its relation to longevity and successful aging. It also provides information about the influence of variables like age, gender and cognitive status on a verbal memory and plasticity assessment task that is in wide use today.


Introduction
The increasing elderly population in Western countries is an unprecedented fact in our recent history. For example, it is expected that by the year 2020, the number of persons over age 65 in Europe and the United States will comprise 20% of the population [1,2].
Aging is usually accompanied by losses in both cognitive and physical abilities [3]. In relation to cognitive loss, impairment is usually observed in skills related to fluid intelligence, such as working memory and episodic memory, reasoning and spatial orientation [4][5][6]. Despite the above, the literature indicates that there are important inter-individual differences in cognitive functioning during old age [7,8]. Following this line, many studies have demonstrated potential for learning and cognitive improvement by exploring the concept of cognitive plasticity [9][10][11].
The concept of cognitive plasticity refers to intraindividual modifiability, and is defined by the authors [12,13] as intellectual performance in old age under optimized conditions that do not normally exist in the person's daily life or in the standard assessment situations of classical intelligence tests [13]. The term cognitive plasticity takes on particular importance in gerontological literature, where one is ± 1.99 F(1/568) 62 1.00 * The difference is significant at 0.05 (p < 0.05). ** The difference is significant at 0.01 (p < 0.01).  1.00 * The difference is significant at 0.05 (p < 0.05). ** The difference is significant at 0.01 (p < 0.01). 2 = 0.001) and A6 (F (1/568) = 2.429, p > 0.05, Geriatrics 2018, 3, x        1.0 * The difference is significant at 0.05 (p < 0.05). ** The difference is significant at 0.01 (p < 0.01). 2 = 0.274), with a significant drop in the score of the cognitive impairment group.

Distribution of the Participants According to Their Age Range, Cognitive Status, Gender and Cognitive Plasticity Status
Second, we analyzed the distribution of participants according to their plasticity status (calculated from the Schöttke et al. algorithm [51], their age range, gender and cognitive status. As shown in Table 2, the distribution was not homogeneous in the case of age range (χ 2 = 26.027 (2/268) p < Figure 1. Participants' learning curves and delayed recall (A7) as a function of age range, gender, and cognitive status. * The difference is significant at 0.05 (p < 0.05). ** The difference is significant at 0.01 (p < 0.01).

Distribution of the Participants According to Their Age Range, Cognitive Status, Gender and Cognitive Plasticity Status
Second, we analyzed the distribution of participants according to their plasticity status (calculated from the Schöttke et al. algorithm [51], their age range, gender and cognitive status. As shown in Table 2, the distribution was not homogeneous in the case of age range (χ 2 = 26.027 (2/268)  such that the highest percentage of persons with low plasticity was found in the 81+ group (63.68%). In the case of gender, the sample showed homogeneous distribution (χ 2 = 0.476 (1/268) p > 0.05), with a similar percentage of persons having high and low plasticity in the groups of men and women. As for cognitive status, the distribution was not homogeneous (χ 2 = 50.063 (1/268) p < 0.0001), such that 62.78% of the total group of persons with high plasticity did not have cognitive impairment, while 67.74% of persons with low plasticity presented cognitive impairment. Likewise, in the group of persons without cognitive impairment, 75.95% were classified with high plasticity and 52.87% of the group with cognitive impairment were classified with low plasticity. The analyses carried out (see Table 3) showed that the multivariate contrasts were significant for age range (Wilks' Lambda Λ (1/4) = 8.587, p < 0.001) and for cognitive status (Wilks' Lambda:      Table 1. Mean scores and differences as a function of the va AVLT-LP gain score.

AVLT-LP TRIALS A1
The Bonferroni correction showed all differences to be significant (p < 0.001).
Although the interaction between the two factors (age range and cognitive status) was not significant in the MANOVA, one may cautiously assert that the ANOVA was significant for the following measures: A4 (F (1/4) = 7.209, p < 0.05,

Discussion
The main objective of the present study was to analyze cognitive plasticity as assessed through the AVLT-LP, in a large sample of older people, and to analyze how that cognitive plasticity relates to variables reported in the specialized literature to have an influence, namely, age range (young-old adults and old-old adults), gender and cognitive status [29,30,45,53].
The results showed significant between-group differences in performance and in the learning curve (trials A1 to A6) in favor of the younger group, who significantly outperformed the over 80 group. These results agree with findings from other studies where learning potential continues to decline with age [4,6,37,54] and with studies that show good levels of cognitive performance in young-old adults [35,36]. Differences also appeared in delayed recall (A7) and in AVLT-LP gain score, our indicator of cognitive plasticity, but in this case it was the over 80 group that showed significantly lower performance than the young-old adults group. It seems in this case that age 80 marks the start of a significant decline in cognitive plasticity and in long-term memory, as suggested by prior research that places the transition from the third to the fourth age at about 80-85 years [28,31,32,37,38]. These data are corroborated by our sample distribution according to age group and cognitive plasticity status (calculated from the Schöttke et al. algorithm [51], where we found that the greatest percentage of persons with low plasticity was in the over 80 group (43.52%).This classification is consistent with reports from prior research indicating that, while plasticity continues to be present at advanced ages (in our study 36.31% of the over 80 group presented plasticity), it is present to a lesser degree than in earlier stages [28][29][30].
In relation to cognitive status, results showed significantly higher performance levels in the healthy elders. Moreover, these differences increased over the duration of the test, with a very significant drop in delayed recall in persons with cognitive impairment. These data are in line with prior studies that indicate important differences in cognitive plasticity between persons with and without cognitive impairment, thereby showing the effectiveness of dynamic assessment procedures for identifying persons with cognitive impairment [20,25,26,45]. Additionally, results for delayed recall confirm that it has an important role in identifying persons with risk of dementia [45]. These authors propose that having a delayed recall score (trial A7) that is lower than one's score in the first trial (A1) would be a clear indicator of Alzheimer-type dementia [45].
The interaction between age range and cognitive status should also be highlighted: The difference between the four groups was significant in the variables that involved learning ability, that is, A4, A5, A6 and AVLT-LP gain score. It also showed that healthy old-old adults had higher scores in those variables than young-old adults with cognitive impairment. These results confirm previous research regarding the presence of cognitive plasticity in old-old adults [29,30]. Decrease in cognitive plasticity appeared to be associated mainly with cognitive impairment, such that the presence of cognitive impairment would be the determinant of less plasticity, and not age range. From our point of view, this result is very significant and should be taken into account in future studies in this topic area.
Regarding gender, results from this study showed that -after controlling for educational level-the women presented slightly better performance than the men in the first four test trials (pre-test and training phases), with no differences in the last two trials, in delayed recall or in gain score (indicative of plasticity). Likewise, looking at our sample distribution, we found a similar percentage of persons with high and low plasticity in the groups of men and of women. Prior studies had reported better performance levels in episodic memory tasks in women [25,[55][56][57]; this might be related to greater verbal ability in women [58] or, as Speer et al. [59] indicate, with biological factors, such as greater vascular risk in men, or an earlier onset of atrophy in the left-medial temporal lobe. In our study, notwithstanding, the differences between men and women are very slight and are not present in delayed recall or in cognitive plasticity, suggesting that there are no gender differences in ability to learn or in long-term memory in old age, after controlling for educational level. This result would confirm previous studies, such as Faille [60], where no gender differences were found in cognitive plasticity in a sample of elders with a mean age of 80 years.
When we analyze the participants classified according to their plasticity and cognitive status, we find the expected higher proportion of high plasticity persons in the group of healthy elders (75.94%). However, in the group of persons with cognitive impairment, we also found that 47.12% benefitted from the training given in the AVLT-LP test, significantly improving their performance on the post-test, and thereby showing cognitive plasticity.
This result is consistent with prior studies [3,22,26,61] that indicate the presence of plasticity in elders with cognitive impairment and also indicate the possibilities for using this type of measure when planning cognitive interventions and predicting the cognitive evolution of elders [22,26,44,62].
In short, the study presented here contributes more evidence of the importance of evaluating cognitive plasticity in the elderly, and offers information about the influence of variables, such as age, gender, and cognitive status, in a widely used task for assessing verbal memory and plasticity [57,63,64]. We consider this fact to be quite relevant, since it underscores the importance of considering variables, such as those analyzed here when evaluating an older population. Variables like age range and gender influence cognitive performance; consequently, specific data should be established as a function of these variables. In addition, the large sample used in this investigation allows the conclusions to be generalized to broader population samples. However, there are certain limitations to the study, for example, that the participants did not have an external diagnosis to confirm the presence or absence of impairment or dementia, and that while the sample is quite large, place of residence was uniformly a retirement home. It would also have been interesting to assess the participants with a test of executive control, due to its connection with cognitive plasticity [27]. Given these limitations, future studies should seek to work with samples of elders that reside in their own homes, and to analyze the differences between elders living in community settings and in senior residences, and who have a clinical diagnosis. Nonetheless, we believe that the data presented here may be of interest to the scientific community, to the extent that it offers information about the utility of the AVLT-LP for assessing the ever-increasing proportion of elders in our society today.