I. INTRODUCTION

It is now well known that one generally experiences relatively mild changes in cognitive abilities with age, particularly with abilities such as short-term memory, executive functions, and confrontation naming [1]. However, a select group of these “successfully” aged individuals evidence virtually no change in their cognitive abilities with age, even into the eleventh decade of life [2]. Such individuals have often been referred to as examples of “pristine” successful aging. At the other end of the continuum, a large percentage of people are known to develop marked cognitive decline with age, characterized by a dementia state, with a majority of those developing Alzheimer’s disease (AD). These individuals fall into the category of “unsuccessful” aging. In recent years, however, clinical researchers have characterized a group as individuals who, with advancing age, show a moderate impairment in one or more cognitive domains that affects the ability to carry out activities of daily living but does not reach the threshold of a dementia state. This category, classified by many as “mild cognitive impairment” (MCI), reasonably can be regarded as a second general category of “unsuccessful” aging. Although many consider MCI as the earliest stage of Alzheimer’s disease, evidence suggests that MCI represents a separate static and chronic state of normal aging. The etiology of MCI is unknown, but stroke and heart disease risk factors, genetics, and education have all been raised as possible contributors.

While nongenetically altered laboratory animals do not evidence the brain changes seen in AD [3], they have reliably demonstrated age-related changes in cognitive function. Evidence from a wide range of studies in rodents, dogs, and non-human primates have shown as a group that aged subjects are significantly impaired relative to young controls on cognitive tasks that assess functions such as working memory, declarative memory, and executive function: the same functions that evidence impairment in human aging [4–16]. However, on close inspection of the data, the degree of impairment within the aged group is anything but uniform and, in fact, is often dichotomous. While the overall group effect yields an impairment in the given function, it is clear that individuals within the aged group evidence only mild or, in some cases, no impairment on the task while others demonstrate severe impairment.

The finding of individual differences, emphasized in the rodent literature (see [17]), has not been addressed previously in studies of nonhuman primates. This is due in part to the small number of studies in aging primates as well as the relatively small sample sizes of aged groups available within studies. This chapter presents data that we have collected over the past 15 years as part of an ongoing study using the rhesus monkey as a model of normal human aging. During this period, more than 125 rhesus monkeys ranging in age from 5 to 31 years of age have been assessed on multiple tests of recognition memory and executive function. In this chapter we present the data from these animals and discuss their varying levels of impairments and how this relates to clinical findings in human studies.

II. NONHUMAN PRIMATES AS SUITABLE ANIMAL MODELS OF AGING

Several hypotheses have been advanced to account for the neural bases that underlie the cognitive decline that occurs in normal, disease-free aging, but the processes underlying such decline are still not well understood. This is in large part due to our inability to concurrently collect behavioral, physiological, and pathological data within a short interval of time in human studies. Additional limitations are encountered by problems related to inadequate preservation of tissue, as well as the usual problems of control over extraneous variables. Given these limitations, it is essential to use a suitable animal model of normal human aging to address some of these questions. In a recent symposium on aging and Alzheimer’s disease, a number of investigators reiterated the value of non-human primates as an animal model of human aging (Assessing Cognition for Emerging Therapeutics in AD, Johns Hopkins School of Medicine, September 2004). Rhesus monkeys have a rich and well-studied behavioral repertoire that is well suited for these types of investigations of normal aging, as they do not develop Alzheimer’s disease. In addition, with this animal model, not only is it possible to collect a wide range of behavioral, morphological, biochemical, and molecular data within a short period of time, but opportunities are also provided for the exploration of treatment modes and interventions to arrest or reverse age-related cognitive decline.

III. COGNITIVE ASSESSMENT OF THE AGED NONHUMAN PRIMATE

As discussed above, monkeys have a rich behavioral repertoire that lends itself suitably to translational studies of human cognition. Indeed, several behavioral tasks developed in the human neuropsychological domain have now been successfully adapted to the nonhuman primate. In some instances, tasks developed for non-human primate studies have been incorporated into both research and clinical test batteries for human studies. This has occurred primarily in the domains of memory, executive function, and attention. The following subsections outline each of these domains as they relate to nonhuman primates.

IV. STUDIES ON SPECIFIC TASKS OF MEMORY AND EXECUTIVE FUNCTION

The behavioral tasks used in our studies were derived from two sources. The first source was a battery of learning, memory, and cognitive flexibility tasks that have been used as “benchmark” tests of function in monkeys with selective limbic system and frontal cortical lesions. Some of these tasks were subsequently adapted for use with normal aged humans and to patients with Alzheimer’s disease, frontal lobe dementia, and a variety of amnestic disorders [67, 68]. The second source of tests came from those used in standard human neuropsychological testing that have been modified for use with monkeys such as the CSST [69]. Together this battery of tasks offers the advantage that (1) it can be administered and performed by aged human and nonhuman primates alike; (2) the tasks are carefully controlled and allow analyses of performance patterns that can differentiate among subjects, both human and monkey, with different neuropathologies; and (3) there exists an accumulated wealth of information on structure-function relationships from human and animal studies assessing and carefully characterizing the effects of specific brain damage using these tasks.

In our cohort, animals range in age from 5 to 31 years of age. Based on an extensive survival study at Yerkes Regional Primate Research Center, which suggests a 1:3 ratio between monkey and human years of age, we have characterized young monkeys as 5 to 10 years of age, middle-aged monkeys as 13 to 19 years of age, early-aged monkeys as 20 to 24 years of age, and advanced-aged monkeys as >25 years of age.

A. Definition of Cognitive Impairment

Within this group of animals, we developed a cognitive impairment index (CII) as a measure of cognitive function in aging. This measure provides a convenient index for ranking and comparing individual animals. The CII was derived based on the principal components analysis [4], which indicated that overall impairments were predicted by a weighted average of each subject’s scores on the DNMS, the DNMS-2 minute delay, and DRST-spatial (see test descriptions below). To simplify this, the scores on each of the three tasks for each individual were converted to a z-score relative to the mean performance of young adults (the baseline reference group). The CII was then computed as a simple average of the three standardized scores, with positive numbers indicating increasing impairments in z-units from the mean of the baseline reference group of young adult monkeys.

With this index, we established a cutoff for mild impairment as a CII that is 1.0 to 2.0 standard deviations above the mean for young adult monkeys. Thus, monkeys with a CII 1.0 to 2.0 SD above the mean of the young animals are considered to be mildly impaired, whereas monkeys with CIIs of 2.0 SDs or more above the mean of the young are considered severely impaired. Monkeys with CIIs below 1.0 are considered in the nonimpaired range. Based on these criteria for levels of impairment, we determine that animals in the normal range of performance and in the mild impairment range are equivalent to what has been termed “successful aging” in the human literature. Similarly, animals that fall into the severely impaired range are equivalent to “unsuccessful aging,” as observed in human clinical studies.

Within our cohort of animals, based on the CII measurement, 4.55% of animals in the 13- to 19-year-old age group were mildly impaired and 22.7% were severely impaired. In the 20- to 24-year-old age range, 20.69% of the animals were mildly impaired and 20.69% of the animals were severely impaired. Finally, 19.35% of the animals in the 25- to 31-year-old age range were mildly impaired while 32.3% were severely impaired (Table 2.1). Overall, the percent of animals in the mild impairment range remained relatively stable through middle age and advanced age but the percent of animals in the severely impaired range (unsuccessful aging) increased by almost 15% from middle age and advanced age. As expected, the overall number of animals demonstrating significant cognitive impairment increased with age but there were still a considerable number of animals with mild or no cognitive impairment (Figure 2.1).

TABLE 2.1

Cognitive Impairment Index

FIGURE 2.1

Cognitive impairment index: percent of animals in the normal, mild impairment, and unsuccessful ranges.

While the CII is an important measure of cognitive function, we thought it was important to also look at animals’ performance on individual tests of memory and executive function. Using the same criterion as with the CII for level of impairment (mild impairment = 1.0–2.0 SD from the mean of the young on each test; and severe impairment equal to or greater than 2.0 SD from the mean of the young on each test), we determined the percent of animals that fall within the normal, mildly impaired, and severely impaired range on each individual test in our study. The results are outlined in the subsections below.

B. Delayed Nonmatching to Sample (DNMS)

1. Overview of DNMS

The DNMS task is a benchmark recognition memory task that assesses the subject’s ability to identify a novel stimulus from a familiar stimulus following a specific delay interval. Although originally developed for assessment of memory in animals, it also has been used with human subjects. Various forms of this task have been used to assess memory function in monkeys following specific lesions of the forebrain, including transection of the fornix [70–72], limited or combined lesions of the hippocampus and amygdala [71–75], or medial dorsal thalamus [76].

This task is administered in three phases. First, in the acquisition phase, the animal must learn the rule of the task to reach criterion. After criterion is reached, a delay component is added where the animal must remember the stimulus over an increasing delay. Finally, in surgical animal models, there is the postoperative relearning phase of the DNMS where the animal must reestablish a level of learning criterion after a surgical procedure. Depending on the experimental paradigm, deficits on the acquisition or post-operative relearning phase of the DNMS task have been reported following damage to the hippocampus [71, 74, 77, 78], and to a greater extent in monkeys with combined damage to the amygdala and hippocampus [73, 74]. More recently, impairments have been found following damage to extrahippocampal regions, including rhinal cortex, entorhinal cortex, perirhinal cortex, and adjacent parahippocampal cortices [79–84], regions that are critical components of temporal lobe neuronal circuitry linking the hippocampus and amygdala with the rest of the forebrain. In humans, the DNMS task also has been shown to be sensitive to selected temporal lobe damage [85] and to a variety amnestic disorders [86], as well as to Alzheimer’s disease and normal aging [67].

In aged monkeys, results from studies in several laboratories have shown an impairment in the acquisition and delay phases of the DNMS task [4, 10, 33, 36, 37, 39, 40]. The findings appear to be quite consistent across these studies and show that, as a group, aged monkeys are mildly impaired on the acquisition and delay conditions of the DNMS task. Another consistent finding is variability in the performance of aged animals. Whereas some aged monkeys evidence impairment, others perform the task as proficiently as young adults [36, 37, 39].

2. Successful vs. Unsuccessful Aging in Performance on DNMS

This pattern of variability in performance on the DNMS task by aged animals is confirmed in the data from our cohort (see Table 2.2). On the acquisition phase, none of the animals in the 13- to 19-year-old age group fell within the mild impairment range (1.0–2.0 SD from the mean) while 21.7% of the animals in this group were in the severe impairment range (greater than 2.0 SD from the mean of the young). Whereas in the 20- to 24-year-old age range, 13.8% and 27.6% of the animals were 1.0–2.0 SD and greater than 2.0 SD, respectively, from the mean of the young. Finally, in the 25- to 31-year-old age range, 9.68% of the animals were mildly impaired and 35.48% were severely impaired. A similar pattern of impairments was observed in the delay components of the DNMS (Table 2.2). It has been suggested that the degree of impairment on the DNMS may be related to the extent of limbic system dysfunction [37, 39]. Consistent with this notion is the suggestion that the nature of the deficit on DNMS in impaired aged monkeys is due to a disproportionate sensitivity to proactive interference [14, 15]. It is of interest that, when aged monkeys were tested on a version of the DNMS task that contains an extensive degree of interference (i.e., using the same pair of objects throughout the task), their performance declined precipitously to a level comparable to that of their performance on the delayed response task [87]. Whether this simply reflects an increase in task difficulty or a shift in the underlying locus of neuronal circuitry is unclear.

TABLE 2.2

Delayed Nonmatching to Sample

C. Delayed Recognition Span Task (DRST)

1. Overview of DRST

This task is a short-term memory test that was designed to investigate recognition memory in monkeys following bilateral removal of the hippocampus [88]. It requires the subject to identify, trial-by-trial, a new stimulus among an increasing array of serially presented, familiar stimuli. The task is administered using different classes of stimulus material, spatial vs. nonspatial (color, pattern, objects), to characterize possible material-specific recognition memory impairments. An expanded form of this task has been used in the same manner to assess recognition in a variety of neurological patient populations including those of Alzheimer’s disease [67, 89], Huntington’s disease or Korsakoff’s disease [68], and Parkinson’s disease [90]. In normal aged human subjects, recognition span memory is impaired in several stimulus classes, including spatial position and visual patterns [68, 91].

2. Successful vs. Unsuccessful Aging in Performance on DRST

In our study, this task is administered using two different classes of stimulus material: spatial location or object shape. This allows us to characterize any recognition memory deficits that may occur as a general impairment or one that is material specific.

a. Delayed Recognition Span Test: Spatial

Unlike the pattern of number of animals considered impaired with increasing age on learning the DNMS basic task, few animals were impaired (1.0–2.0 or greater than 2 Standard Deviations from the mean of the young monkeys) on DRST task. In fact, none of the animals in the 13- to 19-year-old range were impaired, and only 6.89% of animals in the 20- to 24-year-old age range fell within the mild impairment range. None of the animals in this age range were classified as severely impaired. Similarly, 6.45 % and 3.22% of animals in the 25- to 31-year-old range were mildly and severely impaired, respectively, on the spatial DRST (see Table 2.3).

TABLE 2.3

Delayed Recognition Span Test

b. Delayed Recognition Span Test: Object

An almost identical pattern was observed on the object DRST. The performance of a very small number of animals was in the mild and severe impairment ranges (see Table 2.3).

D. Conceptual Set Shifting Task

1. Overview of Conceptual Set-Shifting

Executive function is one of the first cognitive abilities to be compromised in aging and age-related disease [5, 6, 67] and is considered a primary function of the prefrontal cortices [47, 92–94]. As summarized above, we developed a task suitable for testing monkeys based on the principles of the standard frontal lobe set-shifting task used in humans, the Wisconsin Card Sorting Test (WCST) [53, 54]. Our test, the Conceptual Set Shifting Task (CSST), uses a subset of the same stimuli as the WCST to assess abstraction, establishment, maintenance, and shifting of sets and perseveration in a manner that parallels that used in human clinical studies.

2. Successful vs. Unsuccessful Aging in Performance on CSST

Of the 128 animals in our group, 66 were tested on the CSST. Performance on the CSST appears to be affected early in aging and may become the most compromised with advanced age. In contrast to tests of memory where the performance of a few subjects reached the severe impairment range, a large number of animals were in the mild and severe impairment range on the CSST. In fact, on various measures of performance on the CSST, 12 middle-aged animals were mildly impaired and between 25 and 41% were severely impaired. In contrast, in the aged animals, 0 to 32% of the animals were mildly impaired and 0 to 36% were severely impaired (Table 2.4). These findings would suggest that executive system functions may be among the most sensitive domains affected with advancing age.

TABLE 2.4

Conceptual Set-Shifting Task

V. NEUROBIOLOGICAL BASIS FOR COGNITIVE DECLINE

Several possibilities have been advanced to account for mild or marked age-related cognitive decline, ranging from widespread cortical neuronal loss and neurotransmitter depletion, to amyloid deposition and to the development of neuritic plaques. While likely contributing to cognitive dysfunction, we believe that these factors are unlikely primary candidates to account for age-related cognitive decline. With few exceptions, neurons in the cerebral cortex do not undergo marked loss [95] and the presence and the extent of neuritic plaques or amyloid burden are quite variable and are not correlated with cognitive decline [96]. Rather, we have accumulated evidence over the past several years that lead us to the view that alteration and loss of white matter may be the principal neurobiological change that underlies age-related cognitive decline [3]. In electron microscopic (EM) studies of the effects of aging in the cerebral cortex [97, 98], corpus callosum [98], and optic nerve [99] of monkeys, myelin sheaths have been found to show marked age-related changes, including the accumulation of dense cytoplasm and the formation of fluid-filled balloons. In addition, the formation of sheaths with redundant myelin and thick sheaths occur with continued formation of myelin with age [100]. Of particular interest, the frequency of these alterations in myelin with age correlates significantly with the cognitive decline exhibited by monkeys. In support of this, using diffusion tensor magnetic resonance imaging (DT-MRI), we have recently reported significant age-related loss of fractional anisotropy (FA) in forebrain white matter of the frontal lobe. Reduced FA is regarded as a marker of white matter abnormalities and, like the EM measures, correlates with cognitive decline [101]. Further, unpublished data from our group on conduction across the corpus callosum indicates that, with age, there is a significant alteration in the profile of conduction parameters. This result could be explained if the myelin dystrophy observed in the corpus callosum [98] disrupts conduction in a fraction of the nerve fibers and suggests that alterations in myelin integrity and consequent disruption of conduction may alter the signal strength and hence the information transfer that is critical for neuronal circuits to operate properly. Finally, using designed-based stereology and MRI in separate studies, our group has demonstrated nerve fiber loss with age from the optic nerves [99], a 40% loss of nerve fibers in the anterior commissure of aged rhesus monkeys, and a significant loss of white matter volume on with MRI, with an accompanying increase in ventricular size (Wisco, Killiany, and Rosene, unpublished observations). These observations lend further support to the notion that there is likely to be a global loss of myelinated nerve fibers with age. Extensive multidisciplinary investigations into the precise mechanisms of these age-related changes in white matter and their relationship to cognitive decline are the focus of our current studies with the continued use of our nonhuman primate model of normal aging.

ACKNOWLEDGMENTS

The authors wish to acknowledge support from NIH grants PO1-AG0001 (DLR), R37-AG17609 (MBM), and R55-AG12610.

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