Only 40 years ago it was widely believed that if you lived long enough, you would eventually experience serious cognitive decline, particularly with respect to memory. The implication was that achieving an advanced age was effectively equivalent to becoming senile—a word that implies mental defects or illness. As a graduate student back then, I was curious why such conclusions were being drawn about the elderly. I had only to look as far as my own great-grandmother and great-aunt to begin questioning the generalization. They lived to 102 and 93, respectively, and were exceptionally active and quick-witted enough to keep us twentysomethings on our toes. A closer look at the literature didn’t give me any confidence that either the biological basis of memory or how it might change with age was well understood. Many discoveries made in the years since have given us better tools to study memory storage, resulting in a major shift away from the view of “aging as a disease” and towards the view of “aging as a risk factor” for neurological diseases. So why do some people age gracefully, exhibiting relatively minor—and at worst annoying—cognitive changes, while others manifest significant and disabling memory decline? Answers to these questions are fundamental for understanding both how to prevent disease and how to promote quality of life.

A test for normal aging

Cognitive decline at older ages is marked by gradual loss in the ability to retain new information or to recall the past. Although many other changes occur during the aging process—impairment in range of motion, speed of gait, acuity of vision and hearing—none of these factors are as central to one’s personal identity as are one’s cumulative experiences. For me, it seemed that understanding memory, and how it changes with age or disease, was the key to understanding the aging brain.
Infographic: Molecular Learning
View full size JPG | PDFTAMI TOLPA
When I was in graduate school, in 1973, two papers came out that would change the shape of neuroscience and memory research. Terje Lømo, Tim Bliss, and Tony Gardner-Medwin devised a method that could experimentally alter synaptic strength. Earlier theoretical ideas had implied that strengthening the connection between neurons might explain how memories were formed: the stronger the connection, the better a message could be relayed or recalled. As electrophysiologists, Lømo and colleagues tested this idea by sending electrical currents through a group of neurons in the rabbit hippocampus in patterns that mimicked normal electrical activity, and measuring how the connections between the neurons changed. By stimulating neurons, they could create a durable increase in synaptic strength, which was later dubbed long-term potentiation, or LTP. But more than just an intriguing physiological observation, the research presented a fully controllable experimental proxy for learning that made it possible to study memory across the lifespan of an animal for the first time.
Thus, with the discovery of LTP, and the idea that animal models of human memory could be developed, I sought to finish my dissertation research in a lab that was routinely conducting LTP experiments. At the time, there were only three labs in the world that were doing these types of experiments: Graham Goddard’s laboratory at Dalhousie University, Tim Bliss’s at University College London, and Gary Lynch’s at UC, Irvine. As it turned out, my thesis advisor Peter Fried, at Carleton University in Ottawa, had been one of Goddard’s students, and introduced me to him by saying, “I don’t really want you to steal my student, but she has this idea that she thinks you might be interested in.” I explained to Goddard that I wanted to track an animal’s ability to make and keep spatial memories as it aged. Since the hippocampus—the area of the brain where LTP was first discovered—was also involved in spatial memory, I wanted to use Goddard’s setup and surgically implant electrodes that could measure LTP in awake, freely behaving rats. In an act of faith and generosity, Goddard soon purchased animals for me and began to “age” them in anticipation of my arrival the following year.
The behavioral tests used to study spatial memory at this time all used somewhat severe methods to motivate animals: either with shock—a significant stress—or by restricting eating or drinking, both of which were potentially detrimental to survival. Because the precious aged animals could not be replaced without waiting two years to grow another “old” batch, I developed a novel, milder task that is now often referred to as the Barnes maze. With rodents’ natural aversion to open, well-lit areas in mind, I designed a circular platform with many openings around its circumference, only one of which would allow the animal to escape into a dark box beneath the platform’s surface.
Aging is not equivalent to the aberrant process of Alzheimer’s disease; it is in fact a distinctly different neurological process.
At 2–3 years old (an age equivalent to about 70-80 human years), the rats were old enough to begin the behavior and electrophysiological experiments in the latter part of 1975. The animals were permanently implanted with electrodes that could both stimulate the neurons and record their activity. The electrodes allowed us to measure baseline synaptic transmission with single stimuli, then to induce LTP, and finally to monitor its decay over several weeks. We found that LTP decayed about twice as fast in the old rats as it did in the young, with the “synaptic memory” lasting 20 days rather than 40. Most importantly, the durability of LTP was correlated with the memory of the correct hole on the circular platform task. In fact, by combining behavior and electrophysiology techniques, we produced the first demonstration that instead of acting as a mere proxy for learning, LTP might actually represent the cellular mechanism by which all memories are created.1
Just one year before I published my work on aging rats, Bruce McNaughton, then at Dalhousie University, demonstrated that for synaptic strengthening to occur, synapses from several neurons needed to converge and be coactive on the target neuron. The finding made perfect sense, since learning often comes from the association of two or more pieces of information, each of which could be carried by an individual neuron. Later experiments also demonstrated that under some conditions, LTP can be more difficult to induce in aged rats, and conversely, that a reduction in synaptic strength—called long-term depression or LTD—is easier to induce in the hippocampus of old rats.2 This may mean that LTD participates in “erasing” LTP, or reducing its longevity, and thus possibly increases forgetting.
By the mid-1980s it was clear that even in normal aging there are subtle changes in the biological processes that underlie memory, and in the relationship between the strength of memory and the strength of the synapses. But the real message of these experiments was that old animals can and do learn. None of the older animals exhibited what could be considered behaviorally to be “dementia,” nor were their biological mechanisms that allow memory traces to be laid down completely dysfunctional.

Aging networks

While there is much to be learned about the physiology of neural systems by direct artificial stimulation, even the mildest currents do not exactly mimic the selective and distributed activity of cells in normal behavioral states. To more realistically understand the aging brain, it is necessary to monitor cell circuits driven by natural behaviors. Around the time that LTP was discovered, John O’Keefe at University College London discovered “place cells” in the hippocampus—a major breakthrough for the field. By simply placing small microwires very close to hippocampal cells, without stimulating them, John and his student Jonathan Dostrovski noted that individual hippocampal cells discharge action potentials only when a rat is at select physical locations as it traverses a given environment.3 The unique property of these place cells is that their “receptive fields,” or the features that make each of these cells fire, are related to specific regions of space.
Infographic: Lost in Space
View full size JPG | PDFTAMI TOLPA (MAZE); CAROL BARNES (COGNITIVE MAPS, SOURCE: NATURE 388/ 17 JULY 1997)
By recording from many individual place cells at once, using a multipronged electrode (the tetrode) developed by McNaughton, and determining which physical locations activated different cells in the brain, it was possible to visualize how the hippocampus constructs a “cognitive map” of the surroundings. If young rats were given one maze-running session in the morning, and another session in the afternoon, the same hippocampal map was retrieved at both time points—suggesting that the pattern of neuronal firing represented the memory of their walking through the rectangular, figure-eight maze. What surprised us was that about 30 percent of the time, when old rats went back for their second run of the day, a different place-cell distribution would appear—as if the older animals were retrieving the wrong hippocampal map.4 Certainly a rat navigating a familiar space with the wrong map is likely to appear lost, or as though it had forgotten its way. But why was the rat retrieving the wrong map?
The possible answer to this question was published in 1998 by Cliff Kentros, now at the University of Oregon. In young rats, Cliff pharmacologically blocked the NMDA receptor, a critical gateway regulating LTP and synaptic strengthening. When he and colleagues used a dose large enough to block the formation of LTP, the cognitive maps of the young rats began to degrade over time in much the same way as observed in aged rats, suggesting that faulty LTP mechanisms may be responsible for map instability in aging.5

Connecting the hippocampal dots

Even though the new multiple tetrode recording method was a large advance over the limitations of recording one or two neurons at a time, these methods were still constrained to sample sizes of ~100 to 200 cells.
One recent advance has allowed us to monitor cell activity on a broader scale, not with electrodes, but by tracking the expression of genes that are rapidly expressed during behavior. Monitoring the expression of one such gene, Arc, during behavioral tests, for example, John Guzowski in my lab developed a method that could report on activity over hundreds of thousands of cells across the brain (the ‘catFISH’ method).6 This large-scale imaging of single cells has been critical for identifying which cells, within which memory circuits, are altered during normal aging.
This technique also allowed us to tease apart which cells might be more susceptible to decline with age. Unlike electrodes that record LTP, which cannot differentiate between different types of neurons, the catFISH method allows us to distinguish between the three primary cell groups within the hippocampus—the granule cells of the dentate gyrus and the pyramidal cells of regions CA1 and CA3. We were able to show that cell-specific gene expression (and therefore cell activity) did not change with age in CA1 and CA3 cell regions, but that the number of granule cells engaged during behavior showed a continuous decline in aging rats, suggesting these cells are a weak link in the aging rat hippocampus.7 Could this also be true in primates?
Scott Small at Columbia University Medical Center helped me answer this question in young and old monkeys. Although MRI methods do not have single-cell resolution, they can provide an indirect gauge of activity over large segments of the brain. Using a variation of standard MRI that measures regional cerebral blood volume (CBV), we monitored the resting brain activity of monkeys ranging in age from 9 to 27 years (equivalent to 27 to 87 human years), and could then relate this brain activation to an individual animal’s performance in memory tests. There were no differences in resting metabolic measures in the areas of the brain that send most of the signals into or out of the hippocampus, nor were there differences in brain activity within CA1 or CA3. But the old monkeys did show reduced activity in the dentate gyrus, similar to what we had found in aging rats. Critically, we observed that the lower the activity in the dentate gyrus, the poorer the memory.7
Scott had observed a similar pattern in an earlier human aging study. However, with human studies there is always a concern that some of the people we assume are aging normally in fact have the undiagnosed beginnings of human-specific neurological disease, such as Alzheimer’s. Confirming the observation in aging animals, which do not spontaneously get this disease, provides strong evidence that the dentate gyrus is a major player in the changes that occur in normally aging mammals.
Furthermore, these data refute the contention that aging is effectively equivalent to an aberrant process like Alzheimer’s disease, revealing that it is in fact a distinctly different neurological process. In contrast to the results showing that aging primarily affects the dentate gyrus, the granule cells of this brain region in Alzheimer’s patients do not show changes (with respect to age-matched controls) until very late in the illness. Instead, it is the cells in CA1 and in the entorhinal cortex that are dramatically affected. Thus, while aging and Alzheimer’s may in some cases be “superimposed,” there is not a simple linear trajectory that leads us all to end up with the disease.

Memory genes

Infographic: The Seat of Memory
View full size JPG | PDFTAMI TOLPA
Presently, the omics revolution is leading us closer to an understanding of individual differences in aging and cognition. One example with respect to memory is a study that used a genome-wide association approach in 351 young adults to identify the single nucleotide polymorphisms (SNPs) most strongly related to memory. The most significant SNP identified was a simple nucleotide base change in the normal cytosine-thymine sequence at a specific location in the KIBRA gene, which encodes a neural protein that had been suspected of playing a role in memory. Those who had the thymine-thymine SNP had the best memories.8 This was further confirmed in an independent elderly population,9supporting the view that this particular SNP in the KIBRA gene predisposed people of any age to have “better memory.” This could be another clue to help guide our understanding of the molecular cascades that support good memory, as the activity of the KIBRA protein may influence mechanisms related to LTP. Could there be a link between KIBRA and age-related memory decline? One way to test this hypothesis was to find a way to manipulate part of the molecular circuit in which KIBRA is involved. Performing just such an experiment in collaboration with my lab, Matt Huentelman at the Translational Genomics Research Institute in Arizona identified a promising compound, hydroxyfasudil, a metabolite of a drug already approved for use in treatment of chest pain, or angina. As predicted, hydroxyfasudil improved spatial learning and working memory in aged rats.10The clinical applications of the drug’s effects on learning and memory are currently being explored.
David Sweatt at the University of Alabama at Birmingham also recently documented DNA methylation changes in response to learning, and was very interested in collaborating with us to determine whether changes in this epigenetic process during aging might explain our data on Arc expression, which is related to LTP formation and learning. Methylation of DNA typically downregulates transcription. After young and old rats performed exploratory behaviors that engaged the hippocampus, the methylation state of the Arc gene in hippocampal cells was, in fact, reduced in both age groups (which allowed more of the Arc mRNA to be transcribed). The difference between young and old animals was that certain cells of older animals, such as hippocampal granule cells, had higher overall methylation levels in the resting state, which resulted in production of less Arc protein during behavior, and the diminished ability to alter synapses via a mechanism such as LTP.11 There are many complex facets of these data, but the results have led us and others to hypothesize that there may well be a number of epigenetic marks that accumulate during aging, and that epigenetic dysregulation may be a fundamental contributor to normal age-related cognitive decline. While the details of exactly how aging affects epigenetic modifications remain to be elucidated, it is at least a reasonable guess that understanding these mechanisms will be critical for future experimental designs aimed at optimizing cognition across the life span. Luckily, these processes are also amenable to pharmacological manipulation.

Aging in the future

Looking back on the rather grim expectations concerning memory and the elderly that were held only a few decades ago, the vision today is very different and much more positive. There are many who live to very old ages with minimal cognitive decline—and certainly no dementia. One particularly interesting study in this regard followed individuals who were 100 years of age (centenarians) at the beginning of the study until the time of their death, monitoring cognitive function and other factors in the “oldest old.” Interestingly, 73 percent of these centenarians were dementia free at the end of their lives (the oldest reaching an age of 111 years).12 Watching the remarkable discoveries in biology over the past half century, one cannot help but look with excitement towards the next groundbreaking findings that are surely in the making. The future holds great promise for the once remote dream of understanding the core biological processes required for optimal cognitive health during aging—and progress in this regard should also provide the needed backdrop for understanding and preventing the complex neurological diseases that can be superimposed on the aging brain.
Carol Barnes is Director of the Evelyn F. McKnight Brain Institute and a Regents’ Professor of Psychology and Neurology at the University of Arizona.
This article is adapted from an upcoming review in F1000 Biology Reports. It will be available for citation at f1000.com/reports (open access).

References

  1. C. A. Barnes, “Memory deficits associated with senescence: A neuro-physiological and behavioral study in the rat,” J Comp Physiol Psychol, 93:74-104, 1979. ↩
  2. C. Norris et al., “Increased susceptibility to induction of long-term depression and long-term potentiation reversal during aging,” J Neurosci, 16:5382-92, 1996. ↩
  3. J. O’Keefe, J. Dostrovsky, “The hippocampus as a spatial map: Preliminary evidence from unit activity in the freely-moving rat,” Brain Res, 34:171-75, 1971. ↩
  4. C. Barnes et al., “Multistability of cognitive maps in the hippocampus of old rats,” Nature,388:272-75, 1997. ↩
  5. C. Kentros et al., “Abolition of long-term stability of new hippocampal place cell maps by NMDA receptor blockade,” Science, 280:2121-26, 1998. ↩
  6. J.F. Guzowski et al., “Environment-specific expression of the immediate-early gene Arc in hippocampal neuronal ensembles,” Nat Neurosci, 2:1120-24, 1999. ↩
  7. S.A. Small et al., “Imaging correlates of brain function in monkeys and rats isolates a hippocampal subregion differentially vulnerable to aging,” PNAS, 101:7181-86, 2004. ↩
  8. A. Papassotiropoulos et al., “Common Kibra alleles are associated with human memory performance,” Science, 314:475-78, 2006. ↩
  9. K. Schaper et al., “KIBRA gene variants are associated with episodic memory in healthy elderly,”Neurobiol Aging, 29:1123-25, 2008. ↩
  10. M.J. Huentelman et al., “Peripheral delivery of a ROCK inhibitor improves learning and working memory,” Behav Neurosci, 123:218-23, 2009. ↩
  11. M.R. Penner et al., “Age-related changes in Arc transcription and DNA methylation within the hippocampus,” Neurobiol Aging, doi: 10.1016/j.neurobiolaging.2010.01.009 ↩
  12. B. Hagberg, G. Samuelsson, “Survival after 100 years of age: a multivariate model of exceptional survival in Swedish centenarians,” J Gerontol A Biol Sci Med Sci, 63:1219-26, 2008. ↩