This study provides evidence that there is a behavioral memory deficit with aging that can be characterized as a shift in bias from pattern separation to pattern completion. This behavioral deficit may not be detected in typical recognition tasks that do not tax pattern separation, as evidenced by our participants' unimpaired performance on novel and repeated items. A recent report by Toner and colleagues also observed similar behavioral results (increased probability of calling lure items “old”) in older adults using the same task (Toner et al., 2009
). Consistent with the computational models and the animal studies, older adults are more biased towards pattern completion at the expense of pattern separation. The additional behavioral analysis afforded by the normative similarity ratings in Experiment 2 further suggests that the pattern of impairment accurately maps onto the predictions of the computational model. We found that older adults require a larger degree of dissimilarity in the input before separation can occur (the inflection point in the tuning curve is shifted to the right compared to the young). Critically, this was not simply due to an effect of task difficulty, since the significant interaction across conditions L1 through L5 suggests that the age group difference was smaller in the most similar lures (L1) than the most dissimilar lures (L5). We also found no such age differences in a perceptual similarity/working memory version of the same task. Here, it is important to note that although performance on lures was not as high as performance on targets and foils, there was no difference among groups across any of the lure bins. This strongly suggests that although perceptual similarity does seem to have a general modulatory effect on performance on this task, the aging effect is not due to perceptual processing deficits but rather due to deficits in mnemonic abilities.
One pertinent question is how much change in input is required for older adults to separate in comparison to young adults. In order to address this question several factors must be considered. First, our experiment used simple everyday objects. Separation bias is quite likely different for different stimulus classes, e.g. scenes or faces or abstract figures. Although we hypothesize that the pattern of the group difference will overlap across stimulus classes, the exact amounts of change in input will likely vary. Additional experiments are currently being conducted in our laboratory to more directly address this question. Second, the relative emotionality of the stimuli is an important factor in how vividly they are remembered at least in part due to the amygdala's influence on hippocampal encoding (c.f. McGaugh, 2004
for review) and thus may interact with participants' bias to separate. This was not assessed in the current study but is an important future research direction. Finally, in order to derive a quantitative measure of relative or absolute change required for older adults to separate, we would require several variants (morphs) of each stimulus to derive this value for specific stimuli. This analysis was not feasible in the current study, as it would require a large number of new stimuli and hundreds of additional participants. Nevertheless, we can reasonably infer based on the current results that older adults require larger
amounts of change in input across a wide range of stimulus similarity in order to successfully separate.
Previous studies have observed increased levels of activity in the CA3 of the aged rats that also show impairments in pattern separation (Wilson et al., 2003
; Wilson et al., 2005a
; Wilson et al., 2005b
; Wilson et al., 2006
). Here, we provide converging evidence from the human for a link between dysfunctional CA3 hyperactivity and the behavioral deficit. Overall, on the trials in which older adults were able to behaviorally separate and call lure items “similar”, they exhibited greater activation in the CA3/DG region of the hippocampus (relative to when they called lure items “old”), consistent with findings in the rodent. One notable difference, however, was that hyperactivity in the rodent CA3 was noted during free exploration of novel and familiar environments and was not linked to a specific task or condition. Since functional MRI is contrastive in nature, the direct analog of place cell recordings was not feasible. Instead, we selected a contrast that is heavily weighted towards separation to assess CA3's BOLD activity.
On a network level, hyperactivity is likely the result of diminished inhibitory input into the CA3 (Geinisman et al., 1992
), which normally regulates the recurrent auto-associative collaterals, an excitatory input that comprises the majority of synapses onto the CA3 pyramidal neurons. For example, even a modest reduction in cortical input to CA3 and the dentate gyrus could alter the balance of excitation and inhibition in the CA3 region (Smith et al., 2000
; Burke and Barnes, 2006
). Additionally, cholinergic modulation by the medial septum, which is believed to be involved in the switching between recall and storage modes in the hippocampus (Hasselmo et al., 1995
; Hasselmo, 2006
), is decreased with aging (Sugaya et al., 1998
; Nicolle et al., 1999
). Overall, CA3's disinhibition and subsequent elevated activity could be the underlying mechanism by which computational bias shifts from separation to completion. Although one cannot assess this with any degree of certainty using BOLD fMRI, the results from animal and human work are consistent with this account.
A recent study by Miller et al. (2008a)
in healthy older adults demonstrated that low-performing older adults activated their right hippocampus to a greater extent than young or high-performing older adults. This activity was found on successful encoding trials (relative to unsuccessful encoding trials), suggesting that hippocampal hyperactivity may be necessary for those individuals to successfully perform the task, perhaps as part of a compensatory mechanism. While such a “compensatory” account may at first appear to be in conflict with the “dysfunctional” account, these ideas are not mutually exclusive. The Miller et al. results are actually quite consistent with ours and suggest that although there may be an attempt to compensate, individuals showing these hyperactive patterns do not perform as well on the task overall. According to this view, hyperactivity is an index of network dysfunction that does not provide effective compensation. This would be consistent with the rodent studies and with the current computational model of aging. It is also worth nothing that negative correlations between the extent of CA3/DG activity during the separation condition and participants' behavioral separation bias were observed in our study, further suggesting that increased CA3/DG activity is an index of impairment. However, since within-group correlations were not quite significant we hesitate to make strong conclusions on the basis of these correlations. Further investigation with larger samples is needed to fully elucidate this brain-behavior relationship.
Our results are also generally consistent with other age-related mnemonic findings in the literature. For example, older adults typically do not perform as well as young adults on tasks that require the formation of new episodic memories (Craik and Simon, 1980
; Small et al., 1999
; Hedden and Gabrieli, 2004
; Hedden and Gabrieli, 2005
), spatial memory and navigation (Newman and Kaszniak, 2000
), and contextual source memory (Henkel et al., 1998
). Norman and O'Reilly (O'Reilly and Norman, 2002
; Norman and O'Reilly, 2003
) argue that rich contextual processing such as that required for the above tasks places larger demands on pattern separation, and thus separation-related impairments can lead to the differences in behavioral performance observed. Another pertinent finding in the literature is a decrease in recollection and a concomitant increase in familiarity when resolving recognition tasks (Jennings and Jacoby, 1997
). Failure to recollect and relying instead on familiarity or “gist” representations can be thought of us as a combination of poor pattern separation during encoding and a shift to pattern completion during retrieval. Concepts such as separation and completion are not orthogonal to traditional ways to think about memory and related dissociations (e.g. recollection vs. familiarity, source vs. item memory), but serve to further specify them and are largely consistent with their predictions.
The current investigation has several advantages over previous studies of the MTL in aging. First, by using high-resolution functional MRI, we are capable of detecting activity in hippocampal subfields with a high degree of specificity. For example, both our study and the Miller et al. study found hyperactivity in the right hippocampus, however our high-resolution methods are able to further localize this activity with greater precision in the CA3/DG region of the hippocampus. Second, our cross-participant alignment technique focuses its power on our particular regions of interest and can achieve over 90% overlap across participants in many cases. Traditional fMRI studies that use a standard alignment technique such as SPM's normalization, which we have recently shown only results in 40-50% overlap in the hippocampus (Yassa and Stark, 2009
), will underestimate or in some cases completely miss hippocampal activity (Stark and Okado, 2003
; Miller et al., 2005
; Kirwan et al., 2007
). Third, the experimental manipulation taps into a specific function of the hippocampus and shows a clear behavioral deficit in older adults. For example, if the task were a typical Yes/No recognition task (as is often the case with fMRI recognition tests), no behavioral deficit would have been observed. Fourth, the contrast selected for examination in this study (the one showing hyperactivity) is immune from baseline differences between groups which could easily contribute to increases or decreases in BOLD response. A number of studies (Small et al., 2004
; Ances et al., 2009
; Fleischer et al. 2008
) have now shown that increases or decreases in BOLD response could easily arise in comparisons across groups and regions as an artifact of basal state factors such as metabolic rate and neurovascular coupling. In our study, we chose a contrast comparing two types of responses to the same stimuli (i.e. lures called “similar” minus lures called “old) in order to investigate differences that are free from baseline effects. Although this is a notable strength of our design, it is possible that basal factors may interact with task conditions in a way that would induce artificial hyperactivity on such a condition, however the latter possibility is an unlikely alternative. Future research using calibrated functional MRI may shed light on this issue (Davis et al., 1998
We quantified stimulus similarity based on actual participants' memory performance. We feel this is a much more objective way to assess the relevant
similarity in question – mnemonic similarity, than asking participants to rate stimulus pairs on a Likert scale for example. One potential question that arises is why we did not use these ratings to sort fMRI trials post hoc
and examine the BOLD activity the same way we did behavior. We argue that in other designs it would be informative to sort the fMRI trials this way, but it was not ideal in the current study. In an overt recognition memory task, such as the one used here, separation and completion can both occur across many different trial types. For example, when a participant is asked to judge whether an item was seen before or if it was a similar item that was actually seen before, recall of the previous item's presentation may be used to correctly reject the item by saying “similar” and not “old” (a “recall to reject” strategy). Both “old” and “similar” responses to lures likely involve some amount of pattern completion. However, the load on separation is higher in the “similar” trials than in the “old” trials (partly due to explicit demands in the task). Although each of these trial types likely reflects a mixture of processes, the contrast between “similar” and “old” responses to lures should be selective for pattern separation. Although this is not a process-pure approach, we opted to use it in order to assay memory performance in the same task. For one to independently assess the effect of mnemonic similarity on hippocampal activity and be able to detect the sharp transition associated with separation, the task would be better administered as an incidental encoding task similar to our previous study (Bakker et al., 2008
), so that contamination from incidental recall during rejection of lure items is avoided. However, assessing performance during the incidental task would not have been possible (and, given the automatic nature of encoding and retrieval, even the incidental approach is not entirely process-pure).
One notable limitation of our study is the inability to functionally distinguish between the CA3 and the dentate gyrus, even in our high-resolution protocol. Although both regions are thought to play a role in pattern separation, recent evidence from rodent studies suggests that the mechanisms are different (Leutgeb et al., 2007
) and that the dentate is the primary source of separation signals when changes in the input are small. Work by the Tonegawa lab (McHugh et al., 2007
) has also shown that NMDA receptor knockout in dentate granule cells results in selective deficits in dissociating similar contexts (stressing pattern separation) but not in contextual fear conditioning, providing further evidence that the dentate is the source of the separation signal in the hippocampus. In the context of the aging brain, a large literature has shown that dentate granule cells are particularly vulnerable to age-related impairment (Gazzaley et al., 1996
; Moreno et al., 2007
; Penner et al. 2010
; Small et al. 2002
; West, 1993
; see also recent review by Burke and Barnes, 2010
). These studies stress the important distinctions between the dentate gyrus and the CA3 region, especially in the context of the aging brain. Indeed, the rodent model we test in this study makes different predictions for the two regions (namely a reduction in activity in the dentate, and an increase in the CA3). Dissociating the two regions using functional MRI may be difficult at this time, however it is possible that future studies with high-resolution imaging may be able to distinguish BOLD signals from these two regions and find evidence consistent with their hypothesized computations. At the moment, resolution limitations have forced us to group the two and we are unably to functionally dissociate them.
It is also worth mentioning that since our older adult sample had a mean age of 75, some participants could be characterized as “old-old”. One important question that remains to be answered concerns the nature of these age-related changes, their time of onset, and their progression. Although the current investigation does not allow us to directly answer this question, future investigation using a complete lifespan approach will be necessary to fully understand the nature of age-related change.
In conclusion, we present evidence that older adults show impairments in behavioral pattern separation, and tend to shift into using pattern completion to resolve a memory task. This shift can be further characterized as an increased requirement for dissimilarity before separation can successfully occur. We also show that hippocampal circuitry is altered in the course of aging, such that the CA3 and dentate regions exhibit increased activity during trials loaded on pattern separation. This is consistent with recent work in the rodent as well as computational models of neurocognitive aging. It also may also be a feature that can dissociate normal aging from disease states such as Alzheimer's disease. For example, recent work suggests that CA1 place field physiology is affected in AD transgenic mice (Cacucci et al., 2008
), in contrast to the CA3 place field changes observed in aged rodents. Future studies should focus on the CA3/dentate region as a potential locus of change that may underlie age-related memory deficits, and attempt to understand how this is different in the course of dementia.