Discussion

The results of this experiment support the hypothesis that age-related processing speed

deficits contribute to the PCB in aging. The analysis of old/new recognition and the overall lure

discrimination index replicate a wide body of literature showing that OAs experience a decline in

lure discrimination, despite maintaining similar performance on old/new recognition (e.g., Stark

et al., 2015; Toner et al., 2009). This result was true regardless of the rate of presentation

manipulation, suggesting that giving OAs more time does not improve the memory changes

performance changes across degrees of rotation, a complementary, but slightly different result

was found. The core result, that OAs show impairments in lure discrimination, was observed.

When YAs and OAs were given the typical rate of presentation (i.e., 2.5 sec) they exhibited

similar rates of saying “old” to trials that were exact repeats, yet OAs exhibited a decline in their

ability to make fine grain discriminations between previously encountered stimuli and stimuli

that were rotated.

The results also revealed that OAs’ and YAs’ ability to efficiently pattern separate was

significantly impacted by the amount of time given to study a stimulus. This finding would not

be surprising if the manipulation only affected participant’s ability to discriminate between old

and new trials. The fact that providing OAs more study time uniquely improved their ability to

make fine grain discriminations between previously studied images and the rotated versions

presented at test, suggests that the PCB can be modulated by processing speed changes that occur

with age. Further, when YAs’ were given less study time, their performance was highly similar

to OAs. Not only can OA’s performance be improved to mirror YA’s, YA’s performance can be

modulated to mirror that of OA’s. These results are at direct odds with the notion that the PCB in aging cannot be “overcome” (Stark et al., 2015). The hypothesized change of performance based

on study time provides compelling evidence that the PCB in aging is not solely based on

mnemonic changes associated with age. The sensitivity of pattern separation to rate of

presentation indicates a much more complex picture of how mnemonic representations are

formed, retrieved, and how aging impacts these processes.

In the context of cognitive aging theories, this experiment adds to a body of literature

suggesting that age-related memory changes share variance with measures of processing speed

between measures of processing speed (i.e., Trails A and B) and participants’ pattern separation

performance. While this result fits well within the processing speed literature, it is at odds with

some of the findings in the pattern separation literature. Toner et al. (2009) conducted an object

pattern separation task and also collected several measures of cognition in OAs. Their results

revealed only one significant correlation between performance on lure trials and letter

sequencing (i.e., a task similar to Trails A, but using letters). No significant correlations were

found between other measures of processing speed that were collected. These results suggest that

processing speed shares a minimal relationship with PS abilities, yet the results from the current

experiment suggests that processing speed is intimately related to PS. First, there are many

differences in the way the correlations were calculated. Whereas the current study used slopes, or

the change in performance across as well as average lure trial performance, Toner et al. (2009)

used average performance across all lure trials. While correlations were observed with lure trial

performance, these relationships were weaker than the correlations with slope. Second, Toner et

al. (2009) collected these measures on only 20 older adults and, therefore, likely had

significantly less power to find the effect. Despite these issues, even the non-significant

correlations were in the same direction. Therefore, the correlations found in this experiment

between processing speed measures and performance on the mnemonic similarity task adds to

our understanding of what may mediate age-related changes in pattern separation.

The current experiment also adds to the pattern separation literature by providing

empirical evidence that memory processes required to support highly detailed discriminations are

significantly influenced by processing speed changes. While memory declines with age, this

experiment shows that the declines in memory as evidenced by the mnemonic similarity task are

speed that occurs with age. It also suggests that even in YAs, pattern separation processes require

time to form strong mnemonic representations. The importance of this point should not be

understated, as understanding how time interacts with pattern separation processes will be a

critical next step in building knowledge on the PCB in aging, as well as memory functions in

general. It is possible that given even greater study periods (e.g., 7.5 sec), OAs may fully recover

mnemonic discrimination performance. If this is found, then it would suggest that PS processes

are not the cause of memory changes in mnemonic discrimination and that the PCB in aging is

simply a byproduct of age related slowing. This result would fundamentally alter the memory

related theories associated with aging. However, this result is unlikely. While greater time at

encoding improves mnemonic discrimination on this task, there is ample evidence to support the

notion that aging causes neural changes in mnemonic processes that support episodic memory

function, and thus, impairments are likely to be found even if encoding times longer than five

seconds are used.