Aging Impacts Memory For Perceptual, But Not Narrative, Event Details Part 2

Discussion

In the present study, we sought to examine age-related changes in recognition memory for narrative and perceptual information. Younger and older participants viewed an episode of a television sitcom and later completed an old/new recognition test consisting of targets, foils, and similar lure items that tapped into perceptual and narrative domains. Critically, to our knowledge, this is the first study to examine mnemonic discrimination of perceptual information in memory alongside specific narrative details. 

Perceiving information and memory are inseparable. Perceptual information is to obtain information about the external environment through the five senses and then convey it to the brain, and the brain forms memory by storing the information. In other words, without perceptual information, there is no memory.

The relationship between perceptual information and memory can be vividly explained with a simple metaphor: perceptual information is the seed, and memory is the fruit after sowing. Only when information is perceived and an impression is formed in the brain, can the seeds of memory germinate and form a memory.

In addition, perceptual information can also help us better remember learning content. Research shows that understanding and retaining information can be improved by taking in learning content through different modes of perception. For example, visual perception can be carried out through images, videos, pictures, etc., auditory perception can be carried out through audio or voice recording, and tactile perception can be carried out through actual operation perception. Using a variety of perception methods to obtain information can form multiple memory points in the brain and improve the storage and memory of information.

Overall, the relationship between perceptual information and memory is very important. We need to acquire information through various modes of perception, while actively recording and acquiring new knowledge to improve our memory and thinking abilities. In this way, we can better grasp the learning content and improve the efficiency and quality of life and work. It can be seen that we need to improve memory, and Cistanche deserticola can significantly improve memory because Cistanche deserticola is a traditional Chinese medicinal material that has many unique effects, one of which is to improve memory. The efficacy of minced meat comes from the various active ingredients it contains, including acid, polysaccharides, flavonoids, etc. These ingredients can promote brain health in various ways.

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Analyses revealed better performance on basic recognition of repeated targets and novel foils for perceptual compared with narrative trials across age groups. Discrimination of similar lures, however, differed across age groups, with older adults showing a deficit in correctly rejecting perceptual, but not narrative, lures. Importantly, lure discrimination ability was equated across domains in younger adults, suggesting that the perceptual discrimination task is not inherently more difficult. Moreover, older adults performed comparably with younger adults at discriminating highly similar narrative lures from information in the episode.

Our results demonstrate the utility of including measures for more than one type of memory for the same complex stimulus. We adapted a widely used paradigm—the MST—that typically aims to tax pattern separation processes in the hippocampus (Stark et al. 2013, 2019); however, rather than testing solely on perceptual details as previous paradigms have done, we tested detailed recognition of narrative information as well. 

Memory for narrative details is often tested with spoken or written free recall, which is a different and potentially more taxing form of memory retrieval than cued recognition (Craik and McDowd 1987). Some findings showing age-related deficits in recall may be results affected by the difficulty of the task itself. Additionally, recall tests tend to focus largely on narrative details and lessen the focus on perceptual details. The use of a recognition test in our design allowed us to directly assess differences between perceptual and narrative domains while minimizing age-related differences based on the nature of the task. Thus, our results are driven by differences in the information domain (i.e., perceptual and narrative) rather than the format of the test (e.g., recall vs. recognition), which suggests that perceptual and narrative domains may tax distinct cognitive processes.

It has been argued that aging is associated with a loss of detailed memory but a relative preservation of gist (Schacter et al. 1997). This is often operationalized as the retention of central, general features of studied material but the loss of specific (sometimes peripheral) information, resulting in either forgetting or false recognition due to interference (Koutstaal and Schacter 1997; Norman and Schacter 1997; Tun et al. 1998). Broadly in line with this work and prior studies using MST variants (Stark et al. 2013, 2015, 2019), we found an increase in false alarms to lures but a relative preservation of target recognition in older adults. This can be viewed as a shift away from detailed memory in aging. 

Many prior studies suggesting a gist versus detail trade-off have used static images (Stark et al. 2015) or word lists (Norman and Schacter 1997) as stimuli, using false alarms as the key measure. However, continuous events captured by narratives may allow us to tap into distinct mechanisms that go beyond simple visual versus verbal representations. A study by Adams et al. (1997) tested verbal narrative recall of younger and older adults and showed age-related deficits in verbatim details, but that older adults showed a greater tendency toward processing a story’s interpretive meaning. Our results may expand on this phenomenon. Specifically, by testing both simple target recognition and lure discrimination (more taxing of detailed memory representations) across perceptual and narrative domains, our findings suggest that older participants may be more able to retain detailed memory for information that relates to a story’s meaning.

Alternatively, one potential explanation for the relative deficit in perceptual but not narrative lure discrimination among older adults could be an overall difficulty with visual perception. Although we formally included participants with corrected-to-normal vision and ensured they could see the computer screen well, a caveat of this study is that we did not conduct a formal vision test in the laboratory. While visual acuity is sometimes reported to decrease with age, older adults performed similarly to younger adults on the target recognition assessment. There may also be age-related attentional differences beyond low-level visual perception (Verhaeghen and Cerella 2002; Glisky 2007). For example, older adults may simply have attended to the screen to a lesser degree. Although we did not collect pertinent data in this study (e.g., eye tracking) and cannot speak to this directly, future studies in this vein can assess the role of attention and top-down control.

Our findings are in agreement with studies investigating interference in memory about visual information, revealing a deficit specifically for lure discriminability but not target recognition (Yassa et al. 2011b; Toner et al. 2013; Stark et al. 2015; Foster and Giovalleno 2020; Chamberlain et al. 2022). Similar to this study, this may drive a poorer ability to pattern separate similar information in older adults. Our findings may expand on this by demonstrating that this specifically targets perceptual, but not narrative, lures. 

Although we explicitly tested fine-grained details across both domains and took steps to equate task difficulty in younger adults (see the Supplemental Material; Supplemental Table S1), highly detailed memories may be inherently more likely to tap into perceptual representations (Robin and Moscovitch 2017). Moreover, in the context of this study, conditions of narrative lure discrimination may rely on gist-based or more semantically driven representations in older adults. Thus, to some extent, our findings may reflect age-related differences in processing gist versus detailed information with age. In line with this, it has been recently argued that an age-related shift from detailed to gist representations may be driven by multiple factors beyond cognitive decline, including changes in priorities and goals associated with aging (Grilli and Sheldon 2022).

Importantly, the cognitive processes targeted by our study may rely on differentially vulnerable neural mechanisms in the aging brain. Memory representations extend beyond the hippocampus into larger cortico–hippocampal networks, which may differ based on information type. According to one well-supported view, content in memory is dissociated into a posterior–medial (PM) system that supports spatiotemporal, contextual, and situational details and an anterior–temporal (AT) system that tracks items, objects, and individual people (Ranganath and Ritchey 2012; Ritchey et al. 2015; Reagh and Ranganath 2018). 

In this framework, the PM system would more preferentially support narrative details, whereas the AT network may support more perceptually driven information. Given that narrative structure, mediated by the PM network, provides a way to deeply encode information by allowing us to bridge overarching themes and create meaningful associations, we anticipated that older participants would perform better at recognizing narrative details aided by these associative anchors. However, differences in basic recognition performance based on the test domain were driven by better (not worse) performance on perceptual information. Importantly, this effect was present across age groups, suggesting that there may be other reasons such as visual salience or difficulty level across domains that underlie this result in terms of basic recognition memory. Critically, age-related discrimination deficits were limited to perceptual lures despite perceptual target recognition performance being better across both groups than narrative recognition. This further suggests that the selective deficits observed in older adults at perceptual, but not narrative, lure discrimination did not arise as a mere function of task demands differing.

Although this study did not examine age-related pathology, this pattern of results may provide insights into the integrity of the aging brain. Increasing evidence suggests that PM and AT systems are differentially vulnerable to age-related pathology. Accumulation of tau is associated with impairment of episodic memory processes and is strongly predictive of Alzheimer’s disease. Early stages of Alzheimer’s disease are thought to originate in AT regions, as tau depositions accumulate in these areas (Braak and Braak 1997). Increased tau depositions coupled with amyloid plaques later spread in the PM regions, resulting in the progression of Alzheimer’s disease (Jagust 2018; Leal et al. 2018). 

Our results are in line with other findings suggesting that AT-mediated processes may be more generally vulnerable in aging (Reagh et al. 2016, 2018). Together, findings of this sort suggest an increasing vulnerability of PM-mediated processes in aging, perhaps especially in Alzheimer’s disease. Although our sample does not include formally diagnosed dementia patients, our study may provide insights into future studies related to Alzheimer’s disease. Exploratory analyses that incorporated a contrast of cognitive ability indicate that declines in perceptual lure discrimination were largely driven by older adults with poorer global cognitive ability (see Supplemental Material; Supplemental Fig. S2A, B). Future work can examine this in more detail.

In sum, our study used a mnemonic similarity task applied to a naturalistic stimulus to show age-related deficits in perceptual, but not narrative, lure discrimination. In line with several existing studies, we found domain-selective recognition deficits as a function of aging (Reagh et al. 2016, 2018; Güsten et al. 2021). These data indicate that domain selectivity of age-related memory deficits extends to memory for continuous, lifelike information beyond simple laboratory experiments. Perceptual details, which are not anchored by narrative associations, may be particularly vulnerable in the context of aging. Additionally, our findings suggest that cognitive decline may amplify lure discrimination deficits. Testing memory for different aspects of experiences may offer important insights into memory ability in healthy and pathological aging, and a naturalistic approach offers us insights into how these processes operate in real-world situations.

Materials and Methods

Participants

Forty-two participants were recruited from the Davis, California, community: 21 younger adults (M = 20.04, SD = 1.81; range = 18– 25; 20 female) and 21 older adults (M = 73, SD = 7.43; range = 61– 93; 10 female). The study was approved by the Institutional Review Board of the University of California, Davis, and all participants provided written consent before participating in the study. Younger adults were recruited from a pool of undergraduate students enrolled in psychology courses at the University of California. Inclusion criteria for younger adults included normal hearing, normal or corrected-to-normal vision, no history of major neurological or psychiatric illness, and English as a native language. Older adults were recruited from the Davis community through online advertisement, flyers, and word of mouth. 

Older participants were initially contacted by phone or e-mail for a prescreening interview. Inclusion criteria for older adults were the same as for younger adults, except the requirement of English as a native language was relaxed to include individuals who began fluency in English before age 5. All participants were naïve to the stimulus, except one younger participant (i.e., who reported having seen Curb Your Enthusiasm before the study). Results remain the same even after the exclusion of the nonnaïve younger participant (see the Results). No older adults recruited for the study had formal diagnoses of cognitive or neurological disorders, including dementia or mild cognitive impairment. However, a portion of our older adult sample exhibited scores on neuropsychological tests below standardized cutoffs, which we leveraged for exploratory analyses (see Supplemental Material; Supplemental Tables S2, S3).

Materials, design, and procedure

Older participants completed the following neuropsychological tests to assess for cognitive impairments: Craft21 recall immediate, Craft21 recall delayed, Montreal Cognitive Assessment (MoCA), and Multilingual Naming Test (MINT) (see Table 1). Briefly, Craft21 assesses recall for narratives, MoCA coarsely assesses cognitive ability, and MINT assesses the ability to name objects in English. Older and younger participants viewed a 26-min episode of a television show (HBO’s Curb Your Enthusiasm, S01E07: “AAMCO”) and then completed a free recall task, a recognition task, and an event segmentation perception task (not included here). For the recall task, participants were instructed to recall everything that they could remember about the episode in as much detail as possible. Manually scored recall (Levine et al. 2002) resulted in no age-related differences in overall recall performance (see Supplemental Table S2). The present analyses mainly focus on recognition memory task performance.

Participants completed two recognition tasks based on narrative or perceptual details, wherein the narrative recognition task consisted of identifying sentences as old or new via button press, and the perceptual recognition task consisted of identifying images as old or new via button press. We aimed to test recognition memory for highly specific information by adopting a mnemonic similarity task approach. Briefly, in addition to old/new recognition, this recognition task variant includes similar lure trials that induce mnemonic interference. Critically, sentences and images were either studied targets (described or depicted moments from the video encoded), similar lures (moments described or depicted as being similar to the video encoded but differing subtly from the video encoded), and novel foils (described or depicted moments not from the video encoded). 

An example of a lure in the narrative test domain is “Larry offers a man on the street a ham sandwich” when the correct answer is “Larry offers a man on the street a tuna sandwich” (see Supplemental Fig. S1A). Similarly, an example of a lure of the perceptual test domain is an image of Larry at a similar auto shop from a different episode (S01E08) (see Supplemental Fig. S1B). An example of narrative and perceptual test domain includes plausible descriptions or depicted moments such as “Larry goes to see Dr. John Lynch on the third floor of the medical building” (S11E04). Each recognition task consisted of 30 targets, 30 lures, and 30 foils. The order of narrative and perceptual recognition tasks was counterbalanced and pseudorandomized such that odd-numbered participants completed the narrative recognition task first followed by the perceptual recognition task, and even-numbered participants completed the perceptual recognition task first followed by the narrative recognition task.

A key step in comparing task conditions across age groups is to ensure that those conditions do not merely reflect differences in difficulty. To address this, we gathered ratings for each test stimulus from a sample of younger adult participants. Twenty-three participants (M = 20.14, SD = 0.94; range = 18–22; 14 female) watched the television episode used in the main study and were later shown a series of descriptions and images. For each target, foil, and lure trial, participants rated the difficulty of correctly accepting or rejecting each image or description on a scale of 1–5. In addition to rating the difficulty, participants were notified that lure images or descriptions were not from the encoded video and were instructed to rate their similarity to the encoded video. Difficulty and similarity ratings for narrative and perceptual domain and trial type were not statistically different (see Table 2; Supplemental Material). Although we cannot completely rule out differences in difficulty, this pilot sample indicates that the narrative and perceptual test domains are comparably challenging in younger participants.

Analyses

The mean proportion of correct responses for each trial type was calculated (see Table 3). Recognition performance was scored as the proportion of targets, lures, and foils endorsed as being new or old. Targets were scored as hits if endorsed as old and as misses if endorsed as new. Lures and foils were endorsed as correct rejections as new and as false alarms if endorsed as old. Additionally, target recognition was assessed in terms of d′ values (z[target hit rate] − z[foil false alarm rate]) derived from signal detection analysis. Older and younger adults’ recognition performances were compared using pairwise independent sample t-tests within each trial type. 

Additionally, we calculated a lure discrimination index (LDI) (Stark et al. 2013, 2019) for each subject (p[new|lure]−p [old|foil]). Data were analyzed using repeated measures ANOVAs, and post-hoc contrasts were corrected for multiple comparisons using the Bonferroni method. Although there were no age differences in overall recall performance, additional linear mixed-effects model analyses were conducted to ensure that overall memory ability did not account for recognition performance differences. Recall performance was entered as a random covariate into a linear mixed-effects model predicting target recognition performance [d′ ∼age group × test domain + (1|recall performance)] and lure discriminability performance [LDI∼age group × test domain + (1| recall performance)]. Statistical analysis was performed in R (version 4.0.3, https://www.r-project.org) using the afex package (https://github.com/singmann/afex).

Data Deposition

The full stimuli for the materials used in the present experiment, anonymized data files, coded data, R Markdown files, and Jupyter Notebook files containing the analysis scripts are available on Open Science Framework (https://osf.io/3qe9w) and GitHub (https://github.com/aidelarazan/curbage_recognition).

Competing interest statement

The authors declare no competing interests.

Acknowledgments

We thank Alexander Garber, June Dy, Elena Markantonakis, and Ryan Bugsch for their help with data collection. We thank Erwin M. Macalalad, Brendan I. Cohn-Sheehy, and members of the Complex Memory Laboratory and Dynamic Memory Laboratory for helpful discussions and support. This material is based on work supported by the National Institute on Aging under grants 1R03AG063224-01 and T32AG050061 and the National Science Foundation under grants DGE-2139839 and DGE-1745038.

Author contributions: Z.M.R. conceived the study. A.I.D., C.R., and Z.M.R. performed the methodology. A.I.D. and Z.M.R. performed the investigations. A.I.D. and Z.M.R. analyzed the data. A.I.D. visualized the data. A.I.D., C.R., and Z.M.R. wrote, reviewed, and edited the manuscript. Z.M.R. supervised the study.

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