Folville-2022-I Remember It Like It Was Yester Part 1

Abstract

It has been frequently described that older adults subjectively report the vividness of their memories as being as high, or even higher, than young adults, despite poorer objective memory performance. Here, we review studies that examined age-related differences in the subjective experience of memory vividness. By examining vividness calibration and resolution, studies using different types of approaches converge to suggest that older adults overestimate the intensity of their vividness ratings relative to young adults and that they rely on retrieved memory details to a lesser extent to judge vividness. We discuss potential mechanisms underlying these observations. 

Objective memory and memory are two different concepts, but there are some connections between them. Objective memory refers to people's ability to remember and recall facts and details, while memory refers to people's ability to store information in the brain and recall it at any time.

Research has found that there is a certain relationship between objective memory and memory. Typically, people who are better able to retain objective memories are likely to also have stronger memories. This is because, in the process of maintaining objective memory, people need to continuously strengthen the neural connections in the brain, which can improve the brain's memory ability.

How to improve objective memory and memory? First, getting enough sleep and reducing stress can enhance your brain's memory capabilities. Secondly, engaging in cognitive training and recreational activities can help people maintain the flexibility of their memory and objective memory. Finally, diet and exercise are also key factors in maintaining memory and objective recall.

In short, objective memory and memory are related to each other, and they both play a very important role in life. We should actively improve our objective memory and memory, and pay more attention to maintaining brain health in our lives. It can be seen that we need to improve our memory. Cistanche deserticola can significantly improve memory because Cistanche deserticola is a traditional Chinese medicinal material with many unique effects, one of which is to improve memory. The efficacy of minced meat comes from its various active ingredients, including acid, polysaccharides, flavonoids, etc. These ingredients can promote brain health in various ways.

Click know 10 ways to improve memory

Inflation of memory vividness about the richness of memory content may stem from age differences in vividness criterion or scale interpretation and psycho-social factors. The reduced reliance on episodic memory details in older adults may stem from age-related differences in how they monitor these details to make their vividness ratings. Considered together, these findings emphasize the importance of examining age differences in memory vividness using different analytical methods and they provide valuable evidence that the subjective experience of remembering is more than the reactivation of memory content. 

In this vein, we recommend that future studies explore the links between memory vividness and other subjective memory scales (e.g., ratings of details or memory confidence) in healthy aging and/or other populations, as it could be used as a window to better characterize the cognitive processes that underpin the subjective assessment of the quality of recollected events.

Introduction

The subjective experience of remembering refers to the phenomenological experience accompanying the retrieval of a past event in episodic memory (Tulving, 1972, 2002). Mentions of the phenomenological experience accompanying the reminiscence of the past can already be found in the philosophical literature of the last century. Philosophers such as Russell, Malcolm, and Smith notably mentioned that, relative to perception, the mental images constituting one’s recollection of the past are dim, unclear, sketchy, and simplified (see Brewer, 1999, for a summary). The phenomenology of memory retrieval can be operationalized with various measures concerning several dimensions of reminiscence: clarity of visual details, colors, sounds, order of events, the spatial location of people and objects, and the thoughts and feelings experienced during encoding (Johnson et al., 1988; Johnson et al., 1993). 

Yet, in episodic memory studies, participants are usually asked to introspectively rate the sharpness of their mental representations using memory vividness ratings. Vividness can be defined as the quality of being clear, brightly colored, and detailed in one’s mind (Cambridge University Press, n.d.). Vividness correlates with visual details, the clarity of a representation, or its intensity (Tooming & Miyazono, 2020). This implies that the level of vividness of mental representations can strongly vary from one memory to another, with some recollected events being rich and intense while others are vague or blurry.

Although progress in the understanding of the cognitive underpinnings of memory vividness has been made during the last decades (Simons et al., 2020, 2021), much is still to be discovered. Notably, it remains unclear to what extent the intensity of the subjective experience of vividness maps onto the memory content on which it is based so that it can be considered a reliable index of the richness of the retrieved episode. This question has notably arisen following the striking observation that older adults sometimes claim that they experience a vivid and intense sense of recollection when remembering previous episodes while, at the same time, the content of what they recollect is objectively impoverished (Folville, D’Argembeau, et al., 2020; Folville, Jeunehomme, et al., 2020; Hashtroudi et al., 1990; McDonough et al., 2014; St-Laurent et al., 2014). In the cognitive aging literature, previous studies have examined age differences in vividness using various approaches (e.g., laboratory stimuli, autobiographical memory, and future thinking). 

Despite their methodological differences, these studies are usually lumped together, thus leading to the conclusion that older adults inflate their vividness ratings, but a careful comparison of their outcomes is currently lacking. Here, we review recent research that has investigated the subjective experience of memory vividness in normal aging, in an attempt to summarize the current state of knowledge.

If their memories are objectively less detailed than those of young adults, what kind of information/source do older adults take into account to make their subjective memory vividness ratings? Different theoretical perspectives have tried to address this question, mainly by invoking age-related changes in cognitive or memory abilities (Folville, Bahri, et al., 2020; Folville, D’Argembeau, et al., 2020; Johnson et al., 2015; Mitchell & Hill, 2019). However, these explanations have never been considered together, so it is currently unclear whether they can fully account for the observed age differences in memory vividness. In the present review, we discuss the strengths and weaknesses of various theories that may explain age differences in memory vividness, and we identify gaps that future work should fill.

The observation that older adults report strong vividness ratings in the face of poor objective memory performance has also questioned the taken-for-granted assumption that vividness just corresponds to the amount of information available in memory (Renoult & Rugg, 2020). The discrepancy between memory vividness and memory details in aging raises the possibility that the subjective experience of memory vividness is supported to some extent by other cognitive mechanisms than memory retrieval processes. We, therefore, assume that studies examining age differences in memory vividness could be used as a window to identify the cognitive mechanisms that underpin memory vividness, thus providing critical inputs to feed theoretical accounts of episodic memory functioning.

In the following sections, we will first consider evidence relating to the cognitive basis of the subjective experience of memory vividness in young adults. Then, age-related differences in cognition and episodic memory functions will be described before reviewing studies that examined age-related differences in subjective memory vividness. Next, the cognitive and environmental factors that influence how older adults make their vividness ratings will be described. To further characterize how older adults make their ratings, age differences in other subjective memory scales than vividness will be briefly described. Finally, the implications of this research for the study of the subjective experience of vividness will be outlined and some avenues for future investigation will be proposed.

The cognitive bases of memory vividness

Vividness has been widely studied within psychology and philosophy, but the experiential qualities on which a sense of vividness might be based are still a matter of debate (Langkau, 2021). According to recent philosophical accounts, vividness corresponds to the amount of sensory or perceptive information contained in one’s mental image (Langkau, 2021; Tooming & Miyazono, 2020). In psychology, it often relates to the clarity and salience of a mental image (D’Angiulli et al., 2013; Fazekas et al., 2020). When asked to define the characteristics of vividness, people mention the presence of colors, rich details, and well-defined shapes (Cornoldil et al., 1991). 

Consistent with these accounts are results from fMRI investigations showing that the intensity of vividness is related to neural (re)activation in primary and high-level visual areas both when imagining and remembering stimuli (Bone et al., 2020; Cui et al., 2007; Dijkstra et al., 2017; St-Laurent et al., 2015). Regardless of whether it pertains to mental imagery or episodic memory, the intensity of the subjective sense of vividness might thus be determined by the amount of sensory or perceptual information available in the mind. To make a vividness rating, the visual appearance of the mental image may be compared with the clarity of an experience of actual perception (D’Angiulli et al., 2013). Mental imagery is thus a critical component of vividness (Marks, 1973). Consistently, it has been shown that vividness is associated with brain activity in the angular gyrus (Tibon et al., 2019) and precuneus (Richter et al., 2016), brain regions respectively involved in the online maintenance of sensory features (Humphreys et al., 2020; Yazar et al., 2012), and in mental imagery processes (Cavanna & Trimble, 2006; Fulford et al., 2018).

But how does one judge that a mental image is vivid and intense, or on the contrary, vague and blurry? It is considered that such decisions are determined by metacognitive mechanisms. Metacognition refers to one’s knowledge about one’s internal thoughts and cognitive functioning (Flavell, 1979; Fleming, 2010; Fleming & Dolan, 2012). Metacognitive judgments typically require participants to monitor the accuracy of their decisions, and they are influenced by participants’ knowledge, expectancies, and prior experience (Dobromir Rahnev et al., 2015; Sherman et al., 2015; Sherman et al., 2016). In the literature, metacognitive judgments have often been studied using memory confidence measures. 

Memory vividness and memory confidence are both metacognitive judgments that are expressed using Likert (usually from 0/1 to 5 or 7) or visual analog (from 0/1 to 100) scales during memory retrieval. Like memory vividness, memory confidence is thought to be based on the quality of the recollected memory trace (Wong et al., 2012). It is therefore not surprising that these concepts are usually found to correlate in episodic memory tasks (Robinson et al., 2000; Sharot et al., 2007) and that they seem to be supported to some extent by similar brain regions (Simons et al., 2010; Tibon et al., 2019; Yazar et al., 2014). In the metacognition domain, more attention has been given to memory confidence than vividness, however. Therefore, although memory vividness is the topic of interest in the current review, measures of metacognitive confidence judgments will be first described in this section.

Accuracy of metacognitive confidence is usually assessed using two measures: calibration and resolution. Confidence calibration quantifies the extent to which the intensity of confidence ratings matches the probability of memory accuracy and it provides insights as to how participants anchor their judgments on the response scale (i.e., metacognitive bias; Fleming & Lau, 2014), thus revealing under- or over-confidence in participants’ answers (Luna & Martín-Luengo, 2012; Olsson, 2000; Olsson & Juslin, 2002). 

Confidence resolution is modeled by correlating trial-by-trial memory recognition accuracy to the intensity of the confidence rating within each participant before comparing correlation values to zero or between different groups or conditions (i.e., gamma correlations; Goodman & Kruskal, 1959). This measure indexes how the intensity of memory confidence tracks memory accuracy across task trials (i.e., metacognitive sensitivity; Fleming & Lau, 2014). Existing evidence suggests that young individuals have insight as to how to adjust the intensity of their metacognitive confidence ratings concerning the accuracy of their memory responses, as indexed both by calibration and resolution measures (Brewer et al., 2005; Brewer & Sampaio, 2006; Wong et al., 2012).

Less attention has been paid to the relationship between the subjective vividness of memory and other objective measures of the quality of the memory, such as how precisely it is remembered or the number of details that are recalled. There is evidence that individuals can accurately monitor the level of the vividness of non-episodic mental images using the Likert scale. For instance, when participants judge the vividness of imagined visual patterns (e.g., imagining a pattern of green vertical grating), the vividness intensity of the imagined pattern predicts the subsequent perceptual bias (i.e., whether the participant will preferentially orient his/her attention toward a visually presented green vertical gratings) in a visual task (Pearson et al., 2011; see also Cochrane, 2021). Likewise, when participants judge the vividness of mental images corresponding to words, vividness intensity predicts the likelihood that these words will be subsequently recalled in a surprise memory task (D’Angiulli et al., 2013). 

A few studies have examined vividness calibration, that is, the extent to which levels of memory vividness match with memory performance (e.g., the mean number of remembered episodic details in a free-recall task). Young participants can calibrate the intensity of their vividness ratings about the richness of their memories, as revealed by studies showing that mean memory accuracy/precision increases with levels of memory vividness (Cooper et al., 2019; Richter et al., 2016; Thakral et al., 2019; Xie & Zhang, 2017). More recent studies have examined vividness resolution, that is the extent to which the intensity of vividness tracks memory content across task trials. One study used linear regressions conducted within each participant to examine whether the intensity of vividness ratings concerning the reminiscence of pictures was predicted by how participants remembered the visual appearance of these pictures (Cooper et al., 2019). Results revealed that regression values significantly differed from zero, thus suggesting that the intensity of memory vividness was determined by how low-level visual features were reinstated (Cooper et al., 2019). 

Other recent studies have used mixed-effects models to examine the relationship between the intensity of memory vividness and the associated number of retrieved details (Folville, D’Argembeau et Bastin, 2020b, 2020a). While both linear regressions conducted within each participant and mixed-effects analyses consider the dependent and independent variables at the trial level, mixed-effects models offer the advantage of considering both trials and participants as random effects (Baayen et al., 2008). Using these measures, it was shown that the intensity of memory vividness was significantly predicted both by spatial source memory accuracy (Folville, D’Argembeau, et al., 2020b) and the number of retrieved memory details (Folville et al., 2021; Folville, D’Argembeau, et al., 2020b, 2020a). Interestingly, the positive relation between vividness and memory content extends to memory studies conducted outside the laboratory, with young participants’ vividness ratings being related to the amount of recollected units of experience from real-life events (Folville, Jeunehomme, et al., 2020).

In summary, these studies indicate that young individuals have a good metacognitive understanding of how they should subjectively judge the quality of their memories. 

Memory vividness indexes the amount of sensory information available to the mind and participants seem to adequately monitor this source of information to make vividness judgments. What happens when the access to the information used to make vividness ratings, that is, the amount of sensory features, is compromised? Such diminution in access to precise memory details is evident in healthy aging, for which an episodic memory decline has been widely documented over the past decades (for review, see Nilsson, 2003; Park & Gutchess,2005). Age-related differences in episodic memory mechanisms will be described in the following section before considering the impact of these age-related episodic memory differences on vividness ratings.

Age-related differences in cognition and memory

Several theories have been proposed to account for the age-related decline in memory encoding and retrieval. Concerning memory encoding, recent work has revealed that aging diminishes the representational quality of encoded stimuli, with older adults encoding traces in a less precise and distinct fashion than young adults (Trelle et al., 2017, 2019). Aging also diminishes the ability to memorize the relations between encoded elements, so that older adults experience difficulties in forming cohesive episodic memory traces (Naveh-Benjamin, 2000; Naveh-Benjamin et al., 2007). It has also been suggested that young and older participants may differentially attend to stimuli features during memory encoding. For instance, it has been proposed that older adults, due to their reduced inhibitory abilities, have difficulties in ignoring non-relevant information (Hasher & Zacks, 1988). Other evidence has pointed out that older participants focus their attention on visual features to a lesser extent than young adults during memory encoding (Carstensen & Turk-Charles, 1994; Fredrickson & Carstensen, 1990; Labouvie-vief & Blanchard-fields, 1982). This differential focus of attention during encoding may hinder older adults’ memory performance at retrieval, especially in cases in which perceptive aspects of encoded stimuli are assessed (Hashtroudi et al., 1994; Rahhal et al., 2002). 

Interestingly, when young and older adults’ attention is focused on the same features during memory encoding (i.e. when they are specifically asked to focus their attention on the visual appearance and content of the pictures to be encoded), it does not alleviate the age-related decline in source memory performance at retrieval (Mitchell & Hill, 2019). Somewhat similar results have been put forward by McDonough & Gallo (2013), who have shown that increased elaboration during the generation of past events (i.e., asking participants to provide more perceptual details about the event), did not benefit the source memory performance of older participants (i.e., determining whether additional perceptual details were given for each event or not). Enhancing the availability of memory details at retrieval, either by constraining the focus of attention at encoding or by increasing the degree of elaboration during event generation, thus does not seem to narrow age-related differences in source memory performance. 

Together, these results thus provide evidence that older adults’ poorer objective memory performance may not be entirely due to an age-related reduction in the encoding of memory features but may also be attributed to how older adults reinstate and make use of these features in their memory decisions during retrieval (McDonough & Gallo, 2013; Mitchell & Hill, 2019; Trelle et al., 2017, 2019).

Concerning episodic memory retrieval, healthy aging negatively impacts recollection and the capacity to remember previously encoded items with their associated encoding context (Yonelinas, 2002) – while typically having less effect on the sense of familiarity of prior exposure (Koen & Yonelinas, 2014, 2016). Also congruent with this account are studies showing that the capacity to reinstate the precise and specific details of experience declines with advancing age, but that older adults are still efficient at remembering the general meaning, namely the gist, of previously encoded information (Flores et al., 2017; Gallo et al., 2019). 

Other authors assume that the age-related decline in episodic memory retrieval may stem from difficulties for older adults to identify the source of past episodes (Cansino, 2009; Mitchell & Johnson, 2009). Older adults would also experience difficulties in reinstating contextual representations from retrieved items and then strategically using them to guide the retrieval of other information in memory (Healey & Kahana, 2016; Wahlheim et al., 2017).

To compensate for the reduction in the efficiency of episodic memory retrieval processes, older adults may be more likely than young adults to rely on their – relatively preserved – semantic knowledge when remembering (Umanath & Marsh, 2014). 

Yet, overreliance on semantic or schematic knowledge might be a double-edged sword for older adults. While it might positively guide memory reconstruction processes while remembering, it might also mislead episodic memory by enhancing the likelihood of committing false alarms due to an enhanced gist/familiarity-based recognition (Devitt & Schacter, 2016; Koutstaal & Schacter, 1997; Umanath & Marsh, 2014). Particularly relevant to the study of false alarms is the DeeseRoediger-McDermott (DRM) paradigm, in which participants study related words (e.g., nail, screwdriver, wrench…) before remembering these words along with a critically related lure (e.g., hammer) (Gallo, 2006). Some, but not all, studies examining age effects in the DRM paradigms found an age-related increase in false recognition rates of critical lures (Balota et al., 1999; Devitt & Schacter, 2016; Gallo, 2006; Norman & Schacter, 1997). When faced with a challenging memory decision, memory monitoring processes may help in differentiating old from new items (Gallo et al., 2006; Johnson et al., 1993; Johnson, 2006). 

Although spared memory monitoring in aging has been reported on a few occasions (see for instance Gallo et al., 2007), there is mounting evidence that episodic memory monitoring processes become less efficient with advancing age and that it hinders memory discrimination accuracy (Devitt & Schacter, 2016; Gallo et al., 2006; Mitchell & Johnson, 2009; Trelle et al., 2017). Relevant to illustrate this is a study from Dehon and Brédart (2004) showing that young and older participants think about critical lures at the same rate during the memory retrieval phase of the DRM paradigm but that older adults, due to difficulties in monitoring the accuracy of their answers, endorse these lures as old more often than young adults do.

For more information:1950477648nn@gmail.com