The importance of age-related differences in prospective memory: Evidence from diffusion model analyses

The role of offloading intentions on future-oriented thinking

Offloading (e.g., using Google calendar reminders) has been shown to improve prospective memory (PM). One unstudied aspect of PM offloading is whether having reminders reduces our future-oriented thinking about PM intentions in contexts in which the intention cannot be fulfilled. In the current study, participants were given two blocks of an ongoing lexical decision task. Prior to beginning the task, participants formed an intention to make a special response to PM targets only in block 2. Participants in the reminder condition had the PM intention displayed at the top of the screen in block 2, whereas those in the no-reminder condition did not. To assess activation of the intention out of context, PM lures (Experiment 1) or thought probes (Experiments 2 and 3) were presented in block 1. Results showed that reminders improved PM performance in block 2 but did not reduce lure interference or PM-related thoughts in block 1. These findings suggest that offloaded memory representations remain as activated and accessible as non-offloaded representations outside the context in which intentions can be fulfilled.

The effect of impulsive personality traits on prospective memory under different task importance conditions

BACKGROUND

Prospective memory (PM) refers to the ability to perform planned activities in the appropriate future situations. It needs to be planned in advance and processed through multiple stages such as encoding, retention, retrieval, and execution, which usually require more attention resources. Impulsivity trait individuals are usually characterized by lack of consideration, premature expression, excessive risk-taking and easy to make inappropriate reaction, so they are more likely to show disadvantages in PM. Nevertheless, increasing the importance of PM tasks can promote more adequate and effective cue encoding, and encourage individuals to devote attention to PM tasks, which may change the disadvantage of impulsivity individuals in PM performance.

METHODS

In this study, the between-subjects design of 2 (trait type: high-impulsivity trait, low-impulsivity trait) ×2 (task importance: important, unimportant) was adopted in the experiment, the 2-back task was used for the ongoing task, and the focal cues were used for the PM task cues.

RESULTS

The results showed that the PM accuracy of high-impulsivity trait individuals was lower than that of low-impulsivity trait individuals under the task unimportant condition, but there was no difference between the two traits groups under the task important condition.

CONCLUSIONS

The results of this study suggested that high-impulsivity trait individuals had a deficit in PM performance, but emphasizing the importance of PM tasks can compensate for their disadvantage in PM performance.

The difference of time-based prospective memory between Type A and Type B individuals under different time monitoring conditions

Time-based prospective memory (TBPM) is affected by many factors, which include Type A and Type B personality types. Type A individuals have a strong desire to complete tasks and a strong sense of time-urgency to complete established tasks before the deadline. Type B individuals have fewer time constraints and usually procrastinate until the deadline to complete the task. Compared with Type B individuals, Type A individuals may perform better in TBPM due to their advantages in time cognition and attitude. This study explores the differences in the TBPM ability between Type A individuals and Type B individuals under different time monitoring conditions. In Experiment 1, there was no limit to how many times participants could check the time. The results showed that the performance of TBPM between Type A individuals and Type B individuals was not different. In Experiment 2, participants could only check the time once during each TBPM task. The results showed that, compared to Type B individuals, Type A individuals performed better in TBPM, with higher time monitoring frequency and slower response speed to the ongoing tasks. These findings suggest that the performance of Type A individuals in TBPM has an advantage only under the restricted time monitoring condition. This advantage is then mainly due to the increase in the attention consumption of Type A individuals in both internal and external attention.

Evidence accumulation modelling in the wild: understanding safety-critical decisions

Evidence accumulation models (EAMs) are a class of computational cognitive model used to understand the latent cognitive processes that underlie human decisions and response times (RTs). They have seen widespread application in cognitive psychology and neuroscience. However, historically, the application of these models was limited to simple decision tasks. Recently, researchers have applied these models to gain insight into the cognitive processes that underlie observed behaviour in applied domains, such as air-traffic control (ATC), driving, forensic and medical image discrimination, and maritime surveillance. Here, we discuss how this modelling approach helps researchers understand how the cognitive system adapts to task demands and interventions, such as task automation. We also discuss future directions and argue for wider adoption of cognitive modelling in Human Factors research.

Mental speed is high until age 60 as revealed by analysis of over a million participants

Response speeds in simple decision-making tasks begin to decline from early and middle adulthood. However, response times are not pure measures of mental speed but instead represent the sum of multiple processes. Here we apply a Bayesian diffusion model to extract interpretable cognitive components from raw response time data. We apply our model to cross-sectional data from 1.2 million participants to examine age differences in cognitive parameters. To efficiently parse this large dataset, we apply a Bayesian inference method for efficient parameter estimation using specialized neural networks. Our results indicate that response time slowing begins as early as age 20, but this slowing was attributable to increases in decision caution and to slower non-decisional processes, rather than to differences in mental speed. Slowing of mental speed was observed only after approximately age 60. Our research thus challenges widespread beliefs about the relationship between age and mental speed.

The Impact of Error-Consequence Severity on Cue Processing in Importance-Biased Prospective Memory

Prospective memory (PM) enables people to remember to complete important tasks in the future. Failing to do so can result in consequences of varying severity. Here, we investigated how PM error-consequence severity impacts the neural processing of relevant cues for triggering PM and the ramification of that processing on the associated prospective task performance. Participants role-played a cafeteria worker serving lunches to fictitious students and had to remember to deliver an alternative lunch to students (as PM cues) who would otherwise experience a moderate or severe aversive reaction. Scalp-recorded, event-related potential (ERP) measures showed that the early-latency frontal positivity, reflecting the perception-based neural responses to previously learned stimuli, did not differ between the severe versus moderate PM cues. In contrast, the longer-latency parietal positivity, thought to reflect full PM cue recognition and post-retrieval processes, was elicited earlier by the severe than the moderate PM cues. This faster instantiation of the parietal positivity to the severe-consequence PM cues was then followed by faster and more accurate behavioral responses. These findings indicate how the relative importance of a PM can be neurally instantiated in the form of enhanced and faster PM-cue recognition and processing and culminate into better PM.

Adult age differences in remembering gain- and loss-related intentions

Motivational and emotional changes across adulthood have a profound impact on cognition. In this registered report, we conducted an experimental investigation of motivational influence on remembering intentions after a delay (prospective memory; PM) in younger, middle-aged, and older adults, using gain- and loss-framing manipulations. The present study examined for the first time whether motivational framing in a PM task has different effects on younger and older adults' PM performance (N = 180; age range: 18-85 years) in a controlled laboratory setting. Based on lifespan theories of motivation, we assumed that the prevention of losses becomes more relevant with increasing age: We expected that older adults show relatively higher PM performance in a task with loss-related consequences following PM failure than in a task in which successful PM leads to gains. The opposite pattern of performance was expected for younger adults. The findings suggest that the relevance of reward and positive gain-related consequences for successful remembering appears to decrease with age. As hypothesised, a motivational framing × age interaction indicated that age differences in memory performance were smaller with loss-related than gain-related consequences, supporting a loss-prevention view on motivated cognition.

Volition in prospective Memory: Evidence against differences between free and fixed target events

Volition is the extent to which actions are generated as a result of internal states in contrast to responses to external conditions or dictated by external events. Delayed intentions about future action are stored in prospective memory until the intended action has to be formed at a later point in time. It is unknown how voluntary choice affects prospective memory. We compared the difference between freely chosen and fixed targets on the reaction times and task performance in the ongoing task and for the target stimuli in a prospective memory task. The task performance and the reaction time was modelled using a Bayesian hierarchical drift-diffusion model. The analysis showed no differences between self-chosen and fixed prospective memory cues on task responses. The result suggests that volition in choosing the cue to act upon or given a fixed cue does not make a difference for prospective memory task performance.

Age differences in diffusion model parameters: a meta-analysis

Older adults typically show slower response times in basic cognitive tasks than younger adults. A diffusion model analysis allows the clarification of why older adults react more slowly by estimating parameters that map distinct cognitive components of decision making. The main components of the diffusion model are the speed of information uptake (drift rate), the degree of conservatism regarding the decision criterion (boundary separation), and the time taken up by non-decisional processes (i.e., encoding and motoric response execution; non-decision time). While the literature shows consistent results regarding higher boundary separation and longer non-decision time for older adults, results are more complex when it comes to age differences in drift rates. We conducted a multi-level meta-analysis to identify possible sources of this variance. As possible moderators, we included task difficulty and task type. We found that age differences in drift rate are moderated both by task type and task difficulty. Older adults were inferior in drift rate in perceptual and memory tasks, but information accumulation was even increased in lexical decision tasks for the older participants. Additionally, in perceptual and lexical decision tasks, older individuals benefitted from high task difficulty. In the memory tasks, task difficulty did not moderate the negative impact of age on drift. The finding of higher boundary separation and longer non-decision time in older than younger adults generalized over task type and task difficulty. The results of our meta-analysis are consistent with recent findings of a more pronounced age-related decline in memory than in vocabulary performance.

Wait a second . . . Boundary conditions on delayed responding theories of prospective memory

Research suggests that forcing participants to withhold responding for as brief as 600 ms eliminates one of the most reliable findings in prospective memory (PM): the cue focality effect. This result undermines the conventional view that controlled attentional monitoring processes support PM, and instead suggests that cue detection results from increased response thresholds that allow more time for PM information to accumulate. Given the significance of such findings, it is critical to examine the generalizability of the delay mechanism. Experiments 1-4 examined boundary conditions of the delay theory of PM, whereas Experiment 5 more directly tested contrasting theoretical predictions from monitoring theory (e.g., multiprocess framework) and delay theory. Using the same (Experiment 1) or conceptually similar (Experiment 2) delay procedure and identical cues (nonfocal "tor" intention) from the original study failed to show any influence of delay on performance. Using a different nonfocal intention (first letter "S") similarly did not influence performance (Experiment 3), and the difference between focal and nonfocal cue detection was never completely eliminated even with delays as long as 2,500 ms (Experiment 4). Experiment 5 did find the anticipated reduction in the focality effect with increased delays with a larger sample (n = 249). However, the focality effect was not moderated by attention control ability despite the fact that participants with impoverished attention control should benefit most from the delay procedure. These results suggest that any theory of PM that considers only a delay mechanism may not fully capture the dynamic attention processes that support cue detection. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

How Do Gain and Loss Incentives Affect Memory for Intentions Across Adulthood?

OBJECTIVES

Changes in motivational orientation across adulthood affect cognitive processes. The purpose of this research was to investigate if and how motivational incentives (gains or losses) affect prospective memory for intended actions in younger, middle-aged, and older adults.

METHODS

The consequences of memory hits and misses and the framing of the memory tasks were experimentally manipulated between participants: In a gain-framing condition, participants accumulated rewards, dependent on the proportion of target events to which they responded accurately. In a loss-framing condition, participants received an initial endowment from which losses were deducted, dependent on the proportion of targets they missed. We measured memory accuracy, perceived task importance, and ongoing-task performance.

RESULTS

Gains and losses had different effects on memory across age groups: Age × Motivational Valence interactions emerged across two studies. Older adults showed relatively better memory performance to avoid losses than to achieve gains. Moreover, higher age was associated with lower memory performance (Study 1) and slower but more accurate decisions in an ongoing activity (Study 2).

DISCUSSION

The findings reveal that motivational incentives and the framing of consequences as gains or losses moderate the relation between age and memory performance. Older adults' memory performance may benefit when messages encourage the avoidance of losses. This may also help to design age-tailored interventions in applied settings (e.g., health-related behavior).

Systematic Parameter Reviews in Cognitive Modeling: Towards a Robust and Cumulative Characterization of Psychological Processes in the Diffusion Decision Model

Parametric cognitive models are increasingly popular tools for analyzing data obtained from psychological experiments. One of the main goals of such models is to formalize psychological theories using parameters that represent distinct psychological processes. We argue that systematic quantitative reviews of parameter estimates can make an important contribution to robust and cumulative cognitive modeling. Parameter reviews can benefit model development and model assessment by providing valuable information about the expected parameter space, and can facilitate the more efficient design of experiments. Importantly, parameter reviews provide crucial-if not indispensable-information for the specification of informative prior distributions in Bayesian cognitive modeling. From the Bayesian perspective, prior distributions are an integral part of a model, reflecting cumulative theoretical knowledge about plausible values of the model's parameters (Lee, 2018). In this paper we illustrate how systematic parameter reviews can be implemented to generate informed prior distributions for the Diffusion Decision Model (DDM; Ratcliff and McKoon, 2008), the most widely used model of speeded decision making. We surveyed the published literature on empirical applications of the DDM, extracted the reported parameter estimates, and synthesized this information in the form of prior distributions. Our parameter review establishes a comprehensive reference resource for plausible DDM parameter values in various experimental paradigms that can guide future applications of the model. Based on the challenges we faced during the parameter review, we formulate a set of general and DDM-specific suggestions aiming to increase reproducibility and the information gained from the review process.

Do Non-Decision Times Mediate the Association between Age and Intelligence across Different Content and Process Domains?

In comparison to young adults, middle-aged and old people show lower scores in intelligence tests and slower response times in elementary cognitive tasks. Whether these well-documented findings can both be attributed to a general cognitive slow-down across the life-span has become subject to debate in the last years. The drift diffusion model can disentangle three main process components of binary decisions, namely the speed of information processing, the conservatism of the decision criterion and the non-decision time (i.e., time needed for processes such as encoding and motor response execution). All three components provide possible explanations for the association between response times and age. We present data from a broad study using 18 different response time tasks from three different content domains (figural, numeric, verbal). Our sample included people between 18 to 62 years of age, thus allowing us to study age differences across young-adulthood and mid-adulthood. Older adults generally showed longer non-decision times and more conservative decision criteria. For speed of information processing, we found a more complex pattern that differed between tasks. We estimated mediation models to investigate whether age differences in diffusion model parameters account for the negative relation between age and intelligence, across different intelligence process domains (processing capacity, memory, psychometric speed) and different intelligence content domains (figural, numeric, verbal). In most cases, age differences in intelligence were accounted for by age differences in non-decision time. Content domain-general, but not content domain-specific aspects of non-decision time were related to age. We discuss the implications of these findings on how cognitive decline and age differences in mental speed might be related.

Aging and strategic prospective memory monitoring

Monitoring the environment for the occurrence of prospective memory (PM) targets is a resource-demanding process that produces cost (e.g., slowing) to ongoing activities. Prior research has shown that older adults are able to monitor strategically, which involves the activation of monitoring when contextually appropriate and deactivation of monitoring when it is not thereby affording conservation of limited-capacity attentional resources. However, the time course and efficiency with which these processes operate with increased age are unknown. In the current study, participants performed an ongoing lexical decision task in which words/nonwords were blocked by font color in sets of ten trials (ten red trials followed by ten blue trials). Importantly, participants were informed that PM targets ("TOR" syllable) would only occur in red trials. Replicating previous work, both younger and older adults were successfully able to disengage monitoring upon encountering the unexpected (i.e., blue) context. However, while younger adults completely disengaged monitoring in the unexpected context, older adults continued to show monitoring across the majority of trials. Additionally, younger, but not older, adults showed a re-engagement of monitoring at the end of the unexpected context in preparation for the upcoming expected context. These findings suggest that while strategic monitoring generally remains intact with increased age, the disengagement and preparatory re-engagement of strategic monitoring may operate less optimally for older adults.

Aging and the strategic use of context to control prospective memory monitoring

Monitoring the environment for the occurrence of prospective memory (PM) targets is a resource-demanding process that produces cost to ongoing activities. The current study investigated younger and older adults' ability to monitor strategically, which involves the heightening and relaxation of monitoring when it is contextually appropriate thereby affording conservation of limited-capacity attentional resources. Participants performed a lexical-decision task in which words or nonwords were presented in upper or lower locations of the screen. The specific condition was correctly informed that PM targets ("tor" syllable) would occur only in word trials (simple cue; Experiment 1), in word trials in the upper location (complex cue; Experiments 2 and 3A), or in red trials in the upper location (complex cue; Experiment 3B), whereas the nonspecific condition was told that targets could appear in any context. The results showed that older adults generally exhibited similar monitoring patterns as younger adults. When context varied randomly on each trial, younger and older adults in the specific condition utilized simple (Experiment 1) but not complex (Experiment 2) contextual cues to reduce monitoring in unexpected contexts relative to the nonspecific condition. Notably, younger but not older adults were able to use the location dimension of the complex cue to reduce monitoring in unexpected (lower) contexts. When context varied more predictably (i.e., changed every eight trials), both younger and older adults were able to monitor strategically in response to the complex contextual cue (Experiments 3A and 3B). Together these findings suggest that context-sensitive PM monitoring processes generally remain intact with increased age. (PsycINFO Database Record