Recency Effect Research Articles

How do recall requirements affect decision-making in free recall initiation? A linear ballistic accumulator approach.

Models of free recall describe free recall initiation as a decision-making process in which items compete to be retrieved. Recently, Osth and Farrell (Psychological Review, 126, 578–609, 2019) applied evidence accumulation models to complete RT distributions and serial positions of participants’ first recalls in free recall, which resulted in some novel conclusions about primacy and recency effects. Specifically, the results of the modeling favored an account in which primacy was due to reinstatement of the start-of-the-list, and recency was found to be exponential in shape. In this work, we examine what happens when participants are given alternative recall instructions. Prior work has demonstrated weaker primacy and greater recency when fewer items are required to report (Ward & Tan, Memory & Cognition, 2019), and a key question is whether this change in instructions qualitatively changes the nature of the recall process, or merely changes the parameters of the recall competition. We conducted an experiment where participants studied six- or 12-item lists and were post-cued as to whether to retrieve a single item, or as many items as possible. Subsequently, we applied LBA models with various assumptions about primacy and recency, implemented using hierarchical Bayesian techniques. While greater recency was observed when only one item was required for output, the model selection did not suggest that there were qualitative differences between the two conditions. Specifically, start-of-list reinstatement and exponential recency functions were favored in both conditions.Supplementary InformationThe online version contains supplementary material available at (10.3758/s13421-020-01117-2).

Modeling Articulatory Rehearsal in an Attention-Based Model of Working Memory

Maintenance of verbal information within human working memory occurs through two main complementary mechanisms: articulatory rehearsal and refreshing. Both are well-described in the literature but very few computational models have attempted to describe the ways they interact to maintain information. Because these interactions are difficult to apprehend without computer simulations, this paper presents a possible implementation of rehearsal within TBRS* (Time-Based Resource-Sharing Theory), a computational model operating only with refreshing and based on the TBRS verbal theory. Computer code is available at https://osf.io/taqmv/ . The implementation was tested on different benchmark findings and could replicate all main effects attributed to rehearsal, while still being accountable for the same effect as TBRS*. Four aspects of our rehearsal implementation are discussed with respect to the human behavior that is intended to be described: first, the primacy and recency effects in relation to the short-term property of rehearsal and the long-term purpose of refreshing; second, the moment at which long-term memory influences working memory performance during working memory tasks in reference to the redintegration hypothesis; third, the interplay between the two maintenance mechanisms; finally, positional coding as the appropriate representation for rehearsal.

Experience Effects in Finance: Foundations, Applications, and Future Directions

Abstract This article establishes four key findings of the growing literature on experience effects in finance: (i) the long-lasting imprint of past experiences on beliefs and risk taking; (ii) recency effects; (iii) the domain-specificity of experience effects; and (iv) imperviousness to information that is not experience-based. I first discuss the neuroscientific foundations of experience-based learning and sketch a simple model of its role in the stock market based on Malmendier et al. (2020a, b). I then distill the empirical findings on experience effects in stock-market investment, trade dynamics, and international capital flows, highlighting these four key features. Finally, I contrast models of belief formation that rely on “learned information” with models accounting for the neuroscience evidence on synaptic tagging and memory formation, and provide directions for future research.

Systematic Development of Short-Term Load Forecasting Models for the Electric Power Utilities: The Case of Pakistan

Load forecasts are fundamental inputs for the reliable and resilient operation of a power system. Globally, researchers endeavor to improve the accuracy of their forecast models. However, lack of studies detailing standardized model development procedures remains a major issue. In this regard, this study advances the knowledge of the systematic development of short-term load forecast (STLF) models for electric power utilities. The proposed model has been developed by using hourly load (time series) of five years of an electric power utility in Pakistan. Following the investigation of previously developed load forecast models, this study addresses the challenges of STLF by utilizing multiple linear regression, bootstrap aggregated decision trees, and artificial neural networks (ANNs) as mutually competitive forecasting techniques. The study also highlights both rudimentary and advanced elements of data extraction, synthetic weather station development, and the use of elastic nets for feature space development to upscale its reproducibility at global level. Simulations showed the superior forecasting prowess of ANNs over other techniques in terms of mean absolute percentage error (MAPE), root mean squared error (RMSE) and R2 score. Furthermore, an empirical approach has been taken to underline the effects of data recency, climatic events, power cuts, human activities, and public holidays on the model’s overall performance. Further analysis of the results showed how climatic variations, causing floods and heavy rainfalls, could prove detrimental for a utility’s ability to forecast its load demand in future.

“In the land of elections, the populist man is king”: The online communication of Basta and Vox in the 2019 European elections

This article, having an Iberian circumscription, focuses on populist parties – the Portuguese Basta and the Spanish Vox –, specifically on their online communication conducted in the context of the 2019 European elections. Using the mixed method and having a corpus comprised of Facebook posts (n=40) and videos (n=4), a triple content analysis was conducted: quantitative, qualitative, and rhetorical. The results show that, in terms of substance in Facebook, the two political actors focus more on the building of a sense of ingroup favoritism – in order to explore the feeling of inclusion, being the posts with this thematic substance the most liked, shared, and commented –, are unequivocal in presenting themselves as representatives of popular sovereignty and do not denote conflict in national and European entities. In terms of style, the use of visual image reveals that there are more posts focused on positive emotionality. In the videos, the tone against Europe is more critical and the use of rhetorical diversity is noted, such as emotional bipolarity, Manichaeism, exemplification, use of question mark, recency effect, repetition, factual evidence.

Law and order effects: on cognitive dissonance and belief perseverance

Order of evidence presentation affects the evaluation and the integration of evidence in mock criminal cases. In this study, we aimed to determine whether the order in which incriminating and exonerating evidence is presented influences cognitive dissonance and subsequent display of confirmation bias. Law students (N = 407) were presented with a murder case vignette, followed by incriminating and exonerating evidence in various orders. Contrary to a predicted primacy effect (i.e. early evidence being most influential), a recency effect (i.e. late evidence being most influential) was observed in ratings of likelihood of the suspect’s guilt. The cognitive dissonance ratings and conviction rates were not affected by the order of evidence presentation. The effects of evidence presentation order may be limited to specific aspects of legal decisions. However, there is a need to replicate the results using procedures and samples that are more representative of real-life criminal law trials.

The influence of narrative disclosure readability, information ordering and graphical representations on non-professional investors' judgment: evidence from an emerging market

PurposeThis study examines whether manipulation in attributes of corporate narrative disclosures and the use of graphical representations can bias non-professional investors' judgment towards firms' future performance, in an emerging market context.Design/methodology/approachThe authors conduct three different experiments with a 2 × 2 between-subjects design, using accounting and finance senior undergraduate students to proxy for the non-professional investors.FindingsResults show that simple (more readable) disclosures improve non-professional investors' judgment towards firms' future performance. In addition, it is found that non-professional investors are prone to a recency effect from the intentional ordering of narrative information, when using complex (less readable) narratives. However, no primacy effect is found, when using simple (more readable) disclosures. The results further provide evidence that the inclusion of graphical representations, along with the manipulated narrative disclosures, can moderate the recency effect of information order, when using less readable and complex narrative disclosures.Research limitations/implicationsThe results reveal that although the content of corporate disclosures can be objective, neutral and relevant, manipulation in textual features and the use of graphical presentations, can interact to impact how non-professional investors perceive and process the disclosed information. This study provides an Egyptian evidence regarding this issue, as the majority of prior studies concentrate on developed capital markets. In addition, it contributes to prior studies evaluating the appropriateness of the Belief Adjustment Model predictions about the effect of textual presentation order on decision-making, by providing evidence from an emerging market.Practical implicationsResults attempt to increase the awareness of investors and encourage them to use multiple sources of information to avoid the probable bias that can result from management's manipulation of narratives. In addition, the study could be of interest to regulators and standard-setters, where the results reveal the need for guidelines and regulations to guide the disclosure of narrative information and the use of graphical information in corporate reports.Originality/valueTo the best of the authors' knowledge, this is the first study to examine the effect of two impression management strategies in narrative disclosures (readability and information order), along with the use of graphical representations, on non-professional investors' judgment in an emerging market, like Egypt.

The Effect of Fracture Recency on Observed 10-Year Fracture Probability: A Registry-Based Cohort Study.

FRAX estimates 10-year fracture major osteoporotic fracture (MOF) and hip fracture probability from multiple risk factors. FRAX does not consider prior fracture site or time since fracture. Fracture risk is greater in the initial 2-year post-fracture period (imminent risk), implying that FRAX may underestimate risk in this setting. We used the population-based Manitoba Bone Mineral Density (BMD) Program registry to examine the effect of fracture recency and site on incident fracture risk predictions using FRAX. We identified women aged 40 years or older with baseline BMD and FRAX scores. Observed fracture outcomes to 10 years were compared with predicted 10-year fracture probability stratified by prior fracture status: none, recent (<2 years [median 0.3 years]), and remote (≥2 years [median 10.6 years]). For women with recent fractures, we also examined proposed multipliers to adjust FRAX for the effect of fracture recency and site. The cohort comprised 33,465 women aged 40 to 64 years (1897 recent fracture, 2120 remote fracture) and 33,806 women aged ≥65 years (2365 fracture, 4135 remote fracture). Observed fracture probability was consistent with predicted probability in most analyses. In women aged 40 to 64 years, there was a significant effect of recent vertebral and humerus fracture on MOF (observed to predicted 1.61 and 1.48, respectively), but these effects were still lower than the proposed multipliers (2.32 and 1.67, respectively). No significant effect of fracture recency was found after hip or forearm fracture in either age group. Our findings contribute to accumulating evidence of the importance of recent fracture. The effect of fracture recency was not consistent across fracture sites and with a lower magnitude than previously reported. Further quantification of effect size and specificity in additional independent cohorts is warranted to validate and refine recent-fracture multipliers in fracture risk assessment. © 2022 American Society for Bone and Mineral Research (ASBMR).

PPM-Decay: A computational model of auditory prediction with memory decay.

Statistical learning and probabilistic prediction are fundamental processes in auditory cognition. A prominent computational model of these processes is Prediction by Partial Matching (PPM), a variable-order Markov model that learns by internalizing n-grams from training sequences. However, PPM has limitations as a cognitive model: in particular, it has a perfect memory that weights all historic observations equally, which is inconsistent with memory capacity constraints and recency effects observed in human cognition. We address these limitations with PPM-Decay, a new variant of PPM that introduces a customizable memory decay kernel. In three studies-one with artificially generated sequences, one with chord sequences from Western music, and one with new behavioral data from an auditory pattern detection experiment-we show how this decay kernel improves the model's predictive performance for sequences whose underlying statistics change over time, and enables the model to capture effects of memory constraints on auditory pattern detection. The resulting model is available in our new open-source R package, ppm (https://github.com/pmcharrison/ppm).

Digital Marketing Attribution: Understanding the User Path

Digital marketing is a profitable business generating annual revenue over USD 200B and an inter-annual growth over 20%. The definition of efficient marketing investment strategies across different types of channels and campaigns is a key task in digital marketing. Attribution models are an instrument used to assess the return of investment of different channels and campaigns so that they can assist in the decision-making process. A new generation of more powerful data-driven attribution models has irrupted in the market in the last years. Unfortunately, its adoption is slower than expected. One of the main reasons is that the industry lacks a proper understanding of these models and how to configure them. To solve this issue, in this paper, we present an empirical study to better understand the key properties of user-paths and their impact on attribution models. Our analysis is based on a large-scale dataset including more than 95M user-paths from real advertising campaigns of an international hoteling group. The main contribution of the paper is a set of recommendation to build accurate, interpretable and computationally efficient attribution models such as: (i) the use of linear regression, an interpretable machine learning algorithm, to build accurate attribution models; (ii) user-paths including around 12 events are enough to produce accurate models; (iii) the recency of events considered in the user-paths is important for the accuracy of the model.

The Effect of Background Noise on Immediate Free Recall of Words in Younger and Older Listeners with Hearing Loss.

Auditory working memory is a crucial factor for complex cognitive tasks such as speech-in-noise understanding because speech communication in noise engages multiple auditory and cognitive capacities to encode, store, and retrieve information. An immediate free recall task of words has been used frequently as a measure of auditory working memory capacity. The present study investigated performance on the immediate free recall of words in quiet and noisy conditions for hearing-impaired listeners. Fifty hearing-impaired listeners (30 younger and 20 older) participated in this study. Lists of 10 phonetically and lexically balanced words were presented with a fixed presentation rate in quiet and noise conditions. Target words were presented at an individually determined most comfortable level (MCL). Participants were required to recall as many of the words in an arbitrary order immediately after the end of the list. Serial position curves were determined from the accuracy of free recall as a function of the word position in the sequence. Three-way analyses of variance with repeated measures were conducted on the percent-correct word recall scores, with two independent within-group factors (serial position and listening condition) and a between-group factor (younger, older). A traditional serial position curve was found in hearing-impaired listeners, yet the serial position effects depended on the listening condition. In quiet, the listeners with hearing loss were likely to recall more words from the initial and final positions compared with the middle-position words. In multi-talker babble noise, more difficulties were observed when recalling the words in the initial position compared with the words in the final position. Without a noise, a traditional U-shaped serial position curve consisting of primacy and recency effects was observed from hearing-impaired listeners, in accord with previous findings from normal-hearing listeners. The adverse impact of background noise was more pronounced in the primacy effect than in the recency effect.

Holographic Declarative Memory: Distributional Semantics as the Architecture of Memory.

We demonstrate that the key components of cognitive architectures (declarative and procedural memory) and their key capabilities (learning, memory retrieval, probability judgment, and utility estimation) can be implemented as algebraic operations on vectors and tensors in a high-dimensional space using a distributional semantics model. High-dimensional vector spaces underlie the success of modern machine learning techniques based on deep learning. However, while neural networks have an impressive ability to process data to find patterns, they do not typically model high-level cognition, and it is often unclear how they work. Symbolic cognitive architectures can capture the complexities of high-level cognition and provide human-readable, explainable models, but scale poorly to naturalistic, non-symbolic, or big data. Vector-symbolic architectures, where symbols are represented as vectors, bridge the gap between the two approaches. We posit that cognitive architectures, if implemented in a vector-space model, represent a useful, explanatory model of the internal representations of otherwise opaque neural architectures. Our proposed model, Holographic Declarative Memory (HDM), is a vector-space model based on distributional semantics. HDM accounts for primacy and recency effects in free recall, the fan effect in recognition, probability judgments, and human performance on an iterated decision task. HDM provides a flexible, scalable alternative to symbolic cognitive architectures at a level of description that bridges symbolic, quantum, and neural models of cognition.

Preregistered Direct Replication of “Sick Body, Vigilant Mind: The Biological Immune System Activates the Behavioral Immune System”

The tendency to attend to and avoid cues to pathogens varies across individuals and contexts. Researchers have proposed that this variation is partially driven by immunological vulnerability to infection, though support for this hypothesis is equivocal. One key piece of evidence (Miller & Maner, 2011) shows that participants who have recently been ill—and hence may have a reduced ability to combat subsequent infection—allocate more attention to faces with infectious-disease cues than do participants who have not recently been ill. The current article describes a direct replication of this study using a sample of 402 individuals from the University of Michigan, the University of Glasgow, and Vrije Universiteit Amsterdam—more than 4 times the sample size of the original study. No effect of illness recency on attentional bias for disfigured faces emerged. Though it did not support the original finding, this replication provides suggestions for future research on the psychological underpinnings of pathogen avoidance.

Peak-at-end rule: adaptive mechanism predicts time-dependent decision weighting

Humans make decisions under various natural circumstances, integrating multiple pieces of information that are distributed over space and time. Although psychophysical and physiological studies have investigated temporal dynamics underlying perceptual decision making, weighting profiles for inliers and outliers during temporal integration have yet to be fully investigated in most studies. Here, we examined the temporal weighting profile of a computational model characterized by a leaky integrator of sensory evidence. As a corollary of its leaky nature, the model predicts the recency effect and overweights outlying elements around the end of the stream. Moreover, we found that the model underweights outlying values occurring earlier in the stream (i.e., robust averaging). We also show that human observers exhibit exactly the same weighting profile in an average estimation task. These findings suggest that the adaptive decision process in the brain results in the time-dependent decision weighting, the “peak-at-end” rule, rather than the peak-end rule in behavioral economics.

A Dynamic Method, Analysis, and Model of Short-Term Memory for Serial Order with Clinical Applications

This study examined the robustness of a traditional memory task when moved out of controlled traditional settings. A letter recall task was designed to be self-administered via a smart-device which assessed recall by participants’ writing their responses on the device. This enabled collection of both the letter recalled and the timing of this recall such that the temporal dynamics could be examined. Participants were patients with mental illness (n=71) and healthy volunteers (n=103). Temporal dynamics were examined using a new mechanism that measured memory retrieval time precisely. Data were analyzed for accuracy, time and their relationships. The classic memory phenomena and associated effects were replicated. In terms of temporal dynamics, this is the first demonstration of primacy and recency effects in time domain variables, as well as phonological similarity effects as evident by the inverted U-shaped curves in time. The speed of short-term memory processes affects accuracy, error types and timing. The robustness of these memory effects and new approach to temporal dynamics suggest this framework may be suitable for clinical applications, notably for the long-term monitoring of cognition in patients with mental illness.

Infant categorization as a dynamic process linked to memory.

Recency effects are well documented in the adult and infant literature: recognition and recall memory are better for recently occurring events. We explore recency effects in infant categorization, which does not merely involve memory for individual items, but the formation of abstract category representations. We present a computational model of infant categorization that simulates category learning in 10-month-olds. The model predicts that recency effects outweigh previously reported order effects for the same stimuli. According to the model, infant behaviour at test should depend mainly on the identity of the most recent training item. We evaluate these predictions in a series of experiments with 10-month-old infants. Our results show that infant behaviour confirms the model’s prediction. In particular, at test infants exhibited a preference for a category outlier over the category average only if the final training item had been close to the average, rather than distant from it. Our results are consistent with a view of categorization as a highly dynamic process where the end result of category learning is not the overall average of all stimuli encountered, but rather a fluid representation that moves depending on moment-to-moment novelty. We argue that this is a desirable property of a flexible cognitive system that adapts rapidly to different contexts.

Long-term memory of real-world episodes is independent of recency effects: magic tricks as ecological tasks

How episodic memories decay is an unresolved question in cognitive neuroscience. The role of short-term mechanisms regarding the decay of episodic memories is circumscribed to set the maximum recall from which a monotonic decay occurs. However, this sequential view from the short to the long-term is not compulsory, as short-term dependent memory gains (like recency effects when memorizing a list of elements; serial-position effects) may not be translated into long-term memory differences. Moreover, producing memorable events in the laboratory faces important challenges, such as recreating realistic conditions with elevated recall, or avoiding spontaneous retrievals during memory retention (sociocultural hooks). The current study proposes the use of magic to enhance the study of memory. We designed a sequence of magic tricks performed live on stage to evaluate the interaction between memory decay and serial-position effects of those tricks. The audience was asked to freely recall the tricks at four different timepoints: just after the show, 10 days, 1.5 months and 4.5 months. We discovered serial-position differences after the show that were no longer present later on, suggesting that short-term memory gains do not translate into the long-term. Illustrating the power of naturalistic stimuli to study long-term memory while interrogating the interaction between short-term and long-term mechanisms, this work is, to our knowledge, the first scientific study of the memorability of magic tricks.

Recency effects in the buffering of negative news by corporate social responsibility advertising

PurposeDrawing from the theory of how relevant items are processed in memory when making judgements, this study aims to test for recency effects between CSR advertising and related, negative news on how a company is perceived and the explanatory roles of environmentalism, attribution and both feelings and attitudes towards the advertising itself.Design/methodology/approachThis study uses between-subjects experimental design with pretests.FindingsOrder effects exist, which, when ads and news are similarly influential, evidence a recency effect. The process is explained by both the mediating influence of attribution of blame and the moderation of this influence by attitude towards the environment. Differences between the effectiveness of ads are explained by the mediating influence of attitudes towards and feelings about the ad together with the moderation of this influence by involvement in the ad context.Practical implicationsCorporate social responsibility (CSR) ads should be pretested in the context of related but negative news, and not just on their own, to ensure they can buffer such news. CSR ads can be more effective when following rather than preceding such news and should not be withdrawn if such a crisis occurs.Originality/valueThe research first attempts to explain recency effects theoretically from the influence of CSR ads on negative CSR-related news. It also shows the determining factors in how such effects influence consumers by considering attribution, environmentalism, attitude to the context and attitude and feelings towards CSR ads.

Primary and recency effects based on loading path in classical plasticity

We have established an elastoplastic analysis model to explore the effect of loading path in an incompressible thin-walled tube under the combined action of axial force and torque based on Mises yield condition and isotropic linear hardening assumption. Further, four stress areas (σx, τx) are divided according to the characteristics of the final stress, and the plastic stress-strain relationship of twelve stress paths in different stress areas is derived. The “primary effect” of the stress path on plastic strain is demonstrated, namely, the plastic strain caused by the pre-loaded stress in path A (tensile stress is initially applied, followed by shear stress) is always greater than that caused by the post-loaded stress in path C (shear stress is initially applied, followed by tensile stress) irrespective of the value of final stress. The “recency effect” of the strain path on the stress is also established, which indicates that the stress caused by the post-loaded strain in path A is always greater than that caused by the pre-loaded strain in path C irrespective of the value of final strain. From the perspective of deformation, the “primary effect” of the stress path on the plastic strain and the “recency effect” of the strain path on the stress are unified. These effects are succinct and universal, and they provide useful insights on the plastic stress-strain relationship under different loading paths. Furthermore, they can serve as a useful reference for optimizing the processing technologies and construction procedures.

Neuroinflammatory Biomarkers Associated With Mild Traumatic Brain Injury History in Special Operations Forces Combat Soldiers

Special Operations Forces (SOF) combat soldiers are frequently exposed to blast and blunt neurotrauma, most often classified as mild traumatic brain injury (mTBI). Repetitive mTBI may increase the risk of developing long-term neurological sequelae. Identifying changes in neuroinflammatory biomarkers before chronic conditions emerge could serve as preliminary evidence of developing neuropathology. To determine the effects of mTBI history, lifetime mTBI incidence, and recency on blood biomarker concentrations of axonal protein neurofilament light (NfL), glycolytic enzyme neuron-specific enolase (NSE), astrocyte-expressed S100 calcium-binding protein B (S100B), and neurotrophic cytokine interleukin-6 (IL-6) in healthy, active duty SOF combat soldiers. Self-reported mTBI history/recency and fasted blood samples were collected in this cross-sectional study of 104 asymptomatic SOF combat soldiers. Biomarker concentrations were quantified using commercial enzyme-linked immunosorbent assays. Mann-Whitney U and Kruskal-Wallis tests were used to compare groups. Post hoc tests with appropriate corrections were conducted as warranted. Soldiers with mTBI history had higher NSE concentrations than those without (z = -2.60, P = .01). We also observed significant main effects of lifetime mTBI incidence on NSE (χ(3) = 9.52, P = .02) and S100B (χ(3) = 8.21, P = .04) concentrations and a significant main effect of mTBI recency on NfL concentration (χ(2) = 6.02, P = .049). The SOF combat soldiers with mTBI history had increased NSE. Longitudinal studies in this population are needed due to between-subject heterogeneity in biomarker concentrations. The NfL concentrations in our SOF combat soldiers-regardless of mTBI history or recency-were similar to values previously reported in civilian acute TBI patients.