The ability to distinguish between different explanations of human memory abilities continues to be the subject of many ongoing theoretical debates. These debates attempt to account for a growing corpus of empirical phenomena in item-memory judgments, which include the list strength effect, the strength-based mirror effect, and output interference. One of the main theoretical contenders is the Retrieving Effectively from Memory (REM) model. We show that REM, in its current form, has difficulties in accounting for source-memory judgments – a situation that calls for its revision. We propose an extended REM model that assumes a local-matching process for source judgments alongside source differentiation. We report a first evaluation of this model’s predictions using three experiments in which we manipulated the relative source-memory strength of different lists of items. Analogous to item-memory judgments, we observed a null list strength effect and a strength-based mirror effect in the case of source memory. In a second evaluation, which relied on a novel experiment alongside two previously published datasets, we evaluated the model’s predictions regarding the manifestation of output interference in item and lack of it in source memory judgments. Our results showed output interference severely affecting the accuracy of item-memory judgments but having a null or negligible impact when it comes to source-memory judgments. Altogether, these results support REM’s core notion of differentiation (for both item and source information) as well as the concept of local matching proposed by the present extension.

The work of Ed Zigler spans decades of research all singularly dedicated to using science to improve the lives of children facing different challenges. The focus of this article is on one of Zigler's numerous lines of work: advocating for the practice of mental age (MA) matching in empirical research, wherein groups of individuals are matched on the basis of developmental level, rather than chronological age. While MA matching practices represented a paradigm shift that provided the seeds from which the developmental approach to developmental disability sprouted, it is not without its own limits. Here, we examine and test the underlying assumption of linearity inherent in MA matching using three commonly used IQ measures. Results provide practical constraints of using MA matching, a solution which we hope refines future clinical and empirical practices, furthering Zigler's legacy of continued commitment to compassionate, meaningful, and rigorous science in the service of children.

We conducted three experiments specifically designed to simultaneously evaluate the effects on recognition accuracy of adding items during study and adding items during test. The recognition memory list-length effect (LLE) is small and unreliable (Annis et al. 2015 ; Dennis et al. 2008 ), but additional test trials produce a robust decrease in accuracy, termed output interference (OI; Criss et al. 2011 ; Kılıç et al. 2017 ). This is puzzling; why should the size of the effect of additional stimulus exposures depend on whether the item was studied or tested (Malmberg et al. 2012 )? We found a decrease in accuracy when stimulus exposures were added at any stage. However, the harm of adding items during study was less than the output interference that resulted from testing. In addition, feedback presented during test served as a moderator. When feedback was given, OI was diminished, and the LLE increased. Within the framework of our model, this suggests that testing with no feedback often results in the encoding of additional information in a trace originally encoded during study, and testing with feedback decreases the tendency to update traces during test. Several possible accounts of feedback reducing trace updating are discussed.

We present a model of the encoding of episodic associations between items, extending the dynamic approach to retrieval and decision making of Cox and Shiffrin (2017) to the dynamics of encoding. This model is the first unified account of how similarity affects associative encoding and recognition, including why studied pairs consisting of similar items are easier to recognize, why it is easy to reject novel pairs that recombine items that were studied alongside similar items, and why there is an early bias to falsely recognize novel pairs consisting of similar items that is later suppressed (Dosher, 1984; Dosher & Rosedale, 1991). Items are encoded by sampling features into limited-capacity parallel channels in working memory. Associations are encoded by conjoining features across these channels. Because similar items have common features, their channels are correlated which increases the capacity available to encode associative information. The model additionally accounts for data from a new experiment illustrating the importance of similarity for associative encoding across a variety of stimulus types (objects, words, and abstract forms) and types of similarity (perceptual or conceptual), illustrating the generality of the model.

Systems Factorial Technology (SFT; Townsend and Nozawa (1995)) gains much of its power from finding tight nonparametric links between theory and data. But this power comes at a price: Applying SFT typically requires low error rates, many observations, and a guarantee of selective influence of experimental manipulations, conditions that cannot be satisfied in many fields of psychology. We present a set of parametric methods that, while lacking the full power of traditional SFT, allow its logic to be applied to situations that do not adhere to those conditions. These methods are based around building different parallel architectures from systems of Linear Ballistic Accumulators (Brown and Heathcote (2008)), including architectures that involve interactions between processes. The primary output of these methods is an estimate of the probabilities that a participant is best described by each of these architectures. In an example and set of simulations, we show that these methods are accurate and robust at identifying the processing architectures employed by a set of participants, may be estimated in maximum a posteriori or fully Bayesian fashion, and that hierarchical estimation allowing accurate identification with as few as three trials per participant per condition. We provide code that allows researchers to apply these methods to their own data at https://osf.io/m6ubq/.

In an attempt to increase the reliability of empirical findings, psychological scientists have recently proposed a number of changes in the practice of experimental psychology. Most current reform efforts have focused on the analysis of data and the reporting of findings for empirical studies. However, a large contingent of psychologists build models that explain psychological processes and test psychological theories using formal psychological models. Some, but not all, recommendations borne out of the broader reform movement bear upon the practice of behavioral or cognitive modeling. In this article, we consider which aspects of the current reform movement are relevant to psychological modelers, and we propose a number of techniques and practices aimed at making psychological modeling more transparent, trusted, and robust.

The primary aim of this paper is to elucidate the mechanisms governing output interference in cued recall. Output interference describes the phenomenon where accuracy decrease over the course of an episodic memory test. Output inference in cued recall takes the form of a decrease in correct and intrusion responses and an increase in failures to response across the test. This pattern can only be accounted for by a model with two complementary mechanisms: learning during retrieval and a response filter that prevents repeated recall of the same item. We investigate how a retrieval filter might operate by manipulating the similarity of words. The data are consistent with a retrieval filter that does not operate by a global match of a potential target to previously recalled items. Results are discussed within the search of associative memory theory.

Scientific advances across a range of disciplines hinge on the ability to make inferences about unobservable theoretical entities on the basis of empirical data patterns. Accurate inferences rely on both discovering valid, replicable data patterns and accurately interpreting those patterns in terms of their implications for theoretical constructs. The replication crisis in science has led to widespread efforts to improve the reliability of research findings, but comparatively little attention has been devoted to the validity of inferences based on those findings. Using an example from cognitive psychology, we demonstrate a blinded-inference paradigm for assessing the quality of theoretical inferences from data. Our results reveal substantial variability in experts’ judgments on the very same data, hinting at a possible inference crisis.

The target article on robust modeling (Lee et al. in review) generated a lot of commentary. In this reply, we discuss some of the common themes in the commentaries; some are simple points of agreement while others are extensions of a practical or abstract nature. We also address a small number of disagreements or confusions.

Signal detection theory (SDT) is used to quantify people’s ability and bias in discriminating stimuli. The ability to detect a stimulus is often measured through confidence ratings. In SDT models, the use of confidence ratings necessitates the estimation of confidence category thresholds, a requirement that can easily result in models that are overly complex. As a parsimonious alternative, we propose a threshold SDT model that estimates these category thresholds using only two parameters. We fit the model to data from Pratte et al. (Journal of Experimental Psychology: Learning, Memory, and Cognition, 36, 224–232 2010) and illustrate its benefits over previous threshold SDT models.

In single-item recognition, the strength-based mirror effect (SBME) is reliably obtained when encoding strength is manipulated between lists or participants. Debate surrounds the degree to which this effect is due to differentiation (e.g., Criss Journal of Memory and Language, 55, 461-478, 2006) or criterion shifts (e.g., Hicks & Starns Memory & Cognition, 42, 742-754, 2014). Problematically, differing underlying control processes may be equally capable of producing an SBME. The ability of criterion shifts to produce an SBME has been shown in prior work where differentiation was unlikely. The present work likewise produces an SBME under conditions where criterion shifts are unlikely. Specifically, we demonstrate that an SBME can be elicited without the typical number of trials needed to adjust one's decision criterion (Experiments 1, 2, and 5) and using encoding manipulations that do not explicitly alert participants that their memory quality has changed (Experiments 3 and 4). When taken in the context of the broader literature, these results demonstrate the need to prioritize memory models that can predict SBMEs via multiple underlying processes.

Retrieval from episodic memory has consequences (Malmberg, Lehman, Annis, Criss, & Shiffrin, The Psychology of Learning and Motivation, 61; 285–313, 2014). In some cases, the consequences are beneficial, as in the improvement in memory for items that were already retrieved (Izawa, 1970, Journal of Experimental Psychology, 83(2, Pt.1), 340–344; Izawa, Journal of Experimental Psychology, 89(1): 10–21, 1971; Roediger & Karpicke, Psychological Science, 17(3), 249–255, 2006). In other cases, the consequences are negative, as in the case of output interference (OI; Wickens, Borne, & Allen, Journal of Verbal Learning and Verbal Behavior, 2, 440–445, 1963). OI is the decrease in accuracy in episodic memory with increasing test trials. A release from OI is observed when accuracy rebounds following a switch in the category of item being tested (Criss, Salomão, Malmberg, Aue, Kilic, & Claridge, Quarterly Journal of Experimental Psychology, 64(4): 316–326, 2018; Malmberg, Criss, Gangwani, & Shiffrin, Psychological Science, 23(2): 115–119, 2012). In all reports thus far, a release from OI was observed when the conceptual information of stimuli was switched. Here, we evaluate the possibility that changing perceptual information causes a release from OI by presenting items in two perceptual forms (image, audio recording or printed text of the corresponding word) either mixed or blocked at test. A release from OI was observed only for images. We discuss the roles of conceptual and perceptual information in producing OI within the retrieving effectively from memory modeling framework.

The development of memory theory has been constrained by a focus on isolated tasks rather than the processes and information that are common to situations in which memory is engaged. We present results from a study in which 453 participants took part in five different memory tasks: single-item recognition, associative recognition, cued recall, free recall, and lexical decision. Using hierarchical Bayesian techniques, we jointly analyzed the correlations between tasks within individuals-reflecting the degree to which tasks rely on shared cognitive processes-and within items-reflecting the degree to which tasks rely on the same information conveyed by the item. Among other things, we find that (a) the processes involved in lexical access and episodic memory are largely separate and rely on different kinds of information, (b) access to lexical memory is driven primarily by perceptual aspects of a word, (c) all episodic memory tasks rely to an extent on a set of shared processes which make use of semantic features to encode both single words and associations between words, and (d) recall involves additional processes likely related to contextual cuing and response production. These results provide a large-scale picture of memory across different tasks which can serve to drive the development of comprehensive theories of memory. (PsycINFO Database Record

With the advent of the Internet of Things (IoT) and a rapid deployment of smart devices and wireless sensor networks (WSNs), humans interact extensively with machine data. These human decision makers use sensors that provide information through a sociotechnical network. The sensors can be other human users or they can be IoT devices. The decision makers themselves are also part of the network, and there is a need to understand how they will behave. In this paper, the decision fusion behavior of humans is analyzed on the basis of behavioral experiments. The data collected from these experiments demonstrate that people perform decision fusion in a stochastic manner dependent on various factors, unlike machines that perform this task in a deterministic manner. A Bayesian hierarchical model is developed to characterize the observed stochastic human behavior. This hierarchical model captures the differences observed in people at individual, crowd, and population levels. The implications of such a model on designing large-scale inference systems are presented by developing optimal decision fusion trees with both human and machine agents.

What properties of a word make it easy or difficult to remember? Word frequency and context variability are separate, closely related word properties that have disparate influences on memorability. The influence of word frequency changes depending on the memory task, with high-frequency words tending to be recalled better and low-frequency words to be recognized better. Conversely, low-context-variability words tend to be remembered better across tasks. One proposed explanation for the low-variability advantage is that low-variability words are easier to associate with the experimental context, given that they are associated with fewer extra-experimental contexts. On the basis of this explanation, it has been suggested that the formation of interitem associations during encoding should interfere with the formation of item-to-context associations, attenuating the low-variability advantage. Across experiments, we tested whether focusing on interitem associations disrupted the low-variability advantage, by manipulating encoding tasks, test expectancy, final test condition, word frequency, and context variability. Focusing on interitem associations did not harm performance for low-variability words. Words low in both frequency and variability were recognized better, but word pairs composed of high-frequency, low-variability words were recognized better in associative recognition. On the basis of the data, we suggest that focusing on interitem associations does not come at the expense of item-to-context associations. Moreover, the data further support the idea that frequency and variability are distinct properties.

Nonsteroidal anti-inflammatory drugs work by non-selectively inhibiting cyclooxygenase enzymes. Evidence indicates that metabolites of the cyclooxygenase pathway play a critical role in the process of learning and memory. We evaluated whether acute naproxen treatment impairs short-term working memory, episodic memory, or semantic memory in a young, healthy adult population. Participants received a single dose of placebo or naproxen (750 mg) in random order separated by 7–10 days. Two hours following administration, participants completed five memory tasks. The administration of acute high-dose naproxen had no effect on memory in healthy young adults.

Reviewed Work(s): A Partial Review of Cognitive Modeling in Perception and Memory: A Festschrift for Richard M. Shiffrin by Jeroen G. W. Raaijmakers, Amy H. Criss, Robert L. Goldstone, Robert M. Nosofsky, and Mark Steyvers Review by: Kenneth J. Malmberg Source: The American Journal of Psychology, Vol. 129, No. 2 (Summer 2016), pp. 206-211 Published by: University of Illinois Press Stable URL: http://www.jstor.org/stable/10.5406/amerjpsyc.129.2.0206 Accessed: 11-04-2017 12:54 UTC