Familiarity and recollection in heuristic decision making

Are involuntary autobiographical memory and déjà vu natural products of memory retrieval?

Involuntary autobiographical memories (IAMs) and déjà vu are phenomena that occur spontaneously in daily life. IAMs are recollections of the personal past, whereas déjà vu is defined as an experience in which the person feels familiarity at the same time as knowing that the familiarity is false. We present and discuss the idea that both IAMs and déjà vu can be explained as natural phenomena resulting from memory processing and, importantly, are both based on the same memory retrieval processes. Briefly, we hypothesise that both can be described as "involuntary" or spontaneous cognitions, where IAMs deliver content and déjà vu delivers only the feeling of retrieval. We map out the similarities and differences between the two, making a theoretical and neuroscientific account for their integration into models of memory retrieval and how the autobiographical memory literature can explain these quirks of daily life and unusual but meaningful phenomena. We explain the emergence of the déjà vu phenomenon by relating it to well-known mechanisms of autobiographical memory retrieval, concluding that IAMs and déjà vu lie on a continuum.

When Does an Individual Accept Misinformation? An Extended Investigation Through Cognitive Modeling

A new phenomenon is the spread and acceptance of misinformation and disinformation on an individual user level, facilitated by social media such as Twitter. So far, state-of-the-art socio-psychological theories and cognitive models focus on explaining how the accuracy of fake news is judged on average, with little consideration of the individual. In this paper, a breadth of core models are comparatively assessed on their predictive accuracy for the individual decision maker, i.e., how well can models predict an individual’s decision before the decision is made. To conduct this analysis, it requires the raw responses of each individual and the implementation and adaption of theories to predict the individual’s response. Building on methods formerly applied on smaller and more limited datasets, we used three previously collected large datasets with a total of 3794 participants and searched for, analyzed and refined existing classical and heuristic modeling approaches. The results suggest that classical reasoning, sentiment analysis models and heuristic approaches can best predict the “Accept” or “Reject” response of a person, headed by a model put together from research by Jay Van Bavel, while other models such as an implementation of “motivated reasoning” performed worse. Further, hybrid models that combine pairs of individual models achieve a significant increase in performance, pointing to an adaptive toolbox.

Usefulness of familiarity signals during recognition depends on test format: Neurocognitive evidence for a core assumption of the CLS framework

Familiarity-based discrimination between studied items and similar foils in yes/no recognition memory tests is relatively poor. The complementary learning systems (CLS) framework explains this with the small difference in familiarity strength between targets and foils. The framework, however, also predicts that familiarity values of targets and corresponding similar foils are directly comparable - as long as they are presented side by side in a forced-choice corresponding (FCC) test. This is because in each trial, targets tend to be more familiar than their corresponding foils. In contrast, when forced-choice displays contain non-corresponding foils (FCNC) which are similar to other studied items, familiarity values are not directly comparable (as in yes/no-tasks). In a recognition memory task with pictures of objects, we found that the putative ERP correlate of familiarity, the mid-frontal old/new effect for targets vs. foils, was significantly larger in FCC compared to FCNC displays. Moreover, single-trial target-foil amplitude differences predicted the accuracy of the recognition judgment. This study supports the assumption of the CLS framework that the test format can influence the diagnostic reliability of familiarity. Moreover, it implies that the mid-frontal old/new effect does not reflect the difference in the familiarity signal between studied and non-studied items but the task-adequate assessment of this signal.

Dynamics of brain activity reveal a unitary recognition signal

Dual-process models of recognition memory typically assume that independent familiarity and recollection signals with distinct temporal profiles can each lead to recognition (enabling 2 routes to recognition), whereas single-process models posit a unitary "memory strength" signal. Using multivariate classifiers trained on spectral electroencephalogram (EEG) features, we quantified neural evidence for recognition decisions as a function of time. Classifiers trained on a small portion of the decision period performed similarly to those also incorporating information from previous time points indicating that neural activity reflects an integrated evidence signal. We propose a single-route account of recognition memory that is compatible with contributions from familiarity and recollection signals, but relies on a unitary evidence signal that integrates all available evidence. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Further evidence for the memory state heuristic: Recognition latency predictions for binary inferences

According to the recognition heuristic (RH), for decision domains where recognition is a valid predictor of a choice criterion, recognition alone is used to make inferences whenever one object is recognized and the other is not, irrespective of further knowledge. Erdfelder, Küpper-Tetzel, and Mattern (2011) questioned whether the recognition judgment itself affects decisions or rather the memory strength underlying it. Specifically, they proposed to extend the RH to the memory state heuristic (MSH), which assumes a third memory state of uncertainty in addition to recognition certainty and rejection certainty. While the MSH already gathered significant support, one of its basic and more counterintuitive predictions has not been tested so far: In guessing pairs (none of the objects recognized), the object more slowly judged as unrecognized should be preferred, since it is more likely to be in a higher memory state. In this paper, we test this prediction along with other recognition latency predictions of the MSH, thereby adding to the body of research supporting the MSH.

Use of the familiarity difference cue in inferential judgments

The familiarity difference cue has been regarded as a general cue for making inferential judgments (Honda, Abe, Matsuks, & Yamagishi in Memory and Cognition, 39(5), 851-863, 2011; Schwikert & Curran in Journal of Experimental Psychology: General, 143(6), 2341-2365, 2014). The current study tests a model of inference based on familiarity differences that encompasses the recognition heuristic (Goldstein & Gigerenzer, 1999, Goldstein & Gigerenzer in Psychological Review, 109(1), 75-90, 2002). In two studies, using a large pool of stimuli, participants rated their familiarity of cities and made choices on a typical city-size task. The data were fitted with the r-s model (Hilbig, Erdfelder, & Pohl in, Journal of Experimental Psychology: Learning Memory and Cognition, 37(4), 827-839, 2011), which was adapted to include familiarity differences. The results indicated that people used the familiarity difference cue because the participants ignored further knowledge in a substantial number of cases when the familiarity difference cue was available. An analysis of reaction-time data further indicated that the response times were shorter for heuristic judgments than for knowledge-only-based judgments. Furthermore, when knowledge was available, the response times were shorter when knowledge was congruent with a heuristic cue than when it was in conflict with it. Differences between the familiarity difference cue and the fluency heuristic (Schooler & Hertwig, 2005, Psychological Review, 112, 610-628) are discussed.

Measuring Age-Related Differences in Using a Simple Decision Strategy

Abstract. According to the recognition heuristic, decision makers base their inferences on recognition alone, assuming that recognized objects have larger criterion values than unrecognized ones. Knowing that recognition is a valid cue and thus using the recognition heuristic should increase with age. This was tested in two experiments with preadolescents (N = 140), adolescents (N = 186), and adults (N = 78). The results show, as expected, a monotonic age-related trend in the improvement of domain-specific knowledge but, unexpectedly, a non-monotonic one for using the recognition heuristic. More specifically, use of the recognition heuristic increased from preadolescents to adolescents, but then dropped for adults.

Use of the recognition heuristic depends on the domain's recognition validity, not on the recognition validity of selected sets of objects

According to the recognition-heuristic theory, decision makers solve paired comparisons in which one object is recognized and the other not by recognition alone, inferring that recognized objects have higher criterion values than unrecognized ones. However, success-and thus usefulness-of this heuristic depends on the validity of recognition as a cue, and adaptive decision making, in turn, requires that decision makers are sensitive to it. To this end, decision makers could base their evaluation of the recognition validity either on the selected set of objects (the set's recognition validity), or on the underlying domain from which the objects were drawn (the domain's recognition validity). In two experiments, we manipulated the recognition validity both in the selected set of objects and between domains from which the sets were drawn. The results clearly show that use of the recognition heuristic depends on the domain's recognition validity, not on the set's recognition validity. In other words, participants treat all sets as roughly representative of the underlying domain and adjust their decision strategy adaptively (only) with respect to the more general environment rather than the specific items they are faced with.

Memory-Based Simple Heuristics as Attribute Substitution: Competitive Tests of Binary Choice Inference Models

Some researchers on binary choice inference have argued that people make inferences based on simple heuristics, such as recognition, fluency, or familiarity. Others have argued that people make inferences based on available knowledge. To examine the boundary between heuristic and knowledge usage, we examine binary choice inference processes in terms of attribute substitution in heuristic use (Kahneman & Frederick, 2005). In this framework, it is predicted that people will rely on heuristic or knowledge-based inference depending on the subjective difficulty of the inference task. We conducted competitive tests of binary choice inference models representing simple heuristics (fluency and familiarity heuristics) and knowledge-based inference models. We found that a simple heuristic model (especially a familiarity heuristic model) explained inference patterns for subjectively difficult inference tasks, and that a knowledge-based inference model explained subjectively easy inference tasks. These results were consistent with the predictions of the attribute substitution framework. Issues on usage of simple heuristics and psychological processes are discussed.