The computations involved in statistical learning have long been debated. Here, we build on work suggesting that a basic memory process, chunking, may account for the processing of statistical regularities into larger units. Drawing on methods from the memory literature, we developed a novel paradigm to test statistical learning by leveraging a robust phenomenon observed in serial recall tasks: that short‐term memory is fundamentally shaped by long‐term distributional learning. In the statistically induced chunking recall (SICR) task, participants are exposed to (...) an artificial language, using a standard statistical learning exposure phase. Afterward, they recall strings of syllables that either follow the statistics of the artificial language or comprise the same syllables presented in a random order. We hypothesized that if individuals had chunked the artificial language into word‐like units, then the statistically structured items would be more accurately recalled relative to the random controls. Our results demonstrate that SICR effectively captures learning in both the auditory and visual modalities, with participants displaying significantly improved recall of the statistically structured items, and even recall specific trigram chunks from the input. SICR also exhibits greater test–retest reliability in the auditory modality and sensitivity to individual differences in both modalities than the standard two‐alternative forced‐choice task. These results thereby provide key empirical support to the chunking account of statistical learning and contribute a valuable new tool to the literature. (shrink)

In the Deese-Roediger/McDermott paradigm, distinctive encoding of list items typically reduces false recognition of critical lures relative to a read-only control. This reduction can be due to enhanced item-specific processing, reduced relational processing, and/or increased test-based monitoring. However, it is unclear whether distinctive encoding reduces false recognition in a selective or global manner. To examine this question, participants studied DRM lists using a distinctive item-specific anagram generation task and then completed a recognition test which included both DRM critical lures and (...) either strongly related lures or weakly related lures. Compared to a read-control group, the generate groups showed increased correct recognition and decreased false recognition of all lure types. We then estimated the separate contributions of encoding and retrieval processes using signal-detection indices. Generation improved correct recognition by both increasing encoding of memory information for list words and by increasing memory monitoring at test. Generation reduced false recognition by reducing the encoding of memory information and by increasing memory monitoring at test. The reduction in false recognition was equivalent for critical lures and related lures, indicating that generation globally reduces the encoding of related non-presented items at study, while globally increasing list-theme-based monitoring at test. (shrink)

The study of decision making has traditionally been dominated by axiomatic utility theories. More recently, an alternative approach, which focuses on the micro-mechanisms of the underlying deliberation process, has been shown to account for several "paradoxes" in human choice behavior for which simple utility-based approaches cannot. Decision field theory (DFT) is a cognitive-dynamical model of decision making and preferential choice, built on the fundamental principle that decisions are based on the accumulation of subjective evaluations of choice alternatives until a threshold (...) criterion is met. This article extends the basic DFT framework to the domain of dynamic decision making. DFT-Dynamic is proposed as a new alternative to normative backward induction. Through its attention to the processes underlying planning and deliberation DFT-D provides simple, emergent explanations for violations of choice principles traditionally taken as evidence of irrationality. A recent multistage decision making study is used to showcase the model's efficacy for developing cognitive models of individual strategies. (shrink)

Horton and Gerrig outlined a memory-based processing model of conversational common ground that provided a description of how speakers could both strategically and automatically gain access to information about others through domain-general memory processes acting over ordinary memory traces. In this article, we revisit this account, reviewing empirical findings that address aspects of this memory-based model. In doing so, we also take the opportunity to clarify what we believe this approach implies about the cognitive psychology of common ground, and just (...) as important, what it does not imply. We also highlight related areas of research demonstrating how general cognitive processes can constrain access to relevant knowledge in ways that shape both language production and comprehension. (shrink)

We review how leaky competing accumulators (LCAs) can be used to model decision making in two‐alternative, forced‐choice tasks, and we show how they reduce to drift diffusion (DD) processes in special cases. As continuum limits of the sequential probability ratio test, DD processes are optimal in producing decisions of specified accuracy in the shortest possible time. Furthermore, the DD model can be used to derive a speed–accuracy trade‐off that optimizes reward rate for a restricted class of two alternative forced‐choice decision (...) tasks. We review findings that compare human performance with this benchmark, and we reveal both approximations to and deviations from optimality. We then discuss three potential sources of deviations from optimality at the psychological level—avoidance of errors, poor time estimation, and minimization of the cost of control—and review recent theoretical and empirical findings that address these possibilities. We also discuss the role of cognitive control in changing environments and in modulating exploitation and exploration. Finally, we consider physiological factors in which nonlinear dynamics may also contribute to deviations from optimality. (shrink)

Discrete choice experiments—selecting the best and/or worst from a set of options—are increasingly used to provide more efficient and valid measurement of attitudes or preferences than conventional methods such as Likert scales. Discrete choice data have traditionally been analyzed with random utility models that have good measurement properties but provide limited insight into cognitive processes. We extend a well-established cognitive model, which has successfully explained both choices and response times for simple decision tasks, to complex, multi-attribute discrete choice data. The (...) fits, and parameters, of the extended model for two sets of choice data (involving patient preferences for dermatology appointments, and consumer attitudes toward mobile phones) agree with those of standard choice models. The extended model also accounts for choice and response time data in a perceptual judgment task designed in a manner analogous to best–worst discrete choice experiments. We conclude that several research fields might benefit from discrete choice experiments, and that the particular accumulator-based models of decision making used in response time research can also provide process-level instantiations for random utility models. (shrink)

In 2011, van Dijck and Fias described a positional SNARC effect: the SPoARC. To-be-remembered items presented centrally on a screen seemed to acquire a left-to-right spatial dimension. If confirmed, this spatialization could be crucial for immediate memory theories. However, given the intricate links between visual and spatial dimensions, this effect could be due to the visual presentation, which could have probed the left-to-right direction of reading/writing. To allow a generalization of this effect, we adapted van Dijck and Fias's task using (...) an auditory version of Sternberg's paradigm. Lists of five consonants were auditorily presented at a rate of 3 s/item. A SPoARC effect was observed. The consequences are discussed first from an immediate memory perspective, putting forward the view that order could be coded through spatialization, and then in terms of similarities between SPoARC and SNARC. (shrink)

Epistemic feelings like tip-of-the-tongue experiences, feelings of knowing, and feelings of confidence tell us when a memory can be recalled and when a judgment was correct. Thus, they appear to be a form of metacognition, but a curious one: they tell us about content we cannot access, and the information is supplied by a feeling. Evaluativism is the claim that epistemic feelings are components of a distinct, primitive metacognitive mechanism that operates on its own set of inputs. These inputs are (...) heuristics that correlate with the presence of mental content that can’t be accessed directly. I will argue that evaluativism is unmotivated, unsupported, and ill-conceived. I will critique the philosophical and empirical arguments for evaluativism and conclude that there is no reason to posit a distinct mechanism to explain epistemic feelings. I will conclude, however, that epistemic feelings may constitute a nonconceptual form of metacognition, which if true is a significant claim. (shrink)

A framing bias shows risk aversion in problems framed as “gains” and risk seeking in problems framed as “losses,” even when these are objectively equivalent and probabilities and outcomes values are explicitly provided. We test this framing bias in situations where decision makers rely on their own experience, sampling the problem's options and seeing the outcomes before making a choice. In Experiment 1, we replicate the framing bias in description-based decisions and find risk indifference in gains and losses in experience-based (...) decisions. Predictions of an Instance-Based Learning model suggest that objective probabilities as well as the number of samples taken are factors that contribute to the lack of framing effect. We test these two factors in Experiment 2 and find no framing effect when a few samples are taken but when large samples are taken, the framing effect appears regardless of the objective probability values. Implications of behavioral results and cognitive modeling are discussed. (shrink)

Cognitive science continues to make a compelling case for having a coherent, unique, and fundamental subject of inquiry: What is the nature of minds, where do they come from, and how do they work? Central to this inquiry is the notion of agents that have goals, one of which is their own persistence, who use dynamically constructed knowledge to act in the world to achieve those goals. An agentive perspective explains why a special class of systems have a cluster of (...) co‐occurring capacities that enable them to exhibit adaptive behavior in a complex environment: perception, attention, memory, representation, planning, and communication. As an intellectual endeavor, cognitive science may not have achieved a hard core of uncontested assumptions that Lakatos (1978) identifies as emblematic of a successful research program, but there are alternative conceptions according to which cognitive science has been successful. First, challenges of the early, core tenet of “Mind as Computation” have helped put cognitive science on a stronger foundation—one that incorporates relations between minds and their environments. Second, even if a full cross‐disciplinary theoretic consensus is elusive, cognitive science can inspire distant, deep, and transformative connections between pairs of fields. To be intellectually vital, cognitive science need not resemble a traditional discipline with its associated insularity and unchallenged assumptions. Instead, there is strength and resilience in the diverse perspectives and methods that cognitive science assembles together. This interdisciplinary enterprise is fragile and perhaps inherently unstable, as the looming absorption of cognitive science into psychology shows. Still, for many researchers, the excitement and benefits of triangulating on the nature of minds by integrating diverse cases cannot be secured by a stable discipline with an uncontested core of assumptions. (shrink)

I present a computational-level model of semantic interference effects in online word production within a rate–distortion framework. I consider a bounded-rational agent trying to produce words. The agent's action policy is determined by maximizing accuracy in production subject to computational constraints. These computational constraints are formalized using mutual information. I show that semantic similarity-based interference among words falls out naturally from this setup, and I present a series of simulations showing that the model captures some of the key empirical patterns (...) observed in Stroop and Picture–Word Interference paradigms, including comparisons to human data from previous experiments. (shrink)

In recent years quantum probability models have been used to explain many aspects of human decision making, and as such quantum models have been considered a viable alternative to Bayesian models based on classical probability. One criticism that is often leveled at both kinds of models is that they lack a clear interpretation in terms of psychological mechanisms. In this paper we discuss the mechanistic underpinnings of a quantum walk model of human decision making and response time. The quantum walk (...) model is compared to standard sequential sampling models, and the architectural assumptions of both are considered. In particular, we show that the quantum model has a natural interpretation in terms of a cognitive architecture that is both massively parallel and involves both co-operative and competitive interactions between units. Additionally, we introduce a family of models that includes aspects of the classical and quantum walk models. (shrink)