Complex systems are to be seen as typically having multiple levels of organization. For instance, in the behavioural and cognitive sciences, there has been a long lasting trend, promoted by the seminal work of David Marr, putting focus on three distinct levels of analysis: the computational level, accounting for the What and Why issues, the algorithmic and the implementational levels specifying the How problem. However, the tremendous developments in neuroscience knowledge about processes at different scales of organization together with the (...) complexity of today cognitive theories suggest that there will hardly be only three levels of explanation. Instead, there will be many different degrees of commitments corresponding to the different granularities—from high-level (behavioural) models to low-level (neural and molecular) models of the cognitive research program. For instance, Bayesian approaches, that are usually advocated for formalizing Marr’s computational level and rational behaviour, have even been adopted to model synaptic plasticity and axon guidance by molecular gradients. As a result, we can consider the behavioural scientist as dealing with models at a multiplicity of levels. The purpose of this Research Topic in Frontiers in Theoretical and Philosophical Psychology is to promote an approach to the role of the levels and explanation and models which is of interest for cognitive scientists, neuroscientists, psychologists, behavioural scientists, and philosophers of science. (shrink)

Presentation times of study words presented in the Deese/Roediger and McDermott (DRM) paradigm varied from 20 to 2000 ms per word in an attempt to replicate the false memory effect following extremely short presentations reported by . Both in a within-subjects design (Experiment 1) and in a between-subjects design (Experiment 2) subjects showed memory for studied words as well as a false memory effect for related critical lures in the 2000-ms condition. However, in the conditions with shorter presentation times (20 (...) ms in Experiment 1; 20 and 40 ms in Experiment 2) no memory for studied words, nor a false memory effect was found. We argue that there is at present no strong evidence supporting the claim for a nonconscious basis of the false memory effect. (shrink)

Cognitive architectures are unified theories of cognition that take the form of computational formalisms. They support computational models that collectively account for large numbers of empirical regularities using small numbers of computational mechanisms. Empirical coverage and parsimony are the most prominent criteria by which architectures are designed and evaluated, but they are not the only ones. This paper considers three additional criteria that have been comparatively undertheorized. (a) Successful architectures possess subjective and intersubjective meaning, making cognition comprehensible to individual cognitive (...) scientists and organizing groups of like-minded cognitive scientists into genuine communities. (b) Successful architectures provide idioms that structure the design and interpretation of computational models. (c) Successful architectures are strange: They make provocative, often disturbing, and ultimately compelling claims about human information processing that demand evaluation. (shrink)

Recent evidence suggests that experienced events are often mapped to too many episodic states, including those that are logically or experimentally incompatible with one another. For example, episodic over-distribution patterns show that the probability of accepting an item under different mutually exclusive conditions violates the disjunction rule. A related example, called subadditivity, occurs when the probability of accepting an item under mutually exclusive and exhaustive instruction conditions sums to a number >1. Both the over-distribution effect and subadditivity have been widely (...) observed in item and source-memory paradigms. These phenomena are difficult to explain using standard memory frameworks, such as signal-detection theory. A dual-trace model called the over-distribution model can explain the episodic over-distribution effect, but not subadditivity. Our goal is to develop a model that can explain both effects. In this paper, we propose the Generalized Quantum Episodic Memory model, which extends the Quantum Episodic Memory model developed by Brainerd, Wang, and Reyna. We test GQEM by comparing it to the OD model using data from a novel item-memory experiment and a previously published source-memory experiment examining the over-distribution effect. Using the best-fit parameters from the over-distribution experiments, we conclude by showing that the GQEM model can also account for subadditivity. Overall these results add to a growing body of evidence suggesting that quantum probability theory is a valuable tool in modeling recognition memory. (shrink)

Evidence for incubation effects in problem-solving is increasing, but the mechanisms that underlie incubation are unclear. An experiment tested two hypotheses about incubation: Spreading activation and opportunistic assimilation. Participants solved easy or difficult remote associates tasks without incubation period, or with an incubation period filled with high or low cognitive load tasks. A lexical decision task with cue and neutral words was given either before or after a second problem attempt. When solving difficult problems, the low-load incubation group benefitted more (...) from the presence of a cue than the high-load incubation group, and the opposite was found with easy problems. Neither incubation nor an initial problem attempt affected lexical decision times to cue words. The results favour opportunistic assimilation as an explanation of incubation effects. They also suggest a differential role for attentional allocation depending on problem difficulty, easy problems benefitting from focused attent.. (shrink)

Topics in Cognitive Science, Volume 14, Issue 3, Page 621-633, July 2022.

Memory is modified through the act of retrieval. Although retrieving a target piece of information may strengthen the retrieved information itself, it may also serve to weaken retention of related information. This phenomenon, termed retrieval-induced forgetting, has garnered substantial interest for its implications as to why forgetting occurs. The present study attempted to replicate the seminal work by Anderson, Bjork, and Bjork (1994) on retrieval-induced forgetting, given the apparent sensitivity of the effect to certain deviations from the original paradigm developed (...) to study the phenomenon. The study extends the conditions under which retrieval-induced forgetting has been examined by utilizing both a traditional college undergraduate sample (Experiment 1), along with a more diverse internet sample (Experiment 2). In addition, Experiment 3 details a replication attempt of retrieval-induced forgetting using Anderson and Spellman’s (1995) independent cue procedure. Retrieval-induced forgetting was observed when using the traditional retrieval practice paradigm with undergraduate (Experiment 1) and internet (Experiment 2) samples, though the effect was not found when using the independent cue procedure (Experiment 3). Thus, the study can provide an indication as to the robustness of retrieval-induced forgetting to deviations from the traditional college undergraduate samples that have been used in the majority of existing research on the effect. (shrink)

This commentary gives a personal perspective on modeling and modeling developments in cognitive science, starting in the 1950s, but focusing on the author’s personal views of modeling since training in the late 1960s, and particularly focusing on advances since the official founding of the Cognitive Science Society. The range and variety of modeling approaches in use today are remarkable, and for many, bewildering. Yet to come to anything approaching adequate insights into the infinitely complex fields of mind, brain, and intelligent (...) systems, an extremely wide array of modeling approaches is vital and necessary. (shrink)