Cognitive Psychology最新文献

People are often faced with repeated risky decisions that involve uncertainty. In sequential risk-taking tasks, like the Balloon Analogue Risk Task (BART), the underlying decision process is not yet fully understood. Dual-process theory proposes that human cognition involves two main families of processes, often referred to as System 1 (fast and automatic) and System 2 (slow and conscious). We cross models of the BART with different architectures of the two systems to yield a pool of computational dual-process models that are evaluated on multiple performance measures (e.g., parameter identifiability, model recovery, and predictive accuracy). Results show that the best-performing model configuration assumes the two systems are competitively connected, an evaluation process based on the Scaled Target Learning model of the BART, and an assessment rate that incorporates sensitivity to the trial number, pumping opportunity, and bias to engage in System 1. Findings also shed light on how modeling choices and response times in a dual-process framework can benefit our understanding of sequential risk-taking behavior.

Response inhibition is a key attribute of human executive control. Standard stop-signal tasks require countermanding a single response; the speed at which that response can be inhibited indexes the efficacy of the inhibitory control networks. However, more complex stopping tasks, where one or more components of a multi-component action are cancelled (i.e., response-selective stopping) cannot be explained by the independent-race model appropriate for the simple task (Logan and Cowan 1984). Healthy human participants ($n=28$; 10 male; 19–40 years) completed a response-selective stopping task where a ‘go’ stimulus required simultaneous (bimanual) button presses in response to left and right pointing green arrows. On a subset of trials (30%) one, or both, arrows turned red (constituting the stop signal) requiring that only the button-press(es) associated with red arrows be cancelled. Electromyographic recordings from both index fingers (first dorsal interosseous) permitted the assessment of both voluntary motor responses that resulted in overt button presses, and activity that was cancelled prior to an overt response (i.e., partial, or covert, responses). We propose a simultaneously inhibit and start (SIS) model that extends the independent race model and provides a highly accurate account of response-selective stopping data. Together with fine-grained EMG analysis, our model-based analysis offers converging evidence that the selective-stop signal simultaneously triggers a process that stops the bimanual response and triggers a new unimanual response corresponding to the green arrow. Our results require a reconceptualisation of response-selective stopping and offer a tractable framework for assessing such tasks in healthy and patient populations.

Significance Statement

Response inhibition is a key attribute of human executive control, frequently investigated using the stop-signal task. After initiating a motor response to a go signal, a stop signal occasionally appears at a delay, requiring cancellation of the response. This has been conceptualised as a ‘race’ between the go and stop processes, with the successful (or failed) cancellation determined by which process wins the race. Here we provide a novel computational model for a complex variation of the stop-signal task, where only one component of a multicomponent action needs to be cancelled. We provide compelling muscle activation data that support our model, providing a robust and plausible framework for studying these complex inhibition tasks in both healthy and pathological cohorts.

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.

A variety of letter string representations has been proposed in the reading literature to account for empirically established orthographic similarity effects from masked priming studies. However, these similarity effects have not been explored in episodic memory paradigms and very few memory models have employed orthographic representation of words. In the current work, through two recognition memory experiments employing word and pseudoword stimuli respectively, we empirically established a set of key orthographic similarity effects for the first time in recognition memory – namely the substitution effect, transposition effect and reverse effect in recognition memory of words and pseudowords, and a start-letter importance in recognition memory of words. Subsequently, we compared orthographic representations from the reading literature including slot coding, closed-bigram, open-bigram and the overlap model. Each of these representations was situated in a global matching model and fitted to recognition performance via Luce’s choice rule in a hierarchical Bayesian framework. Model selection results showed support for the open-bigram representation in both experiments.

Many decisions we face daily entail deliberation about how to coordinate resources shared between multiple, competing goals. When time permits, people appear to approach these goal prioritization problems by analytically considering all goal-relevant information to arrive at a prioritization decision. However, it is not yet clear if this normative strategy extends to situations characterized by resource constraints such as when deliberation time is scarce or cognitive load is high. We evaluated the questions of how limited deliberation time and cognitive load affect goal prioritization decisions across a series of experiments using a gamified experimental task, which required participants to make a series of interdependent goal prioritization decisions. We fit several candidate models to experimental data to identify decision strategy adaptations at the individual subject-level. Results indicated that participants tended to opt for a simple heuristic strategy when cognitive resources were constrained rather than making a general tradeoff between speed and accuracy (e.g., the type of tradeoff that would be predicted by evidence accumulation models). The most common heuristic strategy involved disproportionately weighing information about goal deadlines compared to other goal-relevant information such as the goal’s difficulty and the goal’s subjective value.

How speakers sequence words and phrases remains a central question in cognitive psychology. Here we focused on understanding the representations and processes that underlie structural priming, the speaker’s tendency to repeat sentence structures encountered earlier. Verb repetition from the prime to the target led to a stronger tendency to produce locative variants of the spray-load alternation following locative primes (e.g., load the boxes into the van) than following with primes (e.g., load the van with the boxes). These structural variants had the same constituent structure, ruling out abstract syntactic structure as the source of the verb boost effect. Furthermore, using cleft constructions (e.g., What the assistant loaded into the lift was the equipment), we found that the thematic role order (thematic role-position mappings) of the prime can persist separately from its argument structure (thematic role-syntactic function mappings). Moreover, both priming effects were enhanced by verb repetition and interacted with each other when the construction of the prime was also repeated in the target. These findings are incompatible with the traditional staged model of grammatical encoding, which postulates the independence of abstract syntax from thematic role information. We propose the interactive structure-building account, according to which speakers build a sentence structure by choosing a thematic role order and argument structure interactively based on their prior co-occurrence together with other structurally relevant information such as verbs and constructions.

Intertemporal preference has been investigated mainly with a choice paradigm. However, a matching paradigm might be more informative for a proper inference about intertemporal preference and a deep understanding of the underlying cognitive mechanisms. This research involved two empirical studies using the matching paradigm and compared various corresponding dynamic models. These models were developed under either the framework of decision field theory, an exemplar theory assuming evidence accumulation, or a non-evidence-accumulation framework built upon the well-established notions of random utility and discrimination threshold (i.e., the RUDT framework). Most of these models were alternative-based whereas the others were attribute-based ones. Participants in Study 1 were required to fill in the amount of an immediate stimulus to make it as attractive as a delayed stimulus, whereas those in Study 2 needed to accomplish a more general matching task in which either the payoff amount or delay length of one stimulus was missing. Consistent behavioral regularities regarding both matching values and response times were revealed in these studies. The results of model comparison favored in general the RUDT framework as well as an attribute-based perspective on intertemporal preference. In addition, the predicted matching values and response times of the best RUDT model were also highly correlated with the observed data and replicated most observed behavioral regularities. Together, this research and previous modeling work on intertemporal choice suggest that evidence accumulation is not essential for generating intertemporal preference. Future research should examine the validity of the new framework in other preferential decisions for a more stringent test of the framework.

It has long been assumed in economic theory that multi-attribute decisions involving several attributes or dimensions – such as probabilities and amounts of money to be earned during risky choices – are resolved by first combining the attributes of each option to form an overall expected value and then comparing the expected values of the alternative options, using a unique evidence accumulation process. A plausible alternative would be performing independent comparisons between the individual attributes and then integrating the results of the comparisons afterwards. Here, we devise a novel method to disambiguate between these types of models, by orthogonally manipulating the expected value of choice options and the relative salience of their attributes. Our results, based on behavioral measures and drift-diffusion models, provide evidence in favor of the framework where information about individual attributes independently impacts deliberation. This suggests that risky decisions are resolved by running in parallel multiple comparisons between the separate attributes – possibly alongside an additional comparison of expected value. This result stands in contrast with the assumption of standard economic theory that choices require a unique comparison of expected values and suggests that at the cognitive level, decision processes might be more distributed than commonly assumed. Beyond our planned analyses, we also discovered that attribute salience affects people of different risk preference type in different ways: risk-averse participants seem to focus more on probability, except when monetary amount is particularly high; risk-neutral/seeking participants, in contrast, seem to focus more on monetary amount, except when probability is particularly low.

There are several ways in which retrieval during a memory test can harm memory: (a) retrieval can cause an increase in interference due to the storage of additional information (i.e., item-noise); (b) retrieval can decrease accessibility to studied items due to context drift; and (c) retrieval can result in a trade in accuracy for speed as testing progresses. While these mechanisms produce similar outcomes in a study-test paradigm, they are dissociated in the ‘continuous’ recognition paradigm, where items are presented continuously and a participant’s task is to detect a repeat of an item. In this paradigm, context drift results in worse performance with increasing study-test lag (the lag effect), whereas increasing item-noise is evident in a decrease in performance for later test trials in the sequence (the test position effect [TPE]). In the present investigation, we measured the influences of item-noise, context drift, and decision-related factors in a novel continuous recognition dataset using variants of the Osth et al. (2018) global matching model. We fit both choice and response times at the single trial level using state-of-the-art hierarchical Bayesian methods while incorporating crucial amendments to the modeling framework, including multiple context scales and sequential effects. We found that item-noise was responsible for producing the TPE, context drift decreased the magnitude of the TPE (by diminishing the impact of item-noise), and speed-accuracy changes had some minor effects that varied across participants.

Connectives such as but are critical for building coherent discourse. They also express meanings that do not fit neatly into the standard distinction between semantics and implicated pragmatics. How do children acquire them? Corpus analyses indicate that children use these words in a sophisticated way by the early pre-school years, but a small number of experimental studies also suggest that children do not understand that but has a contrastive meaning until they reach school age. In a series of eight experiments we tested children’s understanding of contrastive but compared to the causal connective so, by using a word learning paradigm (e.g., It was a warm day but/so Katy put on a pagle). When the connective so was used, we found that even 2-year-olds inferred a novel word meaning that was associated with the sentence context (a t-shirt). However, for the connective but, children did not infer a non-associated contrastive meaning (a winter coat) until age 7. Before that, even 5-year-old children reliably inferred an associated referent, indicating that they failed to correctly assign but a contrastive meaning. Five control experiments ruled out explanations for this pattern based on basic task demands, sentence processing skills or difficulty making adult-like inferences. A sixth experiment reports one particular context in which five-year-olds do interpret but contrastively. However, that same context also leads children to interpret so contrastively. We conclude that children’s sophisticated production of connectives like but and so masks a major difficulty learning their meanings. We suggest that discourse connectives incorporate a class of words whose usage is easy to mimic, but whose meanings are difficult to acquire from everyday conversations, with implications for theories of word learning and discourse processing.