Cognitive Psychology最新文献

There is a high-capacity store of brief time span (∼1000 ms) which information enters from perceptual processing, often called iconic memory or sensory memory. It is proposed that a main function of this store is to hold recent perceptual information in a temporally segregated representation, named the perceptual timescape. The perceptual timescape is a continually active representation of change and continuity over time that endows the perceived present with a perceived history. This is accomplished primarily by two kinds of time marking information: time distance information, which marks all items of information in the perceptual timescape according to how far in the past they occurred, and ordinal temporal information, which organises items of information in terms of their temporal order. Added to that is information about connectivity of perceptual objects over time. These kinds of information connect individual items over a brief span of time so as to represent change, persistence, and continuity over time. It is argued that there is a one-way street of information flow from perceptual processing either to the perceived present or directly into the perceptual timescape, and thence to working memory. Consistent with that, the information structure of the perceptual timescape supports postdictive reinterpretations of recent perceptual information. Temporal integration on a time scale of hundreds of milliseconds takes place in perceptual processing and does not draw on information in the perceptual timescape, which is concerned with temporal segregation, not integration.

In a standard individuation task, infants see two different objects emerge in alternation from behind a screen. If they can assign distinct categorical descriptors to the two objects, they expect to see both objects when the screen is lowered; if not, they have no expectation at all about what they will see (i.e., two objects, one object, or no object). Why is contrastive categorical information critical for success at this task? According to the kind account, infants must decide whether they are facing a single object with changing properties or two different objects with stable properties, and access to permanent, intrinsic, kind information for each object resolves this difficulty. According to the two-system account, however, contrastive categorical descriptors simply provide the object-file system with unique tags for individuating the two objects and for communicating about them with the physical-reasoning system. The two-system account thus predicts that any type of contrastive categorical information, however temporary or scant it may be, should induce success at the task. Two experiments examined this prediction. Experiment 1 tested 14-month-olds (N = 96) in a standard task using two objects that differed only in their featural properties. Infants succeeded at the task when the object-file system had access to contrastive temporary categorical descriptors derived from the objects’ distinct causal roles in preceding support events (e.g., formerly a support, formerly a supportee). Experiment 2 tested 9-month-olds (N = 96) in a standard task using two objects infants this age typically encode as merely featurally distinct. Infants succeeded when the object-file system had access to scant categorical descriptors derived from the objects’ prior inclusion in static arrays of similarly shaped objects (e.g., block-shaped objects, cylinder-shaped objects). These and control results support the two-system account’s claim that in a standard task, contrastive categorical descriptors serve to provide the object-file system with unique tags for the two objects.

In a fundamentally uncertain world, sound information processing is a prerequisite for effective behavior. Given that information processing is subject to inevitable cognitive imprecision, decision makers should adapt to this imprecision and to the resulting epistemic uncertainty when taking risks. We tested this metacognitive ability in two experiments in which participants estimated the expected value of different number distributions from sequential samples and then bet on their own estimation accuracy. Results show that estimates were imprecise, and this imprecision increased with higher distributional standard deviations. Importantly, participants adapted their risk-taking behavior to this imprecision and hence deviated from the predictions of Bayesian models of uncertainty that assume perfect integration of information. To explain these results, we developed a computational model that combines Bayesian updating with a metacognitive awareness of cognitive imprecision in the integration of information. Modeling results were robust to the inclusion of an empirical measure of participants’ perceived variability. In sum, we show that cognitive imprecision is crucial to understanding risk taking in decisions from experience. The results further demonstrate the importance of metacognitive awareness as a cognitive building block for adaptive behavior under (partial) uncertainty.

Position-specific intrusions of items from prior lists are rare but important phenomena that distinguish broad classes of theory in serial memory. They are uniquely predicted by position coding theories, which assume items on all lists are associated with the same set of codes representing their positions. Activating a position code activates items associated with it in current and prior lists in proportion to their distance from the activated position. Thus, prior list intrusions are most likely to come from the coded position. Alternative “item dependent” theories based on associations between items and contexts built from items have difficulty accounting for the position specificity of prior list intrusions. We tested the position coding account with a position-cued recognition task designed to produce prior list interference. Cuing a position should activate a position code, which should activate items in nearby positions in the current and prior lists. We presented lures from the prior list to test for position-specific activation in response time and error rate; lures from nearby positions should interfere more. We found no evidence for such interference in 10 experiments, falsifying the position coding prediction. We ran two serial recall experiments with the same materials and found position-specific prior list intrusions. These results challenge all theories of serial memory: Position coding theories can explain the prior list intrusions in serial recall and but not the absence of prior list interference in cued recognition. Item dependent theories can explain the absence of prior list interference in cued recognition but cannot explain the occurrence of prior list intrusions in serial recall.

Linguistic syntax has often been claimed as uniquely complex due to features like anaphoric relations and distance dependencies. However, visual narratives of sequential images, like those in comics, have been argued to use sequencing mechanisms analogous to those in language. These narrative structures include “refiner” panels that “zoom in” on the contents of another panel. Similar to anaphora in language, refiners indexically connect inexplicit referential information in one unit (refiner, pronoun) to a more informative “antecedent” elsewhere in the discourse. Also like in language, refiners can follow their antecedents (anaphoric) or precede them (cataphoric), along with having either proximal or distant connections. We here explore the constraints on visual narrative refiners created by modulating these features of order and distance. Experiment 1 examined participants’ preferences for where refiners are placed in a sequence using a force-choice test, which revealed that refiners are preferred to follow their antecedents and have proximal distances from them. Experiment 2 then showed that distance dependencies lead to slower self-paced viewing times. Finally, measurements of event-related brain potentials (ERPs) in Experiment 3 revealed that these patterns evoke similar brain responses as referential dependencies in language (i.e., N400, LAN, Nref). Across all three studies, the constraints and (neuro)cognitive responses to refiners parallel those shown to anaphora in language, suggesting domain-general constraints on the sequencing of referential dependencies.

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.