Speeded Decision Task Research Articles

Assessment of embodied visuospatial perspective taking in augmented reality: insights from a reaction time task

Understanding another person’s visual perceptions is known as visuospatial perspective taking, with evidence to date demonstrating it is delineated across two levels, depending on how different that perspective is. Some strategies for visuospatial perspective taking have also been found to involve embodied cognition. However, the current generalisation of these findings is limited due to experimental setup and the use of computer monitors as the interface for experimental tasks. Augmented reality interfaces could possibly extend on the generalisation of these findings by situating virtual stimuli in the real environment, thus providing a higher degree of ecological validity and experimental standardisation. This study aimed to observe visuospatial perspective taking in augmented reality. This was achieved in participant experiments (N=24) using the Left-Right behavioural speeded decision task, which requires participants to discriminate between target objects relative to the perspective of an avatar. Angular disparity and posture congruence between the avatar and participant were manipulated between each trial to delineate between the two levels of visuospatial perspective taking and understand its potentially embodied nature. Although generalised linear mixed modeling indicated that angular disparity increased task difficulty, unexpectedly findings on posture congruence were less clear. Together, this suggests that visuospatial perspective taking in this study can be delineated across two levels. Further implications for embodied cognition and empathy research are discussed.

Mechanisms of Training-Related Change in Processing Speed: A Drift-Diffusion Model Approach.

Processing speed is a crucial ability that changes over the course of the lifespan. Training interventions on processing speed have shown promising effects and have been associated with improved cognitive functioning. While training-related changes in processing speed are often studied using reaction times (RTs) and error rates, these measures provide limited insight into the mechanisms underlying changes during training. The drift-diffusion model provides estimates of the cognitive processes underlying speeded decision tasks, such as the rate of evidence accumulation (drift rate), response strategies (boundary separation), as well as time for other processes such as stimulus encoding and motor response (non-decision time). In the current study, we analyzed existing data of an extensive multi-session training intervention (von Bastian & Oberauer, 2013) to disentangle changes in drift rate, boundary separation, and non-decision time during training of different speeded choice-RT tasks. During this training intervention, 30 participants performed 20 training sessions over the course of four weeks, completing three tasks each session: a face-matching, a pattern-matching, and a digit-matching task. Our results show that processing speed training increased drift rates throughout training. Boundary separation and non-decision time decreased mostly during the initial parts of training. This pattern of prolonged training-related changes in rate of evidence accumulation as well as early changes in response strategy and non-decision processes was observed across all three tasks. Future research should investigate how these training-related changes relate to improvements in cognitive functioning more broadly.

Hidden Markov Models of Evidence Accumulation in Speeded Decision Tasks

Speeded decision tasks are usually modeled within the evidence accumulation framework, enabling inferences on latent cognitive parameters, and capturing dependencies between the observed response times and accuracy. An example is the speed-accuracy trade-off, where people sacrifice speed for accuracy (or vice versa). Different views on this phenomenon lead to the idea that participants may not be able to control this trade-off on a continuum, but rather switch between distinct states (Dutilh et al., Cognitive Science 35(2):211–250, 2010). Hidden Markov models are used to account for switching between distinct states. However, combining evidence accumulation models with a hidden Markov structure is a challenging problem, as evidence accumulation models typically come with identification and computational issues that make them challenging on their own. Thus, an integration of hidden Markov models with evidence accumulation models has still remained elusive, even though such models would allow researchers to capture potential dependencies between response times and accuracy within the states, while concomitantly capturing different behavioral modes during cognitive processing. This article presents a model that uses an evidence accumulation model as part of a hidden Markov structure. This model is considered as a proof of principle that evidence accumulation models can be combined with Markov switching models. As such, the article considers a very simple case of a simplified Linear Ballistic Accumulation. An extensive simulation study was conducted to validate the model’s implementation according to principles of robust Bayesian workflow. Example reanalysis of data from Dutilh et al. (Cognitive Science 35(2):211–250, 2010) demonstrates the application of the new model. The article concludes with limitations and future extensions or alternatives to the model and its application.

Observed and Performed Error Signals in Auditory Lexical Decisions

This study investigates the error processing components in the EEG signal of Performers and Observers using an auditory lexical decision task, in which participants heard spoken items and decided for each item if it was a real word or not. Pairs of participants were tested in both the role of the Performer and the Observer. In the literature, an Error Related Negativity (ERN)-Error Positivity (Pe) complex has been identified for performed (ERN-Pe) and observed (oERN-oPe) errors. While these effects have been widely studied for performance errors in speeded decision tasks relying on visual input, relatively little is known about the performance monitoring signatures in observed language processing based on auditory input. In the lexical decision task, native Dutch speakers listened to real Dutch Words, Non-Words, and crucially, long Pseudowords that resembled words until the final syllable and were shown to be error-prone in a pilot study, because they were responded to too soon. We hypothesised that the errors in the task would result in a response locked ERN-Pe pattern both for the Performer and for the Observer. Our hypothesis regarding the ERN was not supported, however a Pe-like effect, as well as a P300 were present. Analyses to disentangle lexical and error processing similarly indicated a P300 for errors, and the results furthermore pointed to differences between responses before and after word offset. The findings are interpreted as marking attention during error processing during auditory word recognition.

Effects of Task Difficulty and Display Format on Automation Usage Strategy: A Workload Capacity Analysis.

Objective An experiment used workload capacity analysis to quantify automation usage strategy across different task difficulty and display format types in a speeded task. Background Workload capacity measures the efficiency of concurrent information processing and can serve as a gauge of automation usage strategy in speeded decision tasks. The present study used workload capacity analysis to investigate automation usage strategy while information display format and task difficulty were manipulated. Method Subjects performed a speeded judgment task assisted by an automated aid that issued decision cues at varying onset times. Response time distributions were converted to measures of workload capacity. Results Two variants of a workload capacity measure, CzOR and CzAND, gave evidence that operators moderated their own decision times both in anticipation of and following the arrival of the aid's diagnosis under difficult task conditions regardless of display format. Conclusion Assistance from an automated decision aid may cause operators to delay their own responses in a speeded decision task, producing joint response time distributions that are slower than optimal. Application Even when it renders its own judgments quickly and with high accuracy, an automated decision aid may slow responses from a user. Automation designers should consider the relative costs and benefits of response accuracy and time when choosing whether and how to implement an automated decision aid.

Workload Capacity: A Response Time-Based Measure of Automation Dependence.

An experiment used the workload capacity measure C(t) to quantify the processing efficiency of human-automation teams and identify operators' automation usage strategies in a speeded decision task. Although response accuracy rates and related measures are often used to measure the influence of an automated decision aid on human performance, aids can also influence response speed. Mean response times (RTs), however, conflate the influence of the human operator and the automated aid on team performance and may mask changes in the operator's performance strategy under aided conditions. The present study used a measure of parallel processing efficiency, or workload capacity, derived from empirical RT distributions as a novel gauge of human-automation performance and automation dependence in a speeded task. Participants performed a speeded probabilistic decision task with and without the assistance of an automated aid. RT distributions were used to calculate two variants of a workload capacity measure, COR(t) and CAND(t). Capacity measures gave evidence that a diagnosis from the automated aid speeded human participants' responses, and that participants did not moderate their own decision times in anticipation of diagnoses from the aid. Workload capacity provides a sensitive and informative measure of human-automation performance and operators' automation dependence in speeded tasks.

Disentangling decision models: From independence to competition.

A multitude of models have been proposed to account for the neural mechanism of value integration and decision making in speeded decision tasks. While most of these models account for existing data, they largely disagree on a fundamental characteristic of the choice mechanism: independent versus different types of competitive processing. Five models, an independent race model, 2 types of input competition models (normalized race and feed-forward inhibition [FFI]) and 2 types of response competition models (max-minus-next [MMN] diffusion and leaky competing accumulators [LCA]) were compared in 3 combined computational and experimental studies. In each study, difficulty was manipulated in a way that produced qualitatively distinct predictions from the different classes of models. When parameters were constrained by the experimental conditions to avoid mimicking, simulations demonstrated that independent models predict speedups in response time with increased difficulty, while response competition models predict the opposite. Predictions of input-competition models vary between specific models and experimental conditions. Taken together, the combined computational and empirical findings provide support for the notion that decisional processes are intrinsically competitive and that this competition is likely to kick in at a late (response), rather than early (input), processing stage.

Dissociable correlates of response conflict and error awareness in error-related brain activity

Errors in speeded decision tasks are associated with characteristic patterns of brain activity. In the scalp-recorded EEG, error processing is reflected in two components, the error-related negativity (ERN) and the error positivity (Pe). These components have been widely studied, but debate remains regarding the precise aspects of error processing they reflect. The present study investigated the relation between the ERN and the Pe using a novel version of the flanker task to allow a comparison between errors reflecting different causes—response conflict versus stimulus masking. The conflict and mask conditions were matched for overall behavioural performance but differed in underlying response dynamics, as indexed by response time distributions and measures of lateralised motor activity. ERN amplitude varied in relation to these differing response dynamics, being significantly larger in the conflict condition compared to the mask condition. Furthermore, differences in response dynamics between participants were predictive of modulations in ERN amplitude. In contrast, Pe activity varied little between conditions, but varied across trials in relation to participants’ awareness of their errors. Taken together, these findings suggest a dissociation between the ERN and the Pe, with the former reflecting the dynamics of response selection and conflict, and the latter reflecting conscious recognition of an error.

Dissociating Response Conflict and Error Likelihood in Anterior Cingulate Cortex

Neuroimaging studies consistently report activity in anterior cingulate cortex (ACC) in conditions of high cognitive demand, leading to the view that ACC plays a crucial role in the control of cognitive processes. According to one prominent theory, the sensitivity of ACC to task difficulty reflects its role in monitoring for the occurrence of competition, or "conflict," between responses to signal the need for increased cognitive control. However, a contrasting theory proposes that ACC is the recipient rather than source of monitoring signals, and that ACC activity observed in relation to task demand reflects the role of this region in learning about the likelihood of errors. Response conflict and error likelihood are typically confounded, making the theories difficult to distinguish empirically. The present research therefore used detailed computational simulations to derive contrasting predictions regarding ACC activity and error rate as a function of response speed. The simulations demonstrated a clear dissociation between conflict and error likelihood: fast response trials are associated with low conflict but high error likelihood, whereas slow response trials show the opposite pattern. Using the N2 component as an index of ACC activity, an EEG study demonstrated that when conflict and error likelihood are dissociated in this way, ACC activity tracks conflict and is negatively correlated with error likelihood. These findings support the conflict-monitoring theory and suggest that, in speeded decision tasks, ACC activity reflects current task demands rather than the retrospective coding of past performance.

Visual Word Activation in Pure Alexia

A patient with pure alexia (DM) is shown to perform rapid and accurate lexical decisions for common words without the ability to recover their complete identity. We provide evidence using a speeded decision task that DM is not forced to rely on a laborious analysis of individual letter forms when judging the lexical status of orthographic patterns varying in length, though he clearly must use this approach to fully identify a word for explicit report. By contrast, the ability to rapidly classify a word apparently does not extend to judgements of its superordinate category. DM makes semantic decisions for visual words by adopting the same inefficient procedure he uses for verbal report of their identity. The results provide further constraints on the functional deficit responsible for pure alexia. We argue that DM is able to monitor the overall activation of word units without achieving full identification and that such a process may be a characteristic of the normal reading mechanism.

Aging of attention: Does the ability to divide decline?

Previous research has yielded conflicting results regarding the relationship between adult age and the ability to divide attention between two concurrent tasks. At least some of the inconsistency is probably attributable to methodological variations, such as the manner in which divided-attention ability has been assessed, how single-task performance has been considered, and the degree of control over relative emphasis placed on each task. Two experiments employing procedures sensitive to these concerns were conducted in which a speeded decision task was performed during the retention interval of a letter-memory task. The results of both experiments indicated that there were relatively few age-related influences on dual-task performance vis-à-vis those on single-task performance.

Typographic influences on reading.

The research reported here comprises an empirical investigation of the phenomenon of typographic allusion. In a preliminary study, subjects rated the perceptual qualities possessed by different typefaces (e.g. heavy-light, fast-slow). The results indicated that subjects agreed as to typeface characteristics and that typefaces were distinguished by such qualities. In Expt 1, subjects undertook a speeded decision task in which they responded according to which one of four adjectives appeared tachistoscopically. Each word appeared in a typeface whose qualities were either consistent or inconsistent with its meaning. Reaction times for inconsistent stimuli were significantly slower than those for consistent trials. In preparation for Expt 2, the same rating procedure was used to elicit subjects' judgements of the attributes of different animals. Subjects agreed as to animals' qualities and such qualities reliably distinguished between the animals. The names of these animals were then used as targets in a binary decision task and each one appeared in a typeface possessing qualities which were either congruent or incongruent with those of the animal. Subjects responded according to whether they considered the animal presented on each trial to be heavy or light, or fast or slow moving. Responses on trials in which the animal and typeface possessed conflicting attributes were significantly slower than responses when animal and typeface qualities were congruent. These results are discussed in relation to current views regarding the processing of written English. We argue that typographic features of words are able to access a semantic code and that this code can interact with the derivation of a linguistic code specifying a word's meaning and/or with post-lexical access decision processes.