scholarly journals The Discovery and Interpretation of Evidence Accumulation Stages

2021 ◽  
Author(s):  
Leendert van Maanen ◽  
Oscar Portoles ◽  
Jelmer P. Borst
Keyword(s):  
Cognitive Processing ◽  
Recognition Task ◽  
Associative Recognition ◽  
Parameter Estimates ◽  
Evidence Accumulation ◽  
Target Foil ◽  
Eeg Data ◽  
Dot Motion ◽  
Discovery Method ◽  
Speed Accuracy

AbstractTo improve the understanding of cognitive processing stages, we combined two prominent traditions in cognitive science: evidence accumulation models and stage discovery methods. While evidence accumulation models have been applied to a wide variety of tasks, they are limited to tasks in which decision-making effects can be attributed to a single processing stage. Here, we propose a new method that first uses machine learning to discover processing stages in EEG data and then applies evidence accumulation models to characterize the duration effects in the identified stages. To evaluate this method, we applied it to a previously published associative recognition task (Application 1) and a previously published random dot motion task with a speed-accuracy trade-off manipulation (Application 2). In both applications, the evidence accumulation models accounted better for the data when we first applied the stage-discovery method, and the resulting parameter estimates where generally in line with psychological theories. In addition, in Application 1 the results shed new light on target-foil effects in associative recognition, while in Application 2 the stage discovery method identified an additional stage in the accuracy-focused condition — challenging standard evidence accumulation accounts. We conclude that the new framework provides a powerful new tool to investigate processing stages.

scholarly journals Stages of Processing in Associative Recognition: Evidence from Behavior, EEG, and Classification

2013 ◽  
Vol 25 (12) ◽  
pp. 2151-2166 ◽  
Author(s):  
Jelmer P. Borst ◽  
Darryl W. Schneider ◽  
Matthew M. Walsh ◽  
John R. Anderson
Keyword(s):  
Memory Retrieval ◽  
Word Length ◽  
Cognitive Architecture ◽  
Recognition Task ◽  
Associative Recognition ◽  
Machine Learning Techniques ◽  
Probe Type ◽  
Learning Techniques ◽  
Eeg Data

In this study, we investigated the stages of information processing in associative recognition. We recorded EEG data while participants performed an associative recognition task that involved manipulations of word length, associative fan, and probe type, which were hypothesized to affect the perceptual encoding, retrieval, and decision stages of the recognition task, respectively. Analyses of the behavioral and EEG data, supplemented with classification of the EEG data using machine-learning techniques, provided evidence that generally supported the sequence of stages assumed by a computational model developed in the Adaptive Control of Thought-Rational cognitive architecture. However, the results suggested a more complex relationship between memory retrieval and decision-making than assumed by the model. Implications of the results for modeling associative recognition are discussed. The study illustrates how a classifier approach, in combination with focused manipulations, can be used to investigate the timing of processing stages.

scholarly journals An evidence accumulation model of perceptual discrimination with naturalistic stimuli

2018 ◽  
Author(s):  
Hector Palada ◽  
Rachel A Searston ◽  
Annabel Persson ◽  
Timothy Ballard ◽  
Matthew B Thompson
Keyword(s):  
Decision Making ◽  
Cognitive Processes ◽  
Decision Process ◽  
Dynamic Decision Making ◽  
Evidence Accumulation ◽  
Natural Stimuli ◽  
Perceptual Judgments ◽  
Linear Ballistic Accumulator ◽  
Decision Making Model ◽  
Speed Accuracy

Evidence accumulation models have been used to describe the cognitive processes underlying performance in tasks involving two-choice decisions about unidimensional stimuli, such as motion or orientation. Given the multidimensionality of natural stimuli, however, we might expect qualitatively different patterns of evidence accumulation in more applied perceptual tasks. One domain that relies heavily on human decisions about complex natural stimuli is fingerprint discrimination. We know little about the ability of evidence accumulation models to account for the dynamic decision process of a fingerprint examiner resolving if two different prints belong to the same finger or not. Here, we apply a dynamic decision-making model — the linear ballistic accumulator (LBA) — to fingerprint discrimination decisions in order to gain insight into the cognitive processes underlying these complex perceptual judgments. Across three experiments, we show that the LBA provides an accurate description of the fingerprint discrimination decision process with manipulations in visual noise, speed-accuracy emphasis, and training. Our results demonstrate that the LBA is a promising model for furthering our understanding of applied decision-making with naturally varying visual stimuli.

scholarly journals Effects of fixed- and varied-context repetition on associative recognition in amnesia

2010 ◽  
Vol 16 (4) ◽  
pp. 596-602 ◽  
Author(s):  
DANIEL L. GREENBERG ◽  
MIEKE VERFAELLIE
Keyword(s):  
False Alarm ◽  
Recognition Task ◽  
Associative Recognition ◽  
False Alarms ◽  
Study Phase ◽  
Repetition Condition ◽  
Context Condition ◽  
False Alarm Rates

AbstractThis study compared the effects of fixed- and varied-context repetition on associative recognition in amnesia. Controls and amnesic participants were presented with a set of three-word phrases. Each was presented three times. In the varied-context condition, the verb changed with each presentation; in the fixed-context condition, it remained constant. At test, participants performed an associative-recognition task in which they were shown pairs of words from the study phase and asked to distinguish between intact and recombined pairs. For corrected recognition (hits – false alarms), controls performed better in the varied-context than in the fixed-context repetition condition, whereas amnesic participants’ performance did not differ between conditions. Similarly, controls had lower false-alarm rates in the varied-context condition, but there was no significant effect of condition for the amnesic participants. Thus, varied-context repetition does not improve amnesic participants’ performance on a recollection-dependent associative-recognition task, possibly because the amnesic participants were unable to take advantage of the additional cues that the varied-context encoding condition provided. (JINS, 2010, 16, 596–602.)

scholarly journals The influence of evidence volatility on choice, reaction time and confidence in a perceptual decision

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Ariel Zylberberg ◽  
Christopher R Fetsch ◽  
Michael N Shadlen
Keyword(s):  
Visual Cortex ◽  
Reaction Time ◽  
Choice Reaction Time ◽  
Signal To Noise Ratio ◽  
Stimulus Strength ◽  
Signal To Noise ◽  
Perceptual Decision ◽  
Evidence Accumulation ◽  
Decision Speed ◽  
Speed Accuracy

Many decisions are thought to arise via the accumulation of noisy evidence to a threshold or bound. In perception, the mechanism explains the effect of stimulus strength, characterized by signal-to-noise ratio, on decision speed, accuracy and confidence. It also makes intriguing predictions about the noise itself. An increase in noise should lead to faster decisions, reduced accuracy and, paradoxically, higher confidence. To test these predictions, we introduce a novel sensory manipulation that mimics the addition of unbiased noise to motion-selective regions of visual cortex, which we verified with neuronal recordings from macaque areas MT/MST. For both humans and monkeys, increasing the noise induced faster decisions and greater confidence over a range of stimuli for which accuracy was minimally impaired. The magnitude of the effects was in agreement with predictions of a bounded evidence accumulation model.

scholarly journals The time-course of distractor-based activation modulates effects of speed-accuracy tradeoffs in conflict tasks

2021 ◽  
Author(s):  
Victor Mittelstädt ◽  
Jeff Miller ◽  
Hartmut Leuthold ◽  
Ian Grant Mackenzie ◽  
Rolf Ulrich
Keyword(s):  
Decision Making ◽  
Congruency Effect ◽  
Time Course ◽  
Time Pressure ◽  
Evidence Accumulation ◽  
Conflicting Information ◽  
The Mean ◽  
Time Courses ◽  
Decision Boundaries ◽  
Speed Accuracy

AbstractThe cognitive processes underlying the ability of human performers to trade speed for accuracy is often conceptualized within evidence accumulation models, but it is not yet clear whether and how these models can account for decision-making in the presence of various sources of conflicting information. In the present study, we provide evidence that speed-accuracy tradeoffs (SATs) can have opposing effects on performance across two different conflict tasks. Specifically, in a single preregistered experiment, the mean reaction time (RT) congruency effect in the Simon task increased, whereas the mean RT congruency effect in the Eriksen task decreased, when the focus was put on response speed versus accuracy. Critically, distributional RT analyses revealed distinct delta plot patterns across tasks, thus indicating that the unfolding of distractor-based response activation in time is sufficient to explain the opposing pattern of congruency effects. In addition, a recent evidence accumulation model with the notion of time-varying conflicting information was successfully fitted to the experimental data. These fits revealed task-specific time-courses of distractor-based activation and suggested that time pressure substantially decreases decision boundaries in addition to reducing the duration of non-decision processes and the rate of evidence accumulation. Overall, the present results suggest that time pressure can have multiple effects in decision-making under conflict, but that strategic adjustments of decision boundaries in conjunction with different time-courses of distractor-based activation can produce counteracting effects on task performance with different types of distracting sources of information.

scholarly journals Assessing model-based inferences in decision making with single-trial response time decomposition

2020 ◽  
Author(s):  
Gabriel Weindel ◽  
Royce anders ◽  
F.-Xavier Alario ◽  
Boris BURLE
Keyword(s):  
Decision Making ◽  
Decision Processes ◽  
Emg Activity ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Response Force ◽  
Model Based ◽  
Wide Range ◽  
Response Execution ◽  
Speed Accuracy

Decision-making models based on evidence accumulation processes (the most prolific one being the drift-diffusion model – DDM) are widely used to draw inferences about latent psychological processes from chronometric data. While the observed goodness of fit in a wide range of tasks supports the model’s validity, the derived interpretations have yet to be sufficiently cross-validated with other measures that also reflect cognitive processing. To do so, we recorded electromyographic (EMG) activity along with response times (RT), and used it to decompose every RT into two components: a pre-motor (PMT) and motor time (MT). These measures were mapped to the DDM's parameters, thus allowing a test, beyond quality of fit, of the validity of the model’s assumptions and their usual interpretation. In two perceptual decision tasks, performed within a canonical task setting, we manipulated stimulus contrast, speed-accuracy trade-off, and response force, and assessed their effects on PMT, MT, and RT. Contrary to common assumptions, these three factors consistently affected MT. DDM parameter estimates of non-decision processes are thought to include motor execution processes, and they were globally linked to the recorded response execution MT. However, when the assumption of independence between decision and non-decision processes was not met, in the fastest trials, the link was weaker. Overall, the results show a fair concordance between model-based and EMG-based decompositions of RTs, but also establish some limits on the interpretability of decision model parameters linked to response execution.

scholarly journals Hidden Markov Models of Evidence Accumulation in Speeded Decision Tasks

2020 ◽  
Author(s):  
Šimon Kucharský ◽  
N.-Han Tran ◽  
Karel Veldkamp ◽  
Maartje Eusebia Josefa Raijmakers ◽  
Ingmar Visser
Keyword(s):  
Hidden Markov Models ◽  
Markov Models ◽  
Response Times ◽  
Hidden Markov ◽  
Trade Off ◽  
Evidence Accumulation ◽  
Markov Switching Models ◽  
Markov Structure ◽  
Speed Accuracy ◽  
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., 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, hidden Markov models have not used the evidence accumulation framework, giving up on the inference on the latent cognitive parameters, or capturing potential dependencies between response times and accuracy within the states.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. (2010) demonstrates the application of the new model. The article concludes with limitations and future extensions or alternatives to the model and its application.

scholarly journals Emotional Infant Face Processing in Women With Major Depression and Expecting Parents With Depressive Symptoms

2021 ◽  
Vol 12 ◽  
Author(s):  
Agnes Bohne ◽  
Dag Nordahl ◽  
Åsne A. W. Lindahl ◽  
Pål Ulvenes ◽  
Catharina E. A. Wang ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Major Depression ◽  
Attentional Bias ◽  
Interpersonal Relationships ◽  
Facial Expressions ◽  
Cognitive Processing ◽  
Recognition Task ◽  
Emotional Facial Expressions ◽  
Facial Memory ◽  
Infant Faces

Processing of emotional facial expressions is of great importance in interpersonal relationships. Aberrant engagement with facial expressions, particularly an engagement with sad faces, loss of engagement with happy faces, and enhanced memory of sadness has been found in depression. Since most studies used adult faces, we here examined if such biases also occur in processing of infant faces in those with depression or depressive symptoms. In study 1, we recruited 25 inpatient women with major depression and 25 matched controls. In study 2, we extracted a sample of expecting parents from the NorBaby study, where 29 reported elevated levels of depressive symptoms, and 29 were matched controls. In both studies, we assessed attentional bias with a dot-probe task using happy, sad and neutral infant faces, and facial memory bias with a recognition task using happy, sad, angry, afraid, surprised, disgusted and neutral infant and adult faces. Participants also completed the Ruminative Responses Scale and Becks Depression Inventory-II. In study 1, we found no group difference in either attention to or memory accuracy for emotional infant faces. Neither attention nor recognition was associated with rumination. In study 2, we found that the group with depressive symptoms disengaged more slowly than healthy controls from sad infant faces, and this was related to rumination. The results place emphasis on the importance of emotional self-relevant material when examining cognitive processing in depression. Together, these studies demonstrate that a mood-congruent attentional bias to infant faces is present in expecting parents with depressive symptoms, but not in inpatients with Major Depression Disorder who do not have younger children.

Sign in / Sign up

Export Citation Format

Share Document