Identifying Feigned Cognitive Impairment: Investigating the Utility of Diffusion Model Analyses

Assessment ◽  
2020 ◽  
pp. 107319112096231
Author(s):  
Elad Omer ◽  
Tomer Elbaum ◽  
Yoram Braw
Keyword(s):  
Cognitive Impairment ◽  
Diffusion Model ◽  
Cognitive Processes ◽  
Forced Choice ◽  
Model Parameters ◽  
Performance Validity ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Choice Performance ◽  
Feigned Cognitive Impairment

Forced-choice performance validity tests are routinely used for the detection of feigned cognitive impairment. The drift diffusion model deconstructs performance into distinct cognitive processes using accuracy and response time measures. It thereby offers a unique approach for gaining insight into examinees’ speed-accuracy trade-offs and the cognitive processes that underlie their performance. The current study is the first to perform such analyses using a well-established forced-choice performance validity test. To achieve this aim, archival data of healthy participants, either simulating cognitive impairment in the Word Memory Test or performing it to the best of their ability, were analyzed using the EZ-diffusion model ( N = 198). The groups differed in the three model parameters, with drift rate emerging as the best predictor of group membership. These findings provide initial evidence for the usefulness of the drift diffusion model in clarifying the cognitive processes underlying feigned cognitive impairment and encourage further research.

scholarly journals Visuo-Perceptual and Decision-Making Contributions to Visual Hallucinations in Mild Cognitive Impairment in Lewy Body Disease: Insights from a Drift Diffusion Analysis

2020 ◽  
Vol 10 (8) ◽  
pp. 540
Author(s):  
Lauren Revie ◽  
Calum A Hamilton ◽  
Joanna Ciafone ◽  
Paul C Donaghy ◽  
Alan Thomas ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Reaction Time ◽  
Diffusion Model ◽  
Lewy Body ◽  
Drift Rate ◽  
Lewy Body Disease ◽  
Visual Hallucinations ◽  
Drift Diffusion Model ◽  
Drift Diffusion

Background: Visual hallucinations (VH) are a common symptom in dementia with Lewy bodies (DLB); however, their cognitive underpinnings remain unclear. Hallucinations have been related to cognitive slowing in DLB and may arise due to impaired sensory input, dysregulation in top-down influences over perception, or an imbalance between the two, resulting in false visual inferences. Methods: Here we employed a drift diffusion model yielding estimates of perceptual encoding time, decision threshold, and drift rate of evidence accumulation to (i) investigate the nature of DLB-related slowing of responses and (ii) their relationship to visuospatial performance and visual hallucinations. The EZ drift diffusion model was fitted to mean reaction time (RT), accuracy and RT variance from two-choice reaction time (CRT) tasks and data were compared between groups of mild cognitive impairment (MCI-LB) LB patients (n = 49) and healthy older adults (n = 25). Results: No difference was detected in drift rate between patients and controls, but MCI-LB patients showed slower non-decision times and boundary separation values than control participants. Furthermore, non-decision time was negatively correlated with visuospatial performance in MCI-LB, and score on visual hallucinations inventory. However, only boundary separation was related to clinical incidence of visual hallucinations. Conclusions: These results suggest that a primary impairment in perceptual encoding may contribute to the visuospatial performance, however a more cautious response strategy may be related to visual hallucinations in Lewy body disease. Interestingly, MCI-LB patients showed no impairment in information processing ability, suggesting that, when perceptual encoding was successful, patients were able to normally process information, potentially explaining the variability of hallucination incidence.

scholarly journals The drift diffusion model as the choice rule in inter-temporal and risky choice: a case study in medial orbitofrontal cortex lesion patients and controls

2019 ◽  
Author(s):  
Jan Peters ◽  
Mark D’Esposito
Keyword(s):  
Decision Making ◽  
Diffusion Model ◽  
Choice Model ◽  
Sequential Sampling ◽  
Temporal Discounting ◽  
Risky Choice ◽  
Choice Rule ◽  
Model Parameters ◽  
Drift Diffusion Model ◽  
Drift Diffusion

AbstractSequential sampling models such as the drift diffusion model have a long tradition in research on perceptual decision-making, but mounting evidence suggests that these models can account for response time distributions that arise during reinforcement learning and value-based decision-making. Building on this previous work, we implemented the drift diffusion model as the choice rule in inter-temporal choice (temporal discounting) and risky choice (probability discounting) using a hierarchical Bayesian estimation scheme. We validated our approach in data from nine patients with focal lesions to the ventromedial prefrontal cortex / medial orbitofrontal cortex (vmPFC/mOFC) and nineteen age- and education-matched controls. Choice model parameters estimated via standard softmax action selection were reliably reproduced using the drift diffusion model as the choice rule, both for temporal discounting and risky choice. Model comparison revealed that, for both tasks, the data were best accounted for by a variant of the drift diffusion model including a non-linear mapping from value-differences to trial-wise drift rates. Posterior predictive checks of the winning models revealed a reasonably good fit to individual participants reaction time distributions. We then applied this modeling framework and 1) reproduced our previous results regarding temporal discounting in vmPFC/mOFC patients and 2) showed in a previously unpublished data set on risky choice that vmPFC/mOFC patients exhibit increased risk-taking relative to controls. Analyses of diffusion model parameters revealed that vmPFC/mOFC damage abolished neither value sensitivity nor asymptote of the drift rate. Rather, it substantially increased non-decision times and reduced response caution during risky choice. Our results highlight that novel insights can be gained from applying sequential sampling models in studies of inter-temporal and risky decision-making in cognitive neuroscience.

FEATURES OF THE CONFLICT ADAPTATION EFFECT IN MILD COGNITIVE DECLINE

2021 ◽  
pp. 996-1001
Author(s):  
Б. Б. Величковский ◽  
Д. В. Татаринов ◽  
А. А. Хлебникова ◽  
А. В. Зиберова ◽  
И. Ф. Рощина ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Diffusion Model ◽  
Cognitive Aging ◽  
Flanker Task ◽  
Adaptation Effect ◽  
Conflict Adaptation ◽  
Interference Control ◽  
Drift Diffusion Model ◽  
Drift Diffusion

Эффект адаптации к конфликту в задачах на подавление интерференции (таких как задача Струпа или фланговая задача) заключается в улучшении подавления иррелевантных стимулов после их подавления в предыдущей пробе. На материале фланговой задачи показывается, что когнитивное физиологическое старение сопровождается нулевым эффектом адаптации к конфликту, а мягкое когнитивное снижение - обратным (то есть отрицательным) эффектом адаптации к конфликту. Проведенный анализ времени реакции с помощью диффузионной модели ( drift diffusion model ) показал, что изменения в эффекте адаптации к конфликту у пациентов с мягким когнитивным снижением связаны с отсутствием у них адаптивного ускорения скорости переработки стимулов при наличии дистракторов. Этот результат может свидетельствовать о ригидности системы контроля перцептивных процессов, позволяющих осуществлять стратегическое перераспределение внимания в пожилом возрасте и при патологическом старении. Делается вывод о возможной роли обратного (отрицательного) эффекта адаптации к конфликту как раннего индикатора патологической когнитивной дисфункции. Conflict adaptation effect in interference control tasks (like Stroop task or flanker task) consists in better interference suppression in incongruent trials following an incongruent trial. In a flanker task is shown that in normal cognitive aging there is a null conflict adaptation effect and that in mild cognitive impairment there is a reversed (negative) conflict adaptation effect. Using the drift diffusion model of reaction time, it is shown that the change in conflict adaptation effect in mild cognitive impairment is associated with the absence of adaptive increase in processing speed in the presence of distractors. This can be interpreted as the rigidity of perceptual control mechanisms, which are responsible for strategic distribution of attention in older age and in pathological aging, in particular. The conclusion is drawn that reversed conflict adaptation effect may be an early marker of pathological cognitive aging.

scholarly journals Simultaneous Hierarchical Bayesian Parameter Estimation for Reinforcement Learning and Drift Diffusion Models: a Tutorial and Links to Neural Data

2020 ◽  
Vol 3 (4) ◽  
pp. 458-471 ◽  
Author(s):  
Mads L. Pedersen ◽  
Michael J. Frank
Keyword(s):  
Parameter Estimation ◽  
Reinforcement Learning ◽  
Diffusion Model ◽  
Simultaneous Estimation ◽  
Model Parameters ◽  
Hierarchical Bayesian ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Bayesian Parameter Estimation ◽  
The Impact

AbstractCognitive models have been instrumental for generating insights into the brain processes underlying learning and decision making. In reinforcement learning it has recently been shown that not only choice proportions but also their latency distributions can be well captured when the choice function is replaced with a sequential sampling model such as the drift diffusion model. Hierarchical Bayesian parameter estimation further enhances the identifiability of distinct learning and choice parameters. One caveat is that these models can be time-consuming to build, sample from, and validate, especially when models include links between neural activations and model parameters. Here we describe a novel extension to the widely used hierarchical drift diffusion model (HDDM) toolbox, which facilitates flexible construction, estimation, and evaluation of the reinforcement learning drift diffusion model (RLDDM) using hierarchical Bayesian methods. We describe the types of experiments most applicable to the model and provide a tutorial to illustrate how to perform quantitative data analysis and model evaluation. Parameter recovery confirmed that the method can reliably estimate parameters with varying numbers of synthetic subjects and trials. We also show that the simultaneous estimation of learning and choice parameters can improve the sensitivity to detect brain–behavioral relationships, including the impact of learned values and fronto-basal ganglia activity patterns on dynamic decision parameters.

scholarly journals Drift Diffusion Model of Animacy Categorization Task Can Detect Patients with Mild Cognitive Impairment and Mild Alzheimer's Disease

2021 ◽  
Author(s):  
Hamed Karimi ◽  
Haniye Marefat ◽  
Mahdiye Khanbagi ◽  
Alireza Karami ◽  
Zahra Vahabi
Keyword(s):  
Alzheimer’S Disease ◽  
Decision Making ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Diffusion Model ◽  
Computational Approach ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Categorization Task ◽  
Early Stages

Purpose: The process of neurodegeneration in Alzheimer's Disease (AD) is irreversible using current therapeutics. An earlier diagnosis of the disease can lead to earlier interventions, which will help patients sustain their cognitive abilities for longer. Individuals within the early stages of AD, shown to have trouble making confident and sounds decisions. Here we proposed a computational approach to quantify the decision-making ability in patients with mild cognitive impairment and mild AD. Materials and Methods: To study the quantified decision-making abilities at the early stages of the disease, we took advantage of a 2-Alternative Forced-Choice (2AFC) task. We applied the Drift Diffusion Model to determine whether the information accumulation process in a categorization task is altered in patients with mild cognitive impairment and mild AD. We implemented a classification model to detect cognitive impairment based on the Drift Diffusion Model's estimated parameters. Results: The results show a significant correlation of the classification score with the standard pen-and-paper tests, suggesting that the quantified decision-making parameters are undergoing significant change in patients with cognitive impairment. Conclusion: We confirmed that the decision-making ability deteriorates at the early stages of AD. We introduced a computational approach for measuring the decline in decision-making and used that measurement to distinguish patients from healthy individuals.

scholarly journals Gamification of Two Alternative Forced Choice: Validation based on Drift Diffusion Model and Individual Differences

2019 ◽  
Author(s):  
Esin Turkakin ◽  
Ceyla Karamancı ◽  
Kaan Karamancı ◽  
Fuat Balcı
Keyword(s):  
Individual Differences ◽  
Diffusion Model ◽  
Response Times ◽  
Forced Choice ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Obsessive Compulsive ◽  
Constant Variance ◽  
Decision Making Processes ◽  
Evidence Integration

Two alternative forced choice (2AFC) paradigms, coupled with the unified analysis of accuracy and response times within specific decision theoretic frameworks, have provided a wealth of information regarding decision-making processes. One problem of associated experimental tasks is that they are typically not engaging and do not contain stimuli or task representations familiar to participants, resulting in contaminants in the data due to boredom and distraction. Furthermore, when investigating decision strategies, use of noisy stimulus attributes result in undesired variance in the perceptual process complicating the analysis and interpretation of results. To address these fundamental issues, we developed a 2AFC soccer game in which participants’ task is to score goals by making leftward or rightward shots after observing the trajectory of the goalkeeper within a trial. The goalkeeper’s location is repeatedly sampled from a normal distribution with a constant variance and a mean either to the left or right of the midpoint. We tested participants on three difficulty levels parameterized by the distance between the two means and expected the rate of evidence integration to decrease with increasing difficulty and after errors as characteristic of standard 2AFC tasks. Drift- diffusion model provided good fits to data, and their outputs confirmed our predictions outlined above. Furthermore, we found the evidence integration rates to be negatively correlated with individual differences in maladaptive perfectionism, but not in anxiety or obsessive-compulsive traits.

scholarly journals Lexical-semantic and executive deficits revealed by computational modelling: a drift diffusion model perspective

2019 ◽  
Author(s):  
Lara Todorova ◽  
David Neville ◽  
Vitória Piai
Keyword(s):  
Semantic Memory ◽  
Diffusion Model ◽  
Drift Rate ◽  
Related Word ◽  
Model Parameters ◽  
Decision Threshold ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Lexical Semantic ◽  
Two Systems

Flexible language use requires coordinated functioning of two systems: conceptual representations and control. The interaction between two systems can be observed when people are asked to match a word to a picture. Participants are slower and less accurate for related word-picture pairs (word: banana, picture: apple) relative to unrelated pairs (word: banjo, picture: apple). The mechanism underlying interference however is still unclear. We analyzed word-picture verification (WPM) performance of patients with stroke-induced lesions to the left-temporal (N = 5) or left-frontal cortex (N = 5) and matched controls (N = 12) using the drift diffusion model (DDM). In DDM the process of making a decision is described as the stochastic accumulation of evidence towards a response. The parameters of the DDM model that characterize this process are decision threshold, drift rate, starting point and non-decision time. Each of them bears cognitive interpretability and we compared the estimated model parameters from controls and patients to investigate the mechanisms of WPM interference. WPM performance in controls was explained by the amount of information needed to make a decision (decision threshold): a higher threshold was associated with related word-picture pairs relative to unrelated ones. No difference was found in the quality of the evidence (drift rate). This suggests an executive rather than semantic mechanism underlying WPM interference. Both patients with temporal and frontal lesions exhibited both increased drift rate and decision threshold for unrelated pairs relative to related ones. Left-frontal and temporal damage affected the computations required by WPM similarly, resulting in systematic deficits across lexical-semantic memory and executive functions. These results support a diverse but interactive role of lexical-semantic memory and semantic control mechanisms.

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