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.

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 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 Inflammation in mild cognitive impairment due to Parkinson's disease, Lewy body disease, and Alzheimer's disease

2019 ◽  
Vol 34 (8) ◽  
pp. 1244-1250 ◽  
Author(s):  
Eleanor King ◽  
John O'Brien ◽  
Paul Donaghy ◽  
Caroline H. Williams-Gray ◽  
Rachael A. Lawson ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Parkinson’S Disease ◽  
Alzheimer's Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Lewy Body ◽  
Lewy Body Disease

scholarly journals Symptoms associated with Lewy body disease in mild cognitive impairment

2017 ◽  
Vol 32 (11) ◽  
pp. 1163-1171 ◽  
Author(s):  
Paul C. Donaghy ◽  
Nicola Barnett ◽  
Kirsty Olsen ◽  
John-Paul Taylor ◽  
Ian G. McKeith ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Lewy Body ◽  
Lewy Body Disease

scholarly journals Bayesian confidence for drift diffusion observers in dynamic stimuli tasks

2020 ◽  
Author(s):  
Joshua Calder-Travis ◽  
Rafal Bogacz ◽  
Nick Yeung
Keyword(s):  
Diffusion Model ◽  
Drift Rate ◽  
Response Times ◽  
Time Dependent ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Dynamic Stimuli ◽  
Computationally Expensive ◽  
Insight Into ◽  
Confidence Data

AbstractMuch work has explored the possibility that the drift diffusion model, a model of response times and choices, could be extended to account for confidence reports. Many methods for making predictions from such models exist, although these methods either assume that stimuli are static over the course of a trial, or are computationally expensive, making it difficult to capitalise on trial-by-trial variability in dynamic stimuli. Using the framework of the drift diffusion model with time-dependent thresholds, and the idea of a Bayesian confidence readout, we derive expressions for the probability distribution over confidence reports. In line with current models of confidence, the derivations allow for the accumulation of “pipeline” evidence which has been received but not processed by the time of response, the effect of drift rate variability, and metacognitive noise. The expressions are valid for stimuli which change over the course of a trial with normally distributed fluctuations in the evidence they provide. A number of approximations are made to arrive at the final expressions, and we test all approximations via simulation. The derived expressions only contain a small number of standard functions, and only require evaluating once per trial, making trial-by-trial modelling of confidence data in dynamic stimuli tasks more feasible. We conclude by using the expressions to gain insight into the confidence of optimal observers, and empirically observed patterns.

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.

Mild cognitive impairment associated with eventual Lewy body disease pathology: Clinical characterization of 75 patients

2019 ◽  
Vol 405 ◽  
pp. 20
Author(s):  
B. Boeve ◽  
T. Ferman ◽  
N. Graff-Radford ◽  
D. Knopman ◽  
J. Graff-Radford ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Lewy Body ◽  
Lewy Body Disease

scholarly journals Mild cognitive impairment associated with limbic and neocortical lewy body disease: a clinicopathological study

Brain ◽  
2009 ◽  
Vol 133 (2) ◽  
pp. 540-556 ◽  
Author(s):  
Jennifer Molano ◽  
Bradley Boeve ◽  
Tanis Ferman ◽  
Glenn Smith ◽  
Joseph Parisi ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Lewy Body ◽  
Lewy Body Disease ◽  
Clinicopathological Study

scholarly journals At the Zebra Crossing: Modelling Complex Decision Processes with Variable-Drift Diffusion Models

2019 ◽  
Author(s):  
Oscar Terence Giles ◽  
Gustav Markkula ◽  
Jami Pekkanen ◽  
Naoki Yokota ◽  
Naoto Matsunaga ◽  
...  
Keyword(s):  
Diffusion Model ◽  
Drift Rate ◽  
Sensory Information ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Multimodal Distributions ◽  
Complex Models ◽  
Complex Decision ◽  
Pedestrian Crossing ◽  
Decision Tasks

Drift diffusion (or evidence accumulation) models have found widespread use in the modelling of simple decision tasks. Extensions of these models, in which the model’s instantaneous drift rate is not fixed but instead allowed to vary over time as a function of a stream of perceptual inputs, have allowed these models to account for more complex sensorimotor decision tasks. However, many real-world tasks seemingly rely on a myriad of even more complex underlying processes. One interesting example is the task of deciding whether to cross a road with an approaching vehicle. This action decision seemingly depends on sensory information both about own affordances (whether one can make it across before the vehicle) and action intention of others (whether the vehicle is yielding to oneself). Here, we compared three extensions of a standard drift diffusion model, with regards to their ability to capture timing of pedestrian crossing decisions in a virtual reality environment. We find that a single variable-drift diffusion model (S-VDDM) in which the varying drift rate is determined by visual quantities describing vehicle approach and deceleration, saturated at an upper and lower bound, can explain multimodal distributions of crossing times well across a broad range vehicle approach scenarios. More complex models, which attempt to partition the final crossing decision into constituent perceptual decisions, improve the fit to the human data but further work is needed before firm conclusions can be drawn from this finding.

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