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Results: 1 to 10 of 58

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Accumulators, Neurons, and Response Time.
Schall JD
(2019) Trends Neurosci 42: 848-860
MeSH Terms: Animals, Brain, Decision Making, Humans, Mind-Body Relations, Metaphysical, Models, Neurological, Models, Psychological, Neurons, Psychophysiology, Reaction Time
Show Abstract · Added March 18, 2020
The marriage of cognitive neurophysiology and mathematical psychology to understand decision-making has been exceptionally productive. This interdisciplinary area is based on the proposition that particular neurons or circuits instantiate the accumulation of evidence specified by mathematical models of sequential sampling and stochastic accumulation. This linking proposition has earned widespread endorsement. Here, a brief survey of the history of the proposition precedes a review of multiple conundrums and paradoxes concerning the accuracy, precision, and transparency of that linking proposition. Correctly establishing how abstract models of decision-making are instantiated by particular neural circuits would represent a remarkable accomplishment in mapping mind to brain. Failing would reveal challenging limits for cognitive neuroscience. This is such a vigorous area of research because so much is at stake.
Copyright © 2019 Elsevier Ltd. All rights reserved.
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10 MeSH Terms
Disruption of Neural Homeostasis as a Model of Relapse and Recurrence in Late-Life Depression.
Andreescu C, Ajilore O, Aizenstein HJ, Albert K, Butters MA, Landman BA, Karim HT, Krafty R, Taylor WD
(2019) Am J Geriatr Psychiatry 27: 1316-1330
MeSH Terms: Aged, Allostasis, Autonomic Nervous System, Brain, Circadian Rhythm, Cognitive Dysfunction, Depressive Disorder, Major, Homeostasis, Humans, Hypothalamo-Hypophyseal System, Models, Neurological, Models, Psychological, Neural Pathways, Pituitary-Adrenal System, Recurrence, Stress, Psychological
Show Abstract · Added March 3, 2020
The significant public health burden associated with late-life depression (LLD) is magnified by the high rates of recurrence. In this manuscript, we review what is known about recurrence risk factors, conceptualize recurrence within a model of homeostatic disequilibrium, and discuss the potential significance and challenges of new research into LLD recurrence. The proposed model is anchored in the allostatic load theory of stress. We review the allostatic response characterized by neural changes in network function and connectivity and physiologic changes in the hypothalamic-pituitary-adrenal axis, autonomic nervous system, immune system, and circadian rhythm. We discuss the role of neural networks' instability following treatment response as a source of downstream disequilibrium, triggering and/or amplifying abnormal stress response, cognitive dysfunction and behavioral changes, ultimately precipitating a full-blown recurrent episode of depression. We propose strategies to identify and capture early change points that signal recurrence risk through mobile technology to collect ecologically measured symptoms, accompanied by automated algorithms that monitor for state shifts (persistent worsening) and variance shifts (increased variability) relative to a patient's baseline. Identifying such change points in relevant sensor data could potentially provide an automated tool that could alert clinicians to at-risk individuals or relevant symptom changes even in a large practice.
Published by Elsevier Inc.
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16 MeSH Terms
A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task.
Verbruggen F, Aron AR, Band GP, Beste C, Bissett PG, Brockett AT, Brown JW, Chamberlain SR, Chambers CD, Colonius H, Colzato LS, Corneil BD, Coxon JP, Dupuis A, Eagle DM, Garavan H, Greenhouse I, Heathcote A, Huster RJ, Jahfari S, Kenemans JL, Leunissen I, Li CR, Logan GD, Matzke D, Morein-Zamir S, Murthy A, Paré M, Poldrack RA, Ridderinkhof KR, Robbins TW, Roesch M, Rubia K, Schachar RJ, Schall JD, Stock AK, Swann NC, Thakkar KN, van der Molen MW, Vermeylen L, Vink M, Wessel JR, Whelan R, Zandbelt BB, Boehler CN
(2019) Elife 8:
MeSH Terms: Animals, Consensus, Decision Making, Executive Function, Humans, Impulsive Behavior, Inhibition, Psychological, Models, Animal, Models, Psychological, Neuropsychological Tests, Psychomotor Performance, Reaction Time
Show Abstract · Added March 18, 2020
Response inhibition is essential for navigating everyday life. Its derailment is considered integral to numerous neurological and psychiatric disorders, and more generally, to a wide range of behavioral and health problems. Response-inhibition efficiency furthermore correlates with treatment outcome in some of these conditions. The stop-signal task is an essential tool to determine how quickly response inhibition is implemented. Despite its apparent simplicity, there are many features (ranging from task design to data analysis) that vary across studies in ways that can easily compromise the validity of the obtained results. Our goal is to facilitate a more accurate use of the stop-signal task. To this end, we provide 12 easy-to-implement consensus recommendations and point out the problems that can arise when they are not followed. Furthermore, we provide user-friendly open-source resources intended to inform statistical-power considerations, facilitate the correct implementation of the task, and assist in proper data analysis.
© 2019, Verbruggen et al.
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MeSH Terms
The Effects of Pain Severity, Pain Catastrophizing, Depression, and Exercise on Perceived Disability in Acute Low Back Pain Patients.
Salt E, Wiggins AT, Hooker Q, Crofford L, Rayens MK, Segerstrom S
(2018) Res Theory Nurs Pract 32: 436-448
MeSH Terms: Adult, Catastrophization, Cross-Sectional Studies, Depressive Disorder, Disabled Persons, Exercise, Female, Humans, Low Back Pain, Male, Middle Aged, Models, Psychological, Pain Measurement, Severity of Illness Index, Surveys and Questionnaires, Young Adult
Show Abstract · Added March 25, 2020
The effectiveness of cognitive treatments for low back pain, a prevalent and costly condition, are commonly based on the principles of the Cognitive Behavioral Model of Fear of Movement/(Re)injury. In this model, persons with a painful injury/experience who also engage in pain catastrophizing are most likely to avoid activity leading to disability. The validation of this model in patients with acute low back is limited. The purpose of this project was to examine the relationship of perceived disability with variables identified in the Cognitive Behavioral Model of Fear of Movement/(Re)injury such as, pain severity, pain catastrophizing, depression, and exercise in persons with acute low back pain. A multiple linear regression model was used to assess the association of perceived disability with pain severity, pain catastrophizing, depression, and exercise at baseline among subjects with acute low back pain ( = 44) participating in a randomized clinical trial to prevent transition to chronic low back pain. Controlling for age, the overall model was significant for perceived disability ([5, 35] = 14.2; < .001). Higher scores of pain catastrophizing ( = .003) and pain severity ( < .001) were associated with higher perceived disability levels. Exercise and depression were not significantly associated with perceived disability. The use of the Cognitive Behavioral Model of Fear of Movement/(Re)injury in acute LBP patients is appropriate; because this model is commonly used as rationale for the effectiveness of cognitive treatments, these findings have clinical relevance in the treatment of this condition.
© 2018 Springer Publishing Company, LLC.
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MeSH Terms
Associations Among Early Life Stress, Rumination, Symptoms of Psychopathology, and Sex in Youth in the Early Stages of Puberty: a Moderated Mediation Analysis.
LeMoult J, Humphreys KL, King LS, Colich NL, Price AN, Ordaz SJ, Gotlib IH
(2019) J Abnorm Child Psychol 47: 199-207
MeSH Terms: Adolescent, Adverse Childhood Experiences, Behavioral Symptoms, Child, Female, Humans, Male, Models, Psychological, Rumination, Cognitive, Sex Factors, Stress, Psychological
Show Abstract · Added March 3, 2020
Despite the high prevalence and substantial costs of early life stress (ELS), the mechanisms through which ELS confers risk for psychopathology are poorly understood, particularly among youth who are in an earlier stage of the transition through puberty. We sought to advance our understanding of the link between ELS and psychopathology by testing whether rumination mediates the relation between ELS and symptoms of psychopathology in youth in the early stages of puberty, and whether sex moderates this mediation. We assessed levels of ELS, both brooding and reflection subtypes of rumination, and internalizing and externalizing symptoms in 170 youth in the early stages of puberty (56% girls) ages 9-13 years. Brooding, but not reflection, mediated the relation between ELS and both internalizing and externalizing symptoms. Importantly, however, sex moderated the relation among ELS, brooding, and symptoms. Specifically, brooding mediated the relation between ELS and both internalizing and externalizing symptoms for girls, but not for boys. Findings support the formulation that brooding is a mechanism linking ELS to multiple forms of behavioral and emotional problems exclusively in girls in the early stages of puberty.
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11 MeSH Terms
The Quality of Response Time Data Inference: A Blinded, Collaborative Assessment of the Validity of Cognitive Models.
Dutilh G, Annis J, Brown SD, Cassey P, Evans NJ, Grasman RPPP, Hawkins GE, Heathcote A, Holmes WR, Krypotos AM, Kupitz CN, Leite FP, Lerche V, Lin YS, Logan GD, Palmeri TJ, Starns JJ, Trueblood JS, van Maanen L, van Ravenzwaaij D, Vandekerckhove J, Visser I, Voss A, White CN, Wiecki TV, Rieskamp J, Donkin C
(2019) Psychon Bull Rev 26: 1051-1069
MeSH Terms: Adult, Cognition, Female, Humans, Male, Models, Psychological, Models, Statistical, Reaction Time, Reproducibility of Results, Single-Blind Method
Show Abstract · Added April 3, 2018
Most data analyses rely on models. To complement statistical models, psychologists have developed cognitive models, which translate observed variables into psychologically interesting constructs. Response time models, in particular, assume that response time and accuracy are the observed expression of latent variables including 1) ease of processing, 2) response caution, 3) response bias, and 4) non-decision time. Inferences about these psychological factors, hinge upon the validity of the models' parameters. Here, we use a blinded, collaborative approach to assess the validity of such model-based inferences. Seventeen teams of researchers analyzed the same 14 data sets. In each of these two-condition data sets, we manipulated properties of participants' behavior in a two-alternative forced choice task. The contributing teams were blind to the manipulations, and had to infer what aspect of behavior was changed using their method of choice. The contributors chose to employ a variety of models, estimation methods, and inference procedures. Our results show that, although conclusions were similar across different methods, these "modeler's degrees of freedom" did affect their inferences. Interestingly, many of the simpler approaches yielded as robust and accurate inferences as the more complex methods. We recommend that, in general, cognitive models become a typical analysis tool for response time data. In particular, we argue that the simpler models and procedures are sufficient for standard experimental designs. We finish by outlining situations in which more complicated models and methods may be necessary, and discuss potential pitfalls when interpreting the output from response time models.
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10 MeSH Terms
Bayesian statistical approaches to evaluating cognitive models.
Annis J, Palmeri TJ
(2018) Wiley Interdiscip Rev Cogn Sci 9:
MeSH Terms: Bayes Theorem, Cognition, Decision Making, Humans, Models, Psychological, Reaction Time
Show Abstract · Added April 3, 2018
Cognitive models aim to explain complex human behavior in terms of hypothesized mechanisms of the mind. These mechanisms can be formalized in terms of mathematical structures containing parameters that are theoretically meaningful. For example, in the case of perceptual decision making, model parameters might correspond to theoretical constructs like response bias, evidence quality, response caution, and the like. Formal cognitive models go beyond verbal models in that cognitive mechanisms are instantiated in terms of mathematics and they go beyond statistical models in that cognitive model parameters are psychologically interpretable. We explore three key elements used to formally evaluate cognitive models: parameter estimation, model prediction, and model selection. We compare and contrast traditional approaches with Bayesian statistical approaches to performing each of these three elements. Traditional approaches rely on an array of seemingly ad hoc techniques, whereas Bayesian statistical approaches rely on a single, principled, internally consistent system. We illustrate the Bayesian statistical approach to evaluating cognitive models using a running example of the Linear Ballistic Accumulator model of decision making (Brown SD, Heathcote A. The simplest complete model of choice response time: linear ballistic accumulation. Cogn Psychol 2008, 57:153-178). WIREs Cogn Sci 2018, 9:e1458. doi: 10.1002/wcs.1458 This article is categorized under: Neuroscience > Computation Psychology > Reasoning and Decision Making Psychology > Theory and Methods.
© 2017 Wiley Periodicals, Inc.
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6 MeSH Terms
Models of inhibitory control.
Schall JD, Palmeri TJ, Logan GD
(2017) Philos Trans R Soc Lond B Biol Sci 372:
MeSH Terms: Animals, Humans, Inhibition, Psychological, Models, Neurological, Models, Psychological, Reaction Time, Synaptic Transmission
Show Abstract · Added April 14, 2017
We survey models of response inhibition having different degrees of mathematical, computational and neurobiological specificity and generality. The independent race model accounts for performance of the stop-signal or countermanding task in terms of a race between GO and STOP processes with stochastic finishing times. This model affords insights into neurophysiological mechanisms that are reviewed by other authors in this volume. The formal link between the abstract GO and STOP processes and instantiating neural processes is articulated through interactive race models consisting of stochastic accumulator GO and STOP units. This class of model provides quantitative accounts of countermanding performance and replicates the dynamics of neural activity producing that performance. The interactive race can be instantiated in a network of biophysically plausible spiking excitatory and inhibitory units. Other models seek to account for interactions between units in frontal cortex, basal ganglia and superior colliculus. The strengths, weaknesses and relationships of the different models will be considered. We will conclude with a brief survey of alternative modelling approaches and a summary of problems to be addressed including accounting for differences across effectors, species, individuals, task conditions and clinical deficits.This article is part of the themed issue 'Movement suppression: brain mechanisms for stopping and stillness'.
© 2017 The Author(s).
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7 MeSH Terms
A hierarchical causal taxonomy of psychopathology across the life span.
Lahey BB, Krueger RF, Rathouz PJ, Waldman ID, Zald DH
(2017) Psychol Bull 143: 142-186
MeSH Terms: Age Factors, Causality, Classification, Genetic Predisposition to Disease, Humans, Mental Disorders, Models, Psychological, Multivariate Analysis, Sex Factors, Social Environment
Show Abstract · Added April 6, 2017
We propose a taxonomy of psychopathology based on patterns of shared causal influences identified in a review of multivariate behavior genetic studies that distinguish genetic and environmental influences that are either common to multiple dimensions of psychopathology or unique to each dimension. At the phenotypic level, first-order dimensions are defined by correlations among symptoms; correlations among first-order dimensions similarly define higher-order domains (e.g., internalizing or externalizing psychopathology). We hypothesize that the robust phenotypic correlations among first-order dimensions reflect a . Some nonspecific etiologic factors increase risk for all first-order dimensions of psychopathology to varying degrees through a general factor of psychopathology. Other nonspecific etiologic factors increase risk only for all first-order dimensions within a more specific higher-order domain. Furthermore, each first-order dimension has its own unique causal influences. Genetic and environmental influences common to family members tend to be nonspecific, whereas environmental influences unique to each individual are more dimension-specific. We posit that these causal influences on psychopathology are moderated by sex and developmental processes. This causal taxonomy also provides a novel framework for understanding the of each first-order dimension: Different persons exhibiting similar symptoms may be influenced by different combinations of etiologic influences from each of the 3 levels of the etiologic hierarchy. Furthermore, we relate the proposed causal taxonomy to transdimensional psychobiological processes, which also impact the heterogeneity of each psychopathology dimension. This causal taxonomy implies the need for changes in strategies for studying the etiology, psychobiology, prevention, and treatment of psychopathology. (PsycINFO Database Record
(c) 2017 APA, all rights reserved).
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10 MeSH Terms
Central attention is serial, but midlevel and peripheral attention are parallel-A hypothesis.
Tamber-Rosenau BJ, Marois R
(2016) Atten Percept Psychophys 78: 1874-88
MeSH Terms: Attention, Cognition, Humans, Memory, Short-Term, Models, Psychological, Perception, Prefrontal Cortex
Show Abstract · Added April 10, 2017
In this brief review, we argue that attention operates along a hierarchy from peripheral through central mechanisms. We further argue that these mechanisms are distinguished not just by their functional roles in cognition, but also by a distinction between serial mechanisms (associated with central attention) and parallel mechanisms (associated with midlevel and peripheral attention). In particular, we suggest that peripheral attentional deployments in distinct representational systems may be maintained simultaneously with little or no interference, but that the serial nature of central attention means that even tasks that largely rely on distinct representational systems will come into conflict when central attention is demanded. We go on to review both the behavioral and neural evidence for this prediction. We conclude that even though the existing evidence mostly favors our account of serial central and parallel noncentral attention, we know of no experiment that has conclusively borne out these claims. As such, this article offers a framework of attentional mechanisms that will aid in guiding future research on this topic.
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7 MeSH Terms