Analyzing Stochastic Dependence of Cognitive Processes in Multidimensional Source Recognition

2014 ◽  
Vol 61 (5) ◽  
pp. 402-415 ◽  
Author(s):  
Thorsten Meiser
Keyword(s):  
Cognitive Processes ◽  
Model Complexity ◽  
Multinomial Model ◽  
Stochastic Dependence ◽  
New Model ◽  
Multinomial Processing Tree ◽  
Cognitive States ◽  
The Family ◽  
Tree Models ◽  
Flexible Framework

Stochastic dependence among cognitive processes can be modeled in different ways, and the family of multinomial processing tree models provides a flexible framework for analyzing stochastic dependence among discrete cognitive states. This article presents a multinomial model of multidimensional source recognition that specifies stochastic dependence by a parameter for the joint retrieval of multiple source attributes together with parameters for stochastically independent retrieval. The new model is equivalent to a previous multinomial model of multidimensional source memory for a subset of the parameter space. An empirical application illustrates the advantages of the new multinomial model of joint source recognition. The new model allows for a direct comparison of joint source retrieval across conditions, it avoids statistical problems due to inflated confidence intervals and does not imply a conceptual imbalance between source dimensions. Model selection criteria that take model complexity into account corroborate the new model of joint source recognition.

A Hierarchy of Multinomial Models for Multidimensional Source Monitoring

Methodology ◽  
2005 ◽  
Vol 1 (1) ◽  
pp. 2-17 ◽  
Author(s):  
Thorsten Meiser
Keyword(s):  
Cognitive Processes ◽  
Source Monitoring ◽  
Source Information ◽  
Model Comparisons ◽  
Storage And Retrieval ◽  
Multinomial Processing Tree ◽  
Multinomial Models ◽  
Hierarchical Relationship ◽  
Statistical Framework ◽  
Tree Models

Abstract. Several models have been proposed for the measurement of cognitive processes in source monitoring. They are specified within the statistical framework of multinomial processing tree models and differ in their assumptions on the storage and retrieval of multidimensional source information. In the present article, a hierarchical relationship is demonstrated between multinomial models for crossed source information ( Meiser & Bröder, 2002 ), for partial source memory ( Dodson, Holland, & Shimamura, 1998 ) and for several sources ( Batchelder, Hu, & Riefer, 1994 ). The hierarchical relationship allows model comparisons and facilitates the specification of identifiability conditions. Conditions for global identifiability are discussed, and model comparisons are illustrated by reanalyses and by a new experiment on the storage and retrieval of multidimensional source information.

Multinomial Processing Tree Models

2009 ◽  
Vol 217 (3) ◽  
pp. 108-124 ◽  
Author(s):  
Edgar Erdfelder ◽  
Tina-Sarah Auer ◽  
Benjamin E. Hilbig ◽  
André Aßfalg ◽  
Morten Moshagen ◽  
...  
Keyword(s):  
Cognitive Psychology ◽  
Cognitive Processes ◽  
Linear Models ◽  
General Purpose ◽  
Analysis Techniques ◽  
Multinomial Processing Tree ◽  
The Past ◽  
Tree Models ◽  
Recent Trends ◽  
Log Linear

Multinomial processing tree (MPT) models have become popular in cognitive psychology in the past two decades. In contrast to general-purpose data analysis techniques, such as log-linear models or other generalized linear models, MPT models are substantively motivated stochastic models for categorical data. They are best described as tools (a) for measuring the cognitive processes that underlie human behavior in various tasks and (b) for testing the psychological assumptions on which these models are based. The present article provides a review of MPT models and their applications in psychology, focusing on recent trends and developments in the past 10 years. Our review is nontechnical in nature and primarily aims at informing readers about the scope and utility of MPT models in different branches of cognitive psychology.

scholarly journals CPT to RVU conversion improves model performance in the prediction of surgical case length

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nicholas Garside ◽  
Hamed Zaribafzadeh ◽  
Ricardo Henao ◽  
Royce Chung ◽  
Daniel Buckland
Keyword(s):  
Model Performance ◽  
Individual Case ◽  
Model Complexity ◽  
Actual Case ◽  
Surgical Case ◽  
Relative Value ◽  
Prediction Time ◽  
Boosted Decision Tree ◽  
Tree Models ◽  
Duke University

AbstractMethods used to predict surgical case time often rely upon the current procedural terminology (CPT) code as a nominal variable to train machine-learned models, however this limits the ability of the model to incorporate new procedures and adds complexity as the number of unique procedures increases. The relative value unit (RVU, a consensus-derived billing indicator) can serve as a proxy for procedure workload and could replace the CPT code as a primary feature for models that predict surgical case length. Using 11,696 surgical cases from Duke University Health System electronic health records data, we compared boosted decision tree models that predict individual case length, changing the method by which the model coded procedure type; CPT, RVU, and CPT–RVU combined. Performance of each model was assessed by inference time, MAE, and RMSE compared to the actual case length on a test set. Models were compared to each other and to the manual scheduler method that currently exists. RMSE for the RVU model (60.8 min) was similar to the CPT model (61.9 min), both of which were lower than scheduler (90.2 min). 65.2% of our RVU model’s predictions (compared to 43.2% from the current human scheduler method) fell within 20% of actual case time. Using RVUs reduced model prediction time by ninefold and reduced the number of training features from 485 to 44. Replacing pre-operative CPT codes with RVUs maintains model performance while decreasing overall model complexity in the prediction of surgical case length.

scholarly journals Mind wandering and attention during focused meditation: A fine-grained temporal analysis of fluctuating cognitive states

2017 ◽  
Author(s):  
Wendy Hasenkamp ◽  
Christine Wilson-Mendenhall ◽  
Erica Duncan ◽  
Lawrence Barsalou
Keyword(s):  
Cognitive Processes ◽  
Sustained Attention ◽  
Temporal Analysis ◽  
Mind Wandering ◽  
Brain Regions ◽  
Attentional Processing ◽  
Default Mode ◽  
Cognitive Correlates ◽  
Cognitive States ◽  
Task Positive Network

Studies have suggested that the default mode network is active during mind wandering, which is often experienced intermittently during sustained attention tasks. Conversely, an anticorrelated task-positive network is thought to subserve various forms of attentional processing. Understanding how these two systems work together is central for understanding many forms of optimal and sub-optimal task performance. Here we present a basic model of naturalistic cognitive fluctuations between mind wandering and attentional states derived from the practice of focused attention meditation. This model proposes four intervals in a cognitive cycle: mind wandering, awareness of mind wandering, shifting of attention, and sustained attention. People who train in this style of meditation cultivate their abilities to monitor cognitive processes related to attention and distraction, making them well suited to report on these mental events. Fourteen meditation practitioners performed breath-focused meditation while undergoing fMRI scanning. When participants realized their mind had wandered, they pressed a button and returned their focus to the breath. The four intervals above were then constructed around these button presses. We hypothesized that periods of mind wandering would be associated with default mode activity, whereas cognitive processes engaged during awareness of mind wandering, shifting of attention and sustained attention would engage attentional subnetworks. Analyses revealed activity in brain regions associated with the default mode during mind wandering, and in salience network regions during awareness of mind wandering. Elements of the executive network were active during shifting and sustained attention. Furthermore, activations during these cognitive phases were modulated by lifetime meditation experience. These findings support and extend theories about cognitive correlates of distributed brain networks.

Cognitive psychometrics: Assessing storage and retrieval deficits in special populations with multinomial processing tree models.

2002 ◽  
Vol 14 (2) ◽  
pp. 184-201 ◽  
Author(s):  
David M. Riefer ◽  
Bethany R. Knapp ◽  
William H. Batchelder ◽  
Donald Bamber ◽  
Victor Manifold
Keyword(s):  
Special Populations ◽  
Multinomial Processing Tree Models ◽  
Storage And Retrieval ◽  
Multinomial Processing Tree ◽  
Tree Models

The Perraults and Versailles

The Perraults ◽  
2018 ◽  
pp. 103-119
Author(s):  
Oded Rabinovitch
Keyword(s):  
Cultural Politics ◽  
Social World ◽  
New Model ◽  
Exotic Animals ◽  
The Social ◽  
The Family ◽  
Academy Of Sciences

Charles’s position in Colbert’s orbit offered the family new ways to act in the social world. This chapter concentrates on the ways the Perraults drew upon their access to Versailles in a variety of contexts, from the dissections of exotic animals in the Academy of Sciences to their literary sociability, as it served as a library of sorts. By tracing how Versailles became an object in the Perraults’ extended network, this chapter suggests a new model for understanding cultural patronage and Versailles’ role in the cultural politics of Louis XIV’s France. Not simply a radiant palace that stunned visitors by its splendor, the court’s reputation grew through appropriations by men of letters, which benefited the Perraults in their Parisian endeavors while they promoted the king’s glory.

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