Dataset Information

Investigation of Biases and Compensatory Strategies Using a Probabilistic Variant of the Wisconsin Card Sorting Test.

ABSTRACT: The Wisconsin Card Sorting Test (WCST) evaluates a subject's ability to shift to a new pattern of behavior in response to the presentation of unexpected negative feedback. The present study introduces a novel version of the traditional WCST by integrating a probabilistic component into its traditional rule shifting to add uncertainty to the task, as well as the option to forage for information during any particular trial. These changes transformed a task that is trivial for neurotypical individuals into a challenging environment useful for evaluating biases and compensatory strategizing. Sixty subjects performed the probabilistic WCST at four uncertainty levels to determine the effect of uncertainty on subject performance and strategy. Results revealed that increasing the level of uncertainty during a run of trials correlated with a reduction in rational strategizing in favor of both random choice and information foraging, evoking biases and suboptimal strategies such as satisfaction of search, negativity bias, and probability matching.

SUBMITTER: Craig AB

PROVIDER: S-EPMC4722127 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Investigation of Biases and Compensatory Strategies Using a Probabilistic Variant of the Wisconsin Card Sorting Test.

Craig Alexis B AB Phillips Matthew E ME Zaldivar Andrew A Bhattacharyya Rajan R Krichmar Jeffrey L JL

Frontiers in psychology 20160122

The Wisconsin Card Sorting Test (WCST) evaluates a subject's ability to shift to a new pattern of behavior in response to the presentation of unexpected negative feedback. The present study introduces a novel version of the traditional WCST by integrating a probabilistic component into its traditional rule shifting to add uncertainty to the task, as well as the option to forage for information during any particular trial. These changes transformed a task that is trivial for neurotypical individu ...[more]

PMID: 26834686

Similar Datasets

Project description:Cognitive flexibility is a critical component of executive function and is strongly influenced by genetic factors. We conducted a genome-wide association study of cognitive flexibility (as measured by perseverative errors on the Wisconsin Card Sorting Test) in two sets of African American (AA) and European American (EA) subjects (Yale-Penn-1: 1,411 AAs/949 EAs; Yale-Penn-2: 1,178 AAs/1,335 EAs). We examined the association of cognitive flexibility with genotyped or imputed SNPs across the genome. In AAs, two correlated common single nucleotide polymorphisms (SNPs) (rs7165213/rs35633795) in the downstream region of the noncoding gene LOC101927286 on chromosome 15 showed genome-wide significant (GWS) associations with cognitive flexibility (Yale-Penn-1: p = 6.0 × 10-9 /1.3 × 10-8 ; Yale-Penn-2: p = .029/.010; meta-analysis: p = 4.2 × 10-7 /1.0 × 10-7 ) in the same effect direction. In EAs, no GWS associations were observed. Enriched gene sets identified by Data-driven Expression-Prioritized Integration for Complex Traits (DEPICT) analysis of the top SNPs (pmeta-analysis < 10-5 ) included the signalosome and ubiquitin-specific peptidase 9, X-linked (USP9X) subnetwork in AAs, and abnormal frontal and occipital bone morphology in EAs. We also performed polygenic risk score (PRS) analysis to examine the genetic correlation of cognition-proxy phenotypes (general cognitive function, education attainment, childhood intelligence, and infant head circumference) and cognitive flexibility in EAs. The PRS derived from general cognitive function-associated SNPs was significantly associated with cognitive flexibility. Nongenetic factors (age, education, sex, and tobacco recency) also exerted significant effects on cognitive flexibility. Our study demonstrates that both genetic and nongenetic factors impact cognitive flexibility, and variants in genes involved in protein degradation and brain development may contribute to population variation in cognitive function.

Project description:Adaptive behavior emerges through a dynamic interaction between cognitive agents and changing environmental demands. The investigation of information processing underlying adaptive behavior relies on controlled experimental settings in which individuals are asked to accomplish demanding tasks whereby a hidden regularity or an abstract rule has to be learned dynamically. Although performance in such tasks is considered as a proxy for measuring high-level cognitive processes, the standard approach consists in summarizing observed response patterns by simple heuristic scoring measures. With this work, we propose and validate a new computational Bayesian model accounting for individual performance in the Wisconsin Card Sorting Test (WCST), a renowned clinical tool to measure set-shifting and deficient inhibitory processes on the basis of environmental feedback. We formalize the interaction between the task's structure, the received feedback, and the agent's behavior by building a model of the information processing mechanisms used to infer the hidden rules of the task environment. Furthermore, we embed the new model within the mathematical framework of the Bayesian Brain Theory (BBT), according to which beliefs about hidden environmental states are dynamically updated following the logic of Bayesian inference. Our computational model maps distinct cognitive processes into separable, neurobiologically plausible, information-theoretic constructs underlying observed response patterns. We assess model identification and expressiveness in accounting for meaningful human performance through extensive simulation studies. We then validate the model on real behavioral data in order to highlight the utility of the proposed model in recovering cognitive dynamics at an individual level. We highlight the potentials of our model in decomposing adaptive behavior in the WCST into several information-theoretic metrics revealing the trial-by-trial unfolding of information processing by focusing on two exemplary individuals whose behavior is examined in depth. Finally, we focus on the theoretical implications of our computational model by discussing the mapping between BBT constructs and functional neuroanatomical correlates of task performance. We further discuss the empirical benefit of recovering the assumed dynamics of information processing for both clinical and research practices, such as neurological assessment and model-based neuroscience.

Dataset Information

Investigation of Biases and Compensatory Strategies Using a Probabilistic Variant of the Wisconsin Card Sorting Test.

Publications

Investigation of Biases and Compensatory Strategies Using a Probabilistic Variant of the Wisconsin Card Sorting Test.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets