English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

RGT is modeled as a Markov decision process and we extended the classical TD-learning algorithm by incorporating risk seeking [4], reward sensitivity and cognitive inflexibility. These behavioral traits were implemented independently and influence either the learning rate or the perception of rewards by the agent. The parameters of the model were extracted for each rat by fitting their performance to the model. We found that the model could account for the performances of good and poor subpopulations of decision makers. Additionally, the parameters defining the behavioral traits extracted from the model correlated significantly with those measured experimentally for the poor and good decision makers’ subgroups. The model was also able to predict the inflexibility of poor decision makers during reversal conditions. Our work supports the hypothesis that it is a combination of high scores for risk seeking, sensitivity to reward and cognitive inflexibility that lead to poor decisionmaking performances. According to the model, behavioral traits affect the learning process of the subjects by altering the estimated value of the received rewards and reducing their ability to reverse their initial estimations. This results in an incorrect perception of the environment, leading to an optimal decision-making according to their world representation but aberrant according to the real outcome of the task.

Modeling maladaptive decision-making in a rat version of the Iowa Gambling Task