Technical Program

Paper Detail

Paper: PS-2A.31
Session: Poster Session 2A
Location: H Lichthof
Session Time: Sunday, September 15, 17:15 - 20:15
Presentation Time:Sunday, September 15, 17:15 - 20:15
Presentation: Poster
Publication: 2019 Conference on Cognitive Computational Neuroscience, 13-16 September 2019, Berlin, Germany
Paper Title: High trait anxious individuals represent aversive environment as multiple states: a computational mechanism behind reinstatement
Manuscript:  Click here to view manuscript
License: Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
DOI: https://doi.org/10.32470/CCN.2019.1377-0
Authors: Ondrej Zika, Katja Wiech, Oxford University, United Kingdom; Nicolas Schuck, Max Planck Institute for Human Development, Germany
Abstract: Learning the likelihood of aversive events is achieved either by gradual learning or via inference of hidden states. We previously linked the tendency towards state switching to trait anxiety but the effect of environmental noise has not been investigated. In the present study we employ a Pavlovian probabilistic learning paradigm to test how environmental noise promotes either state switching or gradual learning. Participants completed three sessions varying in shock contingency jumps (60/40%, 75/25% or 90/10%). As a signature of state-switching we analyzed steepness of post-reversal switch. In support of our hypothesis we found that steepest switches were present in the 90/10 environment. This effect was found to be driven by high trait anxiety. Trait anxiety also positively correlated with difference between acquisition and extinction. Next, we developed a state switching model and performed model comparison using cross-validation. Analysis of model parameters found positive correlation between trait anxiety and tendency to create more states. In summary, our behavioural and modelling result show that less noisy environments encourage state switching, and that anxious individual have an increased tendency to represent the environment as multiple states. This result highlights trait anxiety as vulnerability in successful extinction treatment.