Pint: A Static Analyzer for Transient Dynamics of Qualitative Networks with IPython Interface

International audienceThe software Pint is devoted to the scalable analysis of the traces of automata networks, which encompass Boolean and discrete networks. Pint implements formal approximations of transient reachability-related properties, including mutation prediction and model reduction. Pint is distributed with command line tools, as well as a Python module pypint. The latter provides a seamless integration with the Jupyter IPython notebook web interface, which allows to easily save, reuse, reproduce , and share workflows of model analysis. Pint can address networks with hundreds to thousands interacting components , which are typically intractable with standard approaches

Influences of State and Trait Affect on Behavior, Feedback-Related Negativity, and P3b in the Ultimatum Game

The present study investigates how different emotions can alter social bargaining behavior. An important paradigm to study social bargaining is the Ultimatum Game. There, a proposer gets a pot of money and has to offer part of it to a responder. If the responder accepts, both players get the money as proposed by the proposer. If he rejects, none of the players gets anything. Rational choice models would predict that responders accept all offers above 0. However, evidence shows that responders typically reject a large proportion of all unfair offers. We analyzed participants’ behavior when they played the Ultimatum Game as responders and simultaneously collected electroencephalogram data in order to quantify the feedback-related negativity and P3b components. We induced state affect (momentarily emotions unrelated to the task) via short movie clips and measured trait affect (longer-lasting emotional dispositions) via questionnaires. State happiness led to increased acceptance rates of very unfair offers. Regarding neurophysiology, we found that unfair offers elicited larger feedback-related negativity amplitudes than fair offers. Additionally, an interaction of state and trait affect occurred: high trait negative affect (subsuming a variety of aversive mood states) led to increased feedback-related negativity amplitudes when participants were in an angry mood, but not if they currently experienced fear or happiness. We discuss that increased rumination might be responsible for this result, which might not occur, however, when people experience happiness or fear. Apart from that, we found that fair offers elicited larger P3b components than unfair offers, which might reflect increased pleasure in response to fair offers. Moreover, high trait negative affect was associated with decreased P3b amplitudes, potentially reflecting decreased motivation to engage in activities. We discuss implications of our results in the light of theories and research on depression and anxiety