Lose-Shift Responding in Humans Is Promoted by Increased Cognitive Load

Abstract

The propensity of animals to shift choices immediately after unexpectedly poor reinforcement outcomes is a pervasive strategy across species and tasks. We report here on the memory supporting such lose-shift responding in humans, assessed using a binary choice task in which random responding is the optimal strategy. Participants exhibited little lose-shift responding when fully attending to the task, but this increased by 30%–40% in participants that performed with additional cognitive load that is known to tax executive systems. Lose-shift responding in the cognitively loaded adults persisted throughout the testing session, despite being a sub-optimal strategy, but was less likely as the time increased between reinforcement and the subsequent choice. Furthermore, children (5–9 years old) without load performed similarly to the cognitively loaded adults. This effect disappeared in older children aged 11–13 years old. These data provide evidence supporting our hypothesis that lose-shift responding is a default and reflexive strategy in the mammalian brain, likely mediated by a decaying memory trace, and is normally suppressed by executive systems. Reducing the efficacy of executive control by cognitive load (adults) or underdevelopment (children) increases its prevalence. It may therefore be an important component to consider when interpreting choice data, and may serve as an objective behavioral assay of executive function in humans that is easy to measure.

Pupil Dilation and Response Slowing Distinguish Deliberate Explorative Choices in the Probabilistic Learning Task

“…Potentially, the disadvantageous choices could be caused solely by negative outcomes of a preceding advantageous choice, which could prompt the participants to immediately change their preference (Gaffan & Davies, 1981;Ivan, Banks, Goodfellow, & Gruber, 2018) i.e., to follow a Win-Stay Lose-Shift strategy (see e.g., Ellerby & Tunney, 2017). In order to check whether the disadvantageous choices were mainly caused by a previous loss, we investigated probabilities of transitions leading from the advantageous to the disadvantageous choice.…”

Switching Competitors Reduces Win-Stay but Not Lose-Shift Behaviour: The Role of Outcome-Action Association Strength on Reinforcement Learning

“…As such, the internal phasic state generated by positive outcomes along with the external experience of switching opponents makes it more likely that better performance will be expressed. In addition to extending time between trials [58], switching opponents can be added to the toolkit that helps to reduce the expression of typical reinforcement learning rules, thereby helping individuals who may be at their most cognitively vulnerable within competitive environments.…”

Behavioural and neural limits in competitive decision making: The roles of outcome, opponency and observation

“…While the data from Experiment 2 suggest a somewhat pessimistic (inhibitory) role of interruption during competition, it is clear that similar kinds of decision-making might be naturally interrupted after the experience of a positive outcome either by the player in the form of post-reinforcement pausing (e.g., Dixon & Schreiber, 2004;Dyson et al, 2018;Verbruggen et al, 2017;Forder & Dyson, 2016) or by the opponent itself such as in the case of slot machines where longer music tends to play when the win is bigger (e.g., Dixon et al, 2013). This leads us to the intriguing possibility that mandatory pauses following negative outcomes during play conditions might help to break the cyclical poorer-quality decision making characterised in problem gambling (see Ivan, Banks, Goodfellow & Gruber, 2018, for a similar suggestion).…”