Summary: Focus on rewards makes teens less able to learn to avoid punishment or consider the consequences of alternative action, a new study reports.
Source: PLOS.
Adolescents focus on rewards and are less able to learn to avoid punishment or consider the consequences of alternative actions, finds a new UCL-led study.The study, published in PLOS Computational Biology, compared how adolescents and adults learn to make choices based on the available information.
18 volunteers aged 12-17 and 20 volunteers aged 18-32 completed tasks in which they had to choose between abstract symbols. Each symbol was consistently associated with a fixed chance of a reward, punishment or no outcome. As the trial progressed, participants learnt which symbols were likely to lead to each outcome and adjusted their choices accordingly.
Adolescents and adults were equally good at learning to choose symbols associated with reward, but adolescents were less good at avoiding symbols associated with punishment. Adults also performed significantly better when they were told what would have happened if they had chosen the other symbol after each choice, whereas adolescents did not appear to take this information into account.
“From this experimental lab study we can draw conclusions about learning during adolescence. We find that adolescents and adults learn in different ways, something that might be relevant to education,” explains lead author Dr Stefano Palminteri, who conducted the study at the UCL Institute of Cognitive Neuroscience and now works at the École Normale Supérieure in Paris. “Unlike adults, adolescents are not so good at learning to modify their choices to avoid punishment. This suggests that incentive systems based on reward rather than punishment may be more effective for this age group. Additionally, we found that adolescents did not learn from being shown what would have happened if they made alternative choices.”
To interpret the results, the researchers developed computational models of learning and ran simulations applying them to the results of the study. The first was a simple model one that learnt from rewards, and the second model added to this by also learning from the option that was not chosen. The third model was the most complete and took the full context into account, with equal weighting given to punishment avoidance and reward seeking. For example, obtaining no outcome rather than losing a point is weighted equally to gaining a point rather than having no outcome.
Comparing the experimental data to the models, the team found that adolescents’ behaviour followed the simple reward-based model whereas adults’ behaviour matched the complete, contextual model.
“Our study suggests that adolescents are more receptive to rewards than they are to punishments of equal value,” explains senior author Professor Sarah-Jayne Blakemore (UCL Institute of Cognitive Neuroscience). “As a result, it may be useful for parents and teachers to frame things in more positive terms. For example, saying ‘I will give you a pound to do the dishes’ might work better than saying ‘I will take a pound from your pocket money if you don’t do the dishes’. In either case they will be a pound better off if they choose to do the dishes, but our study suggests that the reward-based approach is more likely to be effective.”
Funding: SP is supported by a Marie Sklodowska- Curie Individual European Fellowship (PIEF-GA-2012 Grant 328822). EJK is supported by a Medical Research Council studentship. GC is funded by the European Research Council (ERC Consolidator Grant 617629). SJB is funded by a Royal Society University Research Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
Source: Stefano Palminteri – PLOS
Image Source: This NeuroscienceNews.com image is credited to ZEISS Microscopy.
Original Research: Full open access research for “The Computational Development of Reinforcement Learning during Adolescence” by Stefano Palminteri, Emma J. Kilford, Giorgio Coricelli, and Sarah-Jayne Blakemore in PLOS Compuational Biology. Published online June 20 2016 doi:10.1371/journal.pcbi.1004953
[cbtabs][cbtab title=”MLA”]PLOS. “Simple Reward Based Learning Suits Teens Best.” NeuroscienceNews. NeuroscienceNews, 20 June 2016.
<https://neurosciencenews.com/teens-reward-learning-4525/>.[/cbtab][cbtab title=”APA”]PLOS. (2016, June 20). Simple Reward Based Learning Suits Teens Best. NeuroscienceNews. Retrieved June 20, 2016 from https://neurosciencenews.com/teens-reward-learning-4525/[/cbtab][cbtab title=”Chicago”]PLOS. “Simple Reward Based Learning Suits Teens Best.” https://neurosciencenews.com/teens-reward-learning-4525/ (accessed June 20, 2016).[/cbtab][/cbtabs]
Abstract
The Computational Development of Reinforcement Learning during Adolescence
Adolescence is a period of life characterised by changes in learning and decision-making. Learning and decision-making do not rely on a unitary system, but instead require the coordination of different cognitive processes that can be mathematically formalised as dissociable computational modules. Here, we aimed to trace the developmental time-course of the computational modules responsible for learning from reward or punishment, and learning from counterfactual feedback. Adolescents and adults carried out a novel reinforcement learning paradigm in which participants learned the association between cues and probabilistic outcomes, where the outcomes differed in valence (reward versus punishment) and feedback was either partial or complete (either the outcome of the chosen option only, or the outcomes of both the chosen and unchosen option, were displayed). Computational strategies changed during development: whereas adolescents’ behaviour was better explained by a basic reinforcement learning algorithm, adults’ behaviour integrated increasingly complex computational features, namely a counterfactual learning module (enabling enhanced performance in the presence of complete feedback) and a value contextualisation module (enabling symmetrical reward and punishment learning). Unlike adults, adolescent performance did not benefit from counterfactual (complete) feedback. In addition, while adults learned symmetrically from both reward and punishment, adolescents learned from reward but were less likely to learn from punishment. This tendency to rely on rewards and not to consider alternative consequences of actions might contribute to our understanding of decision-making in adolescence.
“The Computational Development of Reinforcement Learning during Adolescence” by Stefano Palminteri, Emma J. Kilford, Giorgio Coricelli, and Sarah-Jayne Blakemore in PLOS Compuational Biology. Published online June 20 2016 doi:10.1371/journal.pcbi.1004953
