Nature has published a list of the top 25 behavioural science articles of 2023. And (with the help of Consensus AI), I’ve been through the papers to see what could inform our work in the future.
Key takeaways
1. Neurochemical balance affects decision-making and impulsivity, relevant to understanding gambling behaviours.
2. Reward prediction errors are processed asymmetrically, influencing risk assessment and reward-seeking in gambling.
3. Cognitive and emotional control mechanisms differ in anxious individuals, potentially affecting risk-taking and decision-making in gambling.
4. The prefrontal cortex plays a crucial role in addiction behaviours, suggesting targeted interventions might mitigate gambling addiction.
5. Understanding brain responses to rewards and losses can inform strategies to address gambling addiction by rebalancing neural pathways involved in reward processing.
Explores the neural mechanisms of emotional action control in anxious individuals, revealing that they rely on the dorsolateral prefrontal cortex instead of the lateral frontal pole, unlike non-anxious peers. This shift is associated with a more excitable lateral frontal pole and stronger amygdalofugal projections to it in anxious participants. These findings suggest a unique neural vulnerability in anxious individuals, potentially leading to a bottleneck in emotional action control due to the saturation of the lateral frontal pole’s neural range by mild emotional challenges.
Utility: evidence that users may experience gambling products in quite different ways. Worth further exploration both in terms of creating appropriate products and keeping all users safe.
Investigates the impact of exposure to the Russian Internet Research Agency’s influence campaign on Twitter during the 2016 US election. It finds that exposure was heavily concentrated among a small percentage of users, predominantly those identifying as Republicans. Despite the significant reach of these campaigns, the research concludes there was no meaningful relationship between exposure and changes in political attitudes, polarization, or voting behaviour. This suggests that the effect of such foreign influence campaigns on social media may be more limited than previously thought.
Utility: the changing landscape of the last 25 years has shown that people generally seek news that confirms their existing world view. While it is easier than ever before to immerse oneself in a bespoke version of reality, the information provided appears to have less effect than the drip drip effect slowly compounding and reinforcing existing views.
A canonical trajectory of executive function maturation from adolescence to adulthood
Presents a comprehensive study on the maturation of executive function from adolescence to adulthood. Integrating data from four large datasets with diverse executive function tasks, it identifies a canonical nonlinear developmental trajectory of executive function maturation. This trajectory shows rapid development from late childhood to mid-adolescence before stabilizing in late adolescence. The study highlights that executive function development during adolescence is predominantly domain-general, driven by common underlying processes across different tasks. These findings contribute significantly to understanding the maturational timing and nature of executive function development, providing a framework for future research in neurodevelopmental psychology.
Utility: maturational timing is important for responsible decision making. Might have use with tailoring different gambling experiences for different age groups, with more deliberate friction for younger users to slow spontaneous action.
Learning how network structure shapes decision-making for bio-inspired computing
Investigates how network structure influences decision-making through bio-inspired computing. Utilising personalised brain network models from 650 Human Connectome Project participants, it found that those with higher intelligence scores took longer to solve difficult problems, indicating a trade-off between speed and accuracy in decision-making influenced by the balance of excitation and inhibition. This research offers insights into the neural mechanisms underlying intelligent behaviour and decision-making processes.
Utility: AI in gambling is likely to be a thing sooner rather than later. Faster-responding AI may need to sacrifice optimal solutions for quicker ones, a consideration for betting in play, for example.
Neural and computational underpinnings of biased confidence in human reinforcement learning
Delves into how confidence bias, influenced by monetary gains or losses, is processed in the brain during reinforcement learning tasks. Utilising fMRI and computational modeling, the research uncovers that confidence is positively associated with neural activity in the ventromedial prefrontal cortex (vmPFC) and negatively in the dorsolateral and dorsomedial prefrontal cortex. It challenges existing models by showing that vmPFC activity correlates more with confidence levels than with the expected values derived from reinforcement learning predictions.
Utility: basically, this suggests that activity in the vmPFC significantly affects confidence in gambling situations, beyond what the user might have ‘learned’ from such activity to that point. There may be opportunities from big data collected to intervene earlier with individuals whose gambling behaviour is at odds with their successes. Antidepressant drugs are known to affect vmPFC activity, as are L-Dopa (antipsychotic medication) and ketamine. We may want to provide additional warnings to inform users who are taking such medications.
Subjective signal strength distinguishes reality from imagination
Investigates how reality and imagination are distinguished in human perception. It presents a model where the strength of sensory signals determines the perception of reality, suggesting that vivid imagined signals can be indistinguishable from real ones. Experiments with participants assessing imagined and real stimuli supported the model, showing that sensory strength influences reality judgments. Neuroimaging confirmed similar brain areas track both vividness and visibility of experiences. This research challenges previous notions about reality monitoring and suggests implications for understanding hallucinations and the influence of vivid imagery on perception of reality.
Utility: if users are playing for long enough, signals that are designed to mimic reward (and encourage continued play) may be interpreted by the user as confirmation that they should continue. We might want to think about limiting push or encouragement notifications after a certain time period, to slow the reward signalling.
Explores how state-level economic factors affect the relationship between family income and both brain structure and mental health in children. It finds that lower income is associated with smaller hippocampal volume and higher psychopathology, but these effects are moderated by the cost of living and state anti-poverty programs. More generous state support can mitigate the impact of low income, suggesting that policy interventions can influence neurodevelopmental and mental health outcomes. Utility: are people from poor backgrounds more susceptible to addictive behaviours? Very possibly. The brain is at its most plastic during the first few years of life, and poverty can increase the likelihood of maternal deprivation in this period (it doesn’t guarantee it, of course!). Maternal deprivation appears to be the greatest single factor in chronic addiction problems later in life. Extremely invasive to elicit this information from users. Facial recognition AI could identify existing addiction problems of some type (potentially, invasively, almost certainly not with 100% accuracy). Compassionately used, it could help protect the most vulnerable users, but with a laundry list of ethical considerations.
1,001 behavioural insights 
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