This research examines whether air pollution affects risk-taking behaviour. Using survey data from 40,000 Indonesians and satellite pollution measurements, it shows that higher pollution levels make people more risk-averse. Because risk preferences influence education, careers, entrepreneurship, and innovation, cleaner air may improve both health outcomes and economic decision-making.

This research investigates how the brain uses different decision-making strategies and how those strategies vary across individuals, including people with neurodivergent conditions such as autism, schizophrenia, and ADHD. Using controlled game environments and brain imaging, the study maps neural decision-making circuits to better understand cognition, behavioural diversity, and potential therapeutic interventions.

This research investigates how reliance on AI systems affects human cognition and reasoning. Using concepts from cognitive offloading, the study compares AI-assisted and independent problem solving, measuring verification behavior, reasoning depth, and decision confidence. The work explores whether increasingly capable AI tools may unintentionally reduce critical thinking and human expertise.

This research uses the Manhattan maze to study rapid learning and memory in mice. The study demonstrates that mice can acquire complex navigation sequences after only a few rewards, retain memories overnight, and generalize learned strategies to new mazes. The findings provide insights into few-shot learning, memory formation, and adaptive intelligence.

This neuroscience research investigates how the human brain constructs and adapts goals. Using fMRI and a dynamic decision-making game, the study identifies neural activity in the prefrontal cortex and anterior cingulate cortex associated with goal selection, valuation, and adaptation. The findings may help develop AI systems better aligned with human goals.

This research investigates the physiological signature of presence by linking heart rate patterns to states of embodiment and attention. Using movement meditation, self-reports, and continuous heart monitoring, it aims to identify the “heartbeat rhythm” of presence. The findings could support technologies that promote emotional regulation, mindfulness, and human connection.

This research investigates the role of force feedback in virtual reality training. By comparing users with and without haptic feedback, it examines effects on brain activity, skill acquisition, and real-world performance. The study aims to improve VR training systems by incorporating sensory input essential for effective motor learning and skill transfer.

This study compares systematic versus exploratory search strategies for locating rare plants. Surprisingly, both methods performed equally, with low detection overall. Challenges such as navigation difficulty and multitasking may explain the results. The findings highlight the need for improved search methods to better identify and protect rare, threatened plant species.

This research examines sound symbolism—the idea that certain sounds inherently convey meaning. Through cross-linguistic analysis of animal names, it investigates how phonetic features relate to perceived traits like size or danger. Findings could improve language learning, branding, and understanding of how human language evolved beyond arbitrary sound-meaning relationships.

This research shows that pauses in information streams alter decision-making. After a break, the brain increases effort, giving greater weight to subsequent information—a “peak-after-break” effect. A computational model explains this as a performance-effort tradeoff. Findings challenge traditional theories and suggest strategic pauses can shape attention, memory, and judgment.