This research develops a method to deliver EGCG, a green tea compound known to break apart Alzheimer's-related protein tangles, into the brain. By chemically attaching EGCG to a carrier that can cross the brain's protective barrier, the project aims to create a potential therapeutic strategy for slowing memory loss and disease progression.

This research investigates mating behavior in Siamese fighting fish and reveals that visual interaction dramatically increases reproductive success. By studying 203 breeding pairs, the project demonstrates the importance of sight in social and mating behavior, suggesting that betta fish possess more sophisticated visual and individual recognition abilities than previously understood.

This research investigates how the olfactory system of the Spanish ribbed newt adapts between aquatic and terrestrial environments. By analyzing cellular and genetic changes in the nose, the study reveals remarkable sensory plasticity, offering broader insights into nervous system flexibility and potential implications for understanding neurodegenerative diseases such as dementia.

This research investigates how differences in butterfly behavior relate to brain evolution and memory. Heliconius butterflies showed superior long-term memory and enlarged mushroom body brain regions compared with related species. The work explores how neurogenesis shapes cognition and may ultimately contribute to understanding memory, brain development, and neurological disorders.

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 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 research improves neural implants for vision restoration by reproducing natural brain activity patterns. Using a two-way stimulation approach in the retina, electrical signals are optimized to activate neurons precisely. This enables more accurate visual perception, moving beyond crude light flashes toward meaningful vision, with potential to restore recognition of familiar faces.

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.

This research uses nematode worms and machine learning to quantify changes in neuron structure linked to neurodegenerative diseases. By replacing subjective visual analysis with objective computational methods, it identifies structural abnormalities and improves understanding of disease mechanisms, supporting future advances in diagnosis and treatment.

This research shows that children born without a hand can generate complex muscle signals by imagining movements, enabling control of advanced prosthetics. Their abilities develop similarly to typical motor patterns, challenging assumptions and expanding access to sophisticated prosthetic technology for paediatric patients.