#Artificialintelligence

A team led by Raphael Kaplan at Universitat Jaume I in Castelló explored how the brain uses context boundaries to guide decisions in both physical and abstract spaces. The study, a collaboration with researchers from Spain, Italy, and the United States, appeared in Nature Communications and PLOS Biology, highlighting how the hippocampus and medial prefrontal cortex process boundaries and social context.

The research shows that context boundaries help the brain make choices more efficiently. The hippocampus, long known for spatial memory, also responds to abstract boundaries. For example, when evaluating a property purchase, the brain integrates factors like price and size as if they were navigational markers. This demonstrates the brain’s versatility in managing both real-world spaces and conceptual ideas.

A collaboration between the University of Göttingen and the Max Planck Institute for Dynamics and Self-Organization has unveiled “infomorphic neurons” that learn autonomously by mimicking brain-like processes. Published in the Proceedings of the National Academy of Sciences, this work shifts away from traditional supervised neural networks toward self-organizing artificial units. The neurons can determine which inputs matter for learning, reducing the need for constant external guidance.

The human brain operates through decentralized, energy-efficient networks. Biological neurons learn by responding to neighboring cells rather than following rigid, pre-set pathways. Infomorphic neurons imitate this adaptability, selecting learning goals and rules with minimal external control. With self-organization and specialization, these networks promise more robust problem solving in real-world tasks.

A team of researchers is advancing brain health insights by linking brain stiffness to aging and neurodegenerative risk. Led by a biomedical engineering associate professor and an electrical engineering assistant professor, the group uses magnetic resonance elastography (MRE) together with artificial intelligence to estimate the brain’s biological age. This approach could improve early detection and intervention for conditions like Alzheimer’s disease, dementia, and other neurodegenerative disorders, with potential relevance for Thailand’s aging population.