#Artificial Intelligence

Recent research from the Decision and Memory group at Universitat Jaume I in Castelló, led by Raphael Kaplan, unveils intriguing insights into how our brains navigate decision-making in both spatial and abstract environments. This collaborative study, involving researchers from Spain, Italy, and the United States, was published in two prominent scientific journals, Nature Communications and PLOS Biology, showcasing the nuanced roles of the hippocampal and medial prefrontal cortex in processing environmental boundaries and social contexts.

In an innovative leap forward for artificial intelligence, researchers from the University of Göttingen and the Max Planck Institute for Dynamics and Self-Organization have unveiled “infomorphic neurons” that can learn independently by emulating the complex learning processes of the human brain. Published in the Proceedings of the National Academy of Sciences, this research presents a significant advancement in creating artificial neurons that more closely mimic their biological counterparts. The capability of these neurons to self-organize and independently derive necessary information marks a substantial departure from conventional artificial neural networks, which largely rely on external supervision to process input signals.

Recent advancements in understanding brain age and health signal a transformative leap in diagnosing and potentially combating neurological diseases such as Alzheimer’s and dementia. Through the pioneering efforts of researchers Curtis Johnson and Austin Brockmeier at the University of Delaware (UD), a new method employing artificial intelligence and magnetic resonance elastography (MRE) is revolutionizing how scientists measure brain aging and deterioration. By accurately mapping brain stiffness and volume, the team provides a groundbreaking tool that aligns predictive accuracy with practical applicability for early identification of neurological disorders.

Recent advancements in neuroimaging spearheaded by scientists at the University of Delaware are shedding light on the intricate relationship between brain stiffness and age-related diseases such as Alzheimer’s. Curtis Johnson, an associate professor of biomedical engineering, and Austin Brockmeier, an assistant professor of electrical and computer engineering, have collaborated to develop innovative methods for predicting the biological age of the brain using magnetic resonance elastography (MRE) combined with artificial intelligence. This groundbreaking research could revolutionize how we understand, prevent, and treat neurodegenerative diseases affecting millions worldwide, including in Thailand.