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Researchers from the National University of Singapore (NUS) have demonstrated that a single, standard silicon transistor, the fundamental building block of microchips used in computers, smartphones and almost every electronic system, can function like a biological neuron and synapse when operated in a specific, unconventional way.

Led by Associate Professor Mario Lanza from the Department of Materials Science and Engineering at the College of Design and Engineering, NUS, the research team’s work presents a highly scalable and energy-efficient solution for hardware-based (ANNs).

This brings —where chips could process information more efficiently, much like the —closer to reality. Their study was published in the journal Nature.

Anyone who develops an AI solution sometimes goes on a journey into the unknown. At least at the beginning, researchers and designers do not always know whether their algorithms and AI models will work as expected or whether the AI will ultimately make mistakes.

Sometimes, AI applications that work well in theory perform poorly under real-life conditions. In order to gain the trust of users, however, an AI should work reliably and correctly. This applies just as much to popular chatbots as it does to AI tools in research.

Any new AI tool has to be tested thoroughly before it is deployed in the real world. However, testing in the real world can be an expensive, or even risky endeavor. For this reason, researchers often test their algorithms in computer simulations of reality. However, since simulations are approximations of reality, testing AI solutions in this way can lead researchers to overestimate an AI’s performance.

New in JNeurosci: In a study comparing human brains to macaque and chimpanzee brains, Bryant et al. discovered neuroanatomical features that are unique to humans.

Learn more. ▶️


Determining the brain specializations unique to humans requires directly comparative anatomical information from other primates, especially our closest relatives. Human (Homo sapiens) (m/f), chimpanzee (Pan troglodytes) (f), and rhesus macaque (Macaca mulatta) (m/f) white matter atlases were used to create connectivity blueprints, i.e., descriptions of the cortical grey matter in terms of the connectivity with homologous white matter tracts. This allowed a quantitative comparative of cortical organization across the species. We identified human-unique connectivity profiles concentrated in temporal and parietal cortices, and hominid-unique organization in prefrontal cortex. Functional decoding revealed human-unique hotspots correlated with language processing and social cognition. Overall, our results counter models that assign primacy to prefrontal cortex for human uniqueness.

Significance statement Understanding what makes the human brain unique requires direct comparisons with other primates, particularly our closest relatives. Using connectivity blueprints, we compared to cortical organization of the human to that of the macaque and, for the first time, the chimpanzee. This approach revealed human-specific connectivity patterns in the temporal and parietal lobes, regions linked to language and social cognition. These findings challenge traditional views that prioritize the prefrontal cortex in defining human cognitive uniqueness, emphasizing instead the importance of temporal and parietal cortical evolution in shaping our species’ abilities.

A new Science Immunology study shows that disruptions to immunosuppressive intraepithelial lymphocytes and intestinal immunity occurs prior to the onset of chronic ileal inflammation in mouse models of Crohn’s Disease.


Multiple layers of γδ IEL dysregulation and loss of their immunosuppressive capacity occur before the onset of chronic ileitis.

The authors show that neuroprotective and neurotoxic astrocytes representional cellular substates present during neuroinflammation and that targeting mTOR in astrocytes reduces neurotoxicity, suggesting a potential therapeutic strategy for neurodegenerative diseases.

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