Harvard researchers have developed a silicon chip that can map more than 70,000 synaptic connections from 2,000 rat neurons, a significant advancement in neural imaging technology. The research, led by Harvard professor Donhee Ham and published in Nature Biomedical Engineering, builds upon a previous project where they mapped 300 synaptic connections in 2020.
This new chip allows for higher resolution neural activity reading, providing a more accurate biological map of brain connectivity. Unlike existing techniques like electron microscopy, the chip can determine the strength of connections and decipher dynamic information. The method also surpasses Nobel prize-winning techniques by recording signals with higher sensitivity levels in a scalable manner.
Researchers aim to understand how neurons connect and generate function, which is crucial in neuroscience and the artificial intelligence field. With the growing interest in AI and neuromorphic engineering, this research opens up new possibilities for developing next-generation artificial intelligence systems.
Postdoctoral researcher Jun Wang believes this tool can provide other neuroscientists and researchers with a platform to study their questions. Despite the achievement, Ham remains humble, noting the vast number of synapses in the brain. The team’s work represents a significant step towards understanding how neurons configure networks to perform higher tasks, and may lead to breakthroughs in both neuroscience and AI research.
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