A groundbreaking study published in the Proceedings of the National Academy of Sciences (PNAS) reveals that individual human cortical neurons can perform far more complex computations than those of other mammals. Researchers from Hebrew University, led by Professors Idan Segev and Mickey London, developed a new method to measure the computational complexity of single brain cells. They found that the richly branching dendritic trees and unique electrical properties of human cortical neurons allow them to process incoming information (like distinguishing between images of cats and dogs) in sophisticated ways — essentially functioning as tiny biological computers rather than simple on-off switches. This challenges the long-held belief that human intelligence stems solely from the sheer number of neurons and their connections. The findings also suggest a new direction for artificial intelligence: brain-inspired AI systems could be built from artificial units that are themselves computationally deep, more closely mirroring biological neurons.
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