The secret of human intelligence may lie in the power of a single brain cell

by Hebrew University of Jerusalem

edited by Lisa Lock, reviewed by Andrew Zinin

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What makes the human brain capable of language, imagination, mathematics and invention? For many years, the prevailing view was that the secret of human intelligence lay mainly in scale: the sheer number of neurons in the human brain—close to 100 billion—and the vast network of connections among them. But a new study published in the Proceedings of the National Academy of Sciences suggests that part of the answer may lie at a much smaller scale: in the extraordinary computational power of individual brain cells.

Researchers found that neurons in the human cortex are significantly more complex information-processing units ("microchips") than those of other mammals. The findings suggest that the building blocks of the human cortex may themselves be uniquely powerful, offering a possible explanation for how humans developed such exceptional cognitive abilities.

The study was led by Hebrew University researchers Profs. Idan Segev and Mickey London, together with Ph.D. students Ido Aizenbud and Daniela Yoeli at the Edmond and Lily Safra Center for Brain Sciences (ELSC), and in collaboration with Prof. Chris de Kock from the Free University, Amsterdam.

"People often think of a neuron as a simple switch that either turns on or off," said Segev. "What we show is that a single human neuron is itself an extraordinarily sophisticated computing device."

To make the discovery, the researchers developed a new way to measure the computational complexity of individual neurons. Using advanced computer models and artificial intelligence, they assessed how difficult it would be for a state-of-the-art artificial neural network (ANN) to learn and reproduce the input/output behavior of a single brain cell.

The harder it is for the "twin" artificial network to imitate the input-to-output function of the neuron, the more computationally powerful that neuron is.

The results show that human cortical neurons have a remarkable computational advantage. Thanks to their richly branching dendritic trees and distinctive electrical properties, these cells can perform surprisingly complex computations on incoming information, such as visual input (e.g., distinguishing between images of cats versus dogs).

This means that a single human cortical neuron is not just a simple "on–off" building block in the brain; it is already a sophisticated computing unit in its own right, with computational capabilities equivalent to those of a deep neural network.

The findings challenge the traditional view that intelligence emerges mainly from the number of neurons and the connections between them. Instead, they suggest that the sophistication of the neurons themselves may have played an important role in the evolution of human cognition.

The study also offers a new systematic and general framework for linking the physical structure of brain cells to their computational abilities, bringing scientists one step closer to understanding how the human brain gives rise to thought, learning and cognition.

The study may also inspire a new generation of brain-inspired AI, built from artificial units that are themselves computationally deep and powerful, more like biological neurons and very different from the highly simplified units that underlie today's state-of-the-art machine-learning systems.

Publication details

Ido Aizenbud et al, Dendritic morphology and synaptic nonlinearities enhance functional complexity in human cortical neurons, Proceedings of the National Academy of Sciences (2026). DOI: 10.1073/pnas.2533168123

Journal information: Proceedings of the National Academy of Sciences

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Neurology Provided by Hebrew University of Jerusalem Who's behind this story?

Lisa Lock

BA art history, MA material culture. Former museum editor, paramedic, and transplant coordinator. Editing for Science X since 2021. Full profile →

Andrew Zinin

Master's in physics with research experience. Long-time science news enthusiast. Plays key role in Science X's editorial success. Full profile →

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