Human Brain Complexity Surpasses Animal Brains
Human brains are superior
not just in the quantity of
neurons, but in the quality
Surprise! The Human Brain is More Complex than Once Believed!
Research on cortical pyramidal neurons has revealed important differences between humans and other mammals. Compared with the mammalian brains examined in this research, the human brain exhibited significantly greater cellular complexity.
by Jerry Bergman, PhD
Introduction
This paper reviews an empirical investigation into the human and mammal brain. The study by five authors primarily from the Hebrew University of Jerusalem addressed the following question:
Humans exhibit unique cognitive abilities within the animal kingdom, but the neural mechanisms driving these advanced capabilities remain poorly understood. Human cortical neurons differ from those of other species, such as rodents, in both their morphological and physiological characteristics.[1]
For many decades, the prevailing view of what makes the human brain capable of language, imagination, mathematics, and invention was mainly the “sheer number of neurons in the human brain—close to 100 billion—and the vast network of connections among them.” A new study published in the Proceedings of the National Academy of Sciences concluded that the “Human Brain Is More Complex Than Once Believed.”[2]
Specifically, they found evidence that it is not just the number of connections that makes the human brain capable of language, imagination, mathematics, music, art and invention, but the extraordinary computational power of individual brain cells in humans compared to mammals.[3] Specifically, they evaluated a type of multipolar neuron found in certain areas of the brain, including the cerebral cortex, the hippocampus, and the amygdala, called pyramidal cells, or pyramidal neurons.
Fig 1. Pyramidal neuron visualized by green fluorescent protein. From Wikimedia Commons.
A pyramidal neuron is a type of multipolar neuron found in the cerebral cortex, hippocampus, and amygdala (see Figure 1)—and discovered that human pyramidal neurons exhibit substantially greater complexity than those of the mammalian species included in the study.
This new discovery is not especially surprising. I regularly come across articles stating that new research has shown that something (ie. Heart, lungs, retina, etc.) is more complex than once believed. Examples abound. Here are a few examples, paraphrased for brevity, that I found in a recent internet search:
- Scientists routinely discover that various elements of our universe are far more complex than once believed, driven by advancements in genomic sequencing, deep-sea exploration, and quantum mechanics. Recent major paradigm shifts span multiple fields of science.
- Traditional anthropological models assumed modern humans evolved linearly from a single, continuous ancestral lineage in Africa but ancestral lineage in Africa has proven to be complex than once believed.
- Eukaryotes (all plants, animals, and fungi) were thought to have evolved only after oxygen became highly abundant in Earth’s atmosphere but eukaryote evolution is more complex than once believed.
- Genetic analysis published in Nature Genetics revealed that human origins are highly structural and more complex than once believed. Modern humans actually descended from at least two separate ancestral populations that drifted apart for over a million years before merging back together.
- Scientists historically assumed quantum memory could be completely understood and measured solely by tracking changes in quantum states over time. But quantum memory is more complex than once believed.
The growing recognition of complexity extends well beyond these examples. Whether studying the human brain, living cells, ecosystems, or the cosmos, scientists repeatedly discover that nature contains additional layers of organization and sophistication that were previously unknown. The greater complexity level gap between mammal and human brains has now been quantified as follows:
Functional Complexity Index (FCI), a deep-learning-based measure that quantifies the input–output complexity of individual cells. Applying FCI to detailed models of human and rat cortical pyramidal neurons, we uncover a pronounced species gap: human neurons exhibit higher complexity. Mechanistically, this is attributable to expanded dendritic surface and richer branching together with greater density and nonlinearity of NMDA-receptor signaling. Layer wise profiles diverge, with neuron complexity peaking in L2/3 in humans.[4]
The greater complexity level gap between mammal and human brains has now been quantified. Specifically, the researchers quantified, for the first time, the computational complexity gap between individual human and rat cortical pyramidal neurons using a new measure called the Functional Complexity Index (FCI). Rats were used for many reasons including they share about 90% of their genes with humans. They are also highly intelligent, capable of complex learning, and are ideal for behavioral psychology, memory, and cognitive studies.[5] When I did genetic research we used mostly rats. The Discussion section of the Aizenbud paper about the mammal and human included these significant admissions about the newly discovered significant neuronal gap between mammals and humans:
This gap in the mammal and human brain is particularly critical in the context of human evolution… human cortical pyramidal neurons are significantly more functionally complex than their rat counterparts; a difference that arises primarily from morphological features and is further amplified by nonlinear synaptic dynamics.[6]
In other words, the researchers concluded that the superior computational capabilities of human pyramidal neurons are not merely the result of having more neurons or more synaptic connections. Instead, individual human neurons possess structural and functional properties that enable them to perform substantially more complex computations than comparable neurons in mammals.
Summary
One line of evidence commonly cited in support of evolution is the design similarity observed in various animals. One such similarity is the structural similarity observed among the nervous systems of different species. However, the study reviewed here documents a substantial functional and structural gap between human and rat cortical pyramidal neurons. Using a newly developed Functional Complexity Index (FCI), the researchers found that individual human pyramidal neurons are significantly more computationally complex than their mammal counterparts.
The study compared humans with rats rather than with our closest living relatives, the primates. A valuable direction for future research would be to apply the same methods to compare human and nonhuman primate cortical pyramidal neurons. My prediction would be that, if such a study was undertaken, a similarly pronounced difference would be found, which would further illuminate the unique neuronal features associated with human cognition.
Summary
Evolutionary theory predicts that organisms sharing a common ancestry should exhibit many similarities in their biological structures. At the same time, important differences are expected to accompany the evolution of distinct capabilities. The study reviewed here documented a substantial difference in the computational complexity of cortical pyramidal neurons between humans and rats. Specifically, the researchers found that human cortical pyramidal neurons are significantly more functionally complex than their rat counterparts.
Because this study compared humans with rats, it does not address how human neurons compare with those of our closest evolutionary relatives. An informative next step would be to conduct similar empirical comparisons between humans and nonhuman primates. If comparable differences were found, they would provide additional insight into the neuronal features that underlie uniquely human cognitive abilities.
Summary
[1] Aizenbud, Ido, et al., “Dendritic morphology and synaptic nonlinearities enhance functional complexity in human cortical neurons” Proceedings of the National Academy of Sciences 123(28): e2533168123, https://doi.org/10.1073/pnas.2533168123, 7 July 2026.
[2] Aizenbud, et al., 2026.
[3] Aizenbud, et al., 2026.
[4] Aizenbud, et al., 2026; emphasis added.
[5] The Advantages Of Rat Models. https://www.genetargeting.com/ingenious-blog/the-advantages-of-rat-models/
[6] Aizenbud,et al., 2026, emphasis added.
Dr. Jerry Bergman has taught biology, genetics, chemistry, biochemistry, anthropology, geology, and microbiology for over 40 years at several colleges and universities including Bowling Green State University, Medical College of Ohio where he was a research associate in experimental pathology, and The University of Toledo. He is a graduate of the Medical College of Ohio, Wayne State University in Detroit, the University of Toledo, and Bowling Green State University. He has over 1,900 publications in 14 languages and 40 books and monographs. His books and textbooks that include chapters that he authored are in over 1,800 college libraries in 27 countries. So far over 80,000 copies of the 60 books and monographs that he has authored or co-authored are in print. For more articles by Dr Bergman, see his Author Profile.