Unveiling the Mathematical Blueprint of Neuron Clustering in the Brain

unveiling the mathematical blueprint of neuron clustering in the brain.jpg Science

In a groundbreaking discovery that could pave the way for more advanced computer models of the brain, scientists have found that the density of neurons in the brain adheres to a fundamental mathematical function. This intriguing revelation, confirmed across various mammals, provides a statistical perspective that could illuminate the relationship between neuron densities and brain connectivity, according to Aitor Morales-Gregorio, a study co-author and researcher at the German scientific institute Forschungszentrum Jülich.

Despite previous attempts to understand what regulates the density of neurons in the brain, it has remained a largely unexplored area, with limited information available on the variation of nerve cell density within cortical regions. This new study, led by Morales-Gregorio and his colleague Alexander van Meegen, a postdoctoral researcher at Harvard University, combined data from several mammals and unveiled a common pattern of neuron distribution described by a lognormal distribution. This implies that while most regions have average neuron densities, a few areas possess a significantly higher density, potentially indicating crucial deviations from the norm.

Brain Neuron Density Decoded: A Lognormal Distribution Across Mammals

A groundbreaking finding reveals that the density of neurons in the brain, across a diverse range of mammals, is governed by a basic mathematical function. This discovery, led by researchers Aitor Morales-Gregorio from Forschungszentrum Jülich and Alexander van Meegen, a postdoctoral researcher at Harvard University, holds potential for future advancements in building more accurate computer models of the brain.

Discovering the Pattern

In an attempt to build brain models, the team found a lack of understanding about what determines the density of neurons in the brain. Previous research mostly compared densities from different species or from some cortex layers, providing little insight into how nerve cell density might fluctuate within cortical regions.

Analyzing previously collected data from various mammals including mice, marmosets, macaques, humans, galagos, owl monkeys and baboons, the researchers discovered a common pattern. Regardless of the species, the neuron density within different cortical regions followed a lognormal distribution.

The Significance of Lognormal Distribution

Plotting a lognormal distribution on a graph results in a skew to one side, tapering off to a long tail on the right. According to van Meegen, this indicates that while many regions have average neuron densities, some regions demonstrate significantly higher density. These higher density regions, although rare, hold significance as they represent important deviations from the norm.

Van Meegen explains that focusing solely on the mean number of neurons might overlook these differences. The long-tailed distribution suggests that even minor changes to extreme outliers in density could substantially impact brain connectivity or function.

Origin of the Lognormal Distribution

The team also explored why this pattern was consistent across such varied mammals. They found that the lognormal distribution arises naturally from the way neurons are created, by cell division in a somewhat unpredictable environment, without the need for any regulatory processes.

Morales-Gregorio suggests that the origin of this pattern could be linked to how the brain develops, "by cells splitting over and over with a little bit of noise, possibly from internal variability or changes in the environment." He adds, "This probably explains why it’s everywhere."

The researchers are now focusing on how this distribution pattern influences neuron communication and whether disruptions in the pattern could lead to neurological issues.


This discovery of a universal pattern in neuron density across various mammals is a significant stride in neuroscience. It provides a fresh perspective on understanding brain connectivity and function, which could lead to advancements in creating more accurate computer models of the brain. Furthermore, the research promises to shed light on the potential link between disruptions in neuron density distribution and neurological problems.

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