Similarities between human brains, worms and computer chips
Scientists from the US, the UK, and Germany have discovered that the human brain, the nervous system of a worm, and a computer chip have striking similarities.
Washington: Scientists from the US, the UK, and Germany have discovered that the human brain, the nervous system of a worm, and a computer chip have striking similarities.
"Brains are often compared to computers, but apart from the trivial fact that both process information using a complex pattern of connections in a physical space, it has been unclear whether this is more than just a metaphor," said Danielle Bassett, first author and a postdoctoral research associate in the Department of Physics at UC Santa Barbara.
The scientists have uncovered novel quantitative organizational principles that underlie the network organizations of the human brain, high performance computer circuits, and the nervous system of the worm, known as nematode C. elegans.
Using data that is largely in the public domain, including magnetic resonance imaging data from human brains, a map of the nematode`s nervous system, and a standard computer chip, they examined how the elements in each system are networked together.
They found that all three shared two basic properties. First, the human brain, the nematode`s nervous system, and the computer chip all have a Russian doll-like architecture, with the same patterns repeating over and over again at different scales.
Second, all three showed what is known as Rent`s scaling, a rule used to describe the relationship between the number of elements in a given area and the number of links between them.
Worm brains may seem to have very little in common with human brains and even less in common with computer circuits, Bassett said.
In fact, each of these systems contains a pattern of connections that are locked solidly in a physical space, similar to how the tracks in a railway system are locked solidly to the ground, forming traffic paths that have fixed GPS coordinates.
A computer chip starts out as an abstract connectivity pattern, which can perform a specific function. Stage two involves mapping that connectivity pattern onto the two-dimensional surface of the chip.
This mapping is a key step and must be done carefully in order to minimize the total length of wires –– a powerful predictor of the cost of manufacturing a chip –– while maintaining the abstract connectivity or function.
"Brains are similarly characterized by a precise connectivity which allows the organism to function, but are constrained by the metabolic costs associated with the development and maintenance of long ``wires,`` or neurons," said Bassett.
She said that, given the similar constraints in brains and chips, it seems that both evolution and technological innovation have developed the same solutions to optimal mapping patterns.
The finding is reported in the journal PloS Computational Biology today.