Scientists at the University of Southern California are trying to replicate the functions of brain neurons using carbon nanotubes. The end goal, about 15,000 years from now, is to build an interconnected artificial brain that can do basic functions that the brains of animals can.
From the National Science Foundation:
The researchers have shown that portions of a neuron can be modeled electronically using carbon nanotube circuit models and have performed detailed simulations of the circuit models. A single archetypical neuron, including excitatory and inhibitory synapses, has been modeled electronically and simulated. Parker and her co-researcher Chongwu Zhou are in the process of combining these circuit models of neurons to create a functional carbon nanotube circuit model of a small network of neurons. This small network of interconnected neurons will be simulated using the carbon nanotube models. This network demonstrates an interesting neural circuit that detects moving edges in a selected direction.
Parker believes carbon nanotubes are an ideal material to emulate brain function because their three-dimensional structure allows connectivity in all directions on all planes and because a carbon-based prosthesis is less likely to be rejected by the human body than one made from inorganic materials. But their invasive nature could result in them invading surrounding tissue and prompting lesions and cancers.
“It’s a possibility and something else that needs to be addressed for the technology to be feasible,” Parker said.
As the researchers move ahead with their mathematical modeling and neuron construction, beginning with a single synapse, they ponder “plasticity,” neuroscientists’ term for the brain’s ability to learn and adapt to change. “Our brains can grow new neurons and the synapses between them in an hour–a remarkable biological feature that is difficult to emulate from an engineering perspective,” Parker said.
Emulating such plasticity in a synthetic brain will require a major leap in technology, similar to the leap from cathode ray tubes to transistors. “We don’t know what the new technology will look like yet, but it will be a technology that can self-assemble and reshape itself. As we work in the lab building neurons or constructing mathematical models, we must consider the requirement of plasticity, even if we don’t yet know what it looks like.”