For many engineers, plasticity is a term referring to a material's deformation under load, but when talking about the brain, plasticity refers to how brain structures change from experience. The plasticity phenomenon is believed to affect functions including memory and learning, and researchers at Massachusetts Institute of Technology (MIT; Cambridge, MA) are moving one step closer to creating a computer system replicating aspects of the human brain by developing a new computer chip that models how neurons respond to information at synapses.
The activity of a single synapse, a connection between two neurons in the brain, takes about 400 transistors to recreate in the MIT team's silicon chip. In the brain, neurons release neurotransmitters, which bind to receptors across the synapse to activate ion channels, changing the cell's electrical potential and firing an electrical impulse if the change is dramatic enough. In the MIT chip, transistors imitate the activity of ion channels, with current flowing in analog pattern rather than in a binary, on/off digital pattern. This allows a gradient of electrical potential to flow through the transistors in a way similar to cellular flow through ion channels.
While previous research has resulted in circuits that could simulate the firing of an electrical impulse, they couldn't simulate all the circumstances that produced the action potential. The parameters of the circuit can be tweaked to match the specific ion channels, according to Chi-Sang Poon, a principal research scientist, so not only the spike of the action potential is mimicked, but also the ion channel-based intracellular processes.
In the future, the silicon chip could have applications in neural prosthetic devices like artificial retinas, or could interface with other biological systems. The ion channels, which control the flow of calcium, potassium, and sodium, are also related to synapse weakening long-term depression (LTD) and synapse strengthening long-term potentiation (LTP). Proposing a resolution to the debate on how depression occurs, the team has been able to accurately simulate both LTP and LTD with the chip. NMDA receptors detect post synaptic activation, and the researchers found that if they are active at the same time as endo-cannabinoid receptors, which are involved in functions including pain sensation, memory, and appetite, LTD is a result. Endo-cannabinoid receptors involvement with LTD has only been a theory until the MIT team was able to simulate the receptors role with the chip. A paper describing the chip was published in the Nov. 14 Proceedings of the National Academy of Sciences.