Your brain is home to around 100 billion neurons, all of which are perpetually establishing and breaking connections, known as synapses, with other neurons. There are trillions of these connections throughout your brain helping orchestrate everything from movement, to learning, to establishing and recalling memories.
But we still don't understand how all the connections between those neurons work. Now researchers at MIT and Harvard have created a new computer chip model that could change that in a big way.
Your basic synapse is a connection between two neurons: a presynaptic neuron, and a postsynaptic neuron. Presynaptic neurons release neurotransmitters, which dock with receptors on the postsynaptic neuron and activate what are known as ion channels in the postsynaptic cell membrane.
Ion channels are like a neuron's gatekeepers; they allow charged atoms such as sodium, potassium and calcium into and out of the cell, and are thought to play an important role in the regulation of synaptic plasticity, i.e. the strengthening or weakening of neuronal connections over time.
All this is to say that when neurons talk to one another, there's more regulating their communication than a simple on/off switch; and yet, most of the computer chips that we use to model brain activity operate in this binary fashion.
But researcher Chi-Sang Poon and his colleagues in the Harvard-MIT Division of Health Sciences and Technology have created a model of synaptic plasticity that can actually mimic the intricate intracellular ongoings of a single neuron in a single synapse.
"If you really want to mimic brain function realistically, you have to do more than just spiking [turning neuron-connections on and off]," explains Poon. "You have to capture the intracellular processes that are ion channel-based."
To accomplish this, Poon and his colleagues designed a silicon chip with a total of 400 transistors, which allow current to flow through not in a digital, on/off fashion, but an finely tuned analog one. (The chip is pictured at left.)
"We can tweak the parameters of the circuit to match specific ion channels," Poon says. "We now have a way to capture each and every ionic process that's going on in a neuron."
The researchers describe the implications of their findings in the latest issue of Proceedings of the National Academy of Sciences:
The versatile [synapse device] is applicable to a variety of neuroprosthesis, brain-machine interface, neurorobotics, neuromimetic computation, machine learning, and neural-inspired adaptive control problems.
Translation? The team believes their work will have applications down the road ranging from disease research and treatment, to integration into brain-machine interfaces.
According to Poon, the chip is a huge step towards achieving an unprecedented level of understanding of the human mind, one that could soon allow us to build systems that could actually replace portions of a damaged brain (think novel treatments for stroke victims), or even "enhance part of the brain systems beyond the normal human capacity."
Top image via VLADGRIN/Shutterstock