Robotic arm could help reveal brain’s inner secrets
A group of researchers at MIT and Georgia Tech has built a robotic arm that can automate whole-cell patch clamping, a complicated technique that normally requires great manual dexterity and takes researchers months to master. Once streamlined, this technology will monitor and record the electrical signals generated by the neurons in a living brain, to help uncover the secret inner workings of the human mind - or at least, in the not-so-distant future, of a lab rat's.
Robots have become the biologist's best friend across a number of fields: the Human Genome Project wouldn't have been possible without the help of a genome sequencer and, in some cases, robots have become so helpful that they've proved they could even replace biologists altogether.
As of now, robotics has yet to make a real dent in neuroscientific research. But the robotic device developed at MIT and Georgia Tech may soon change the game once and for all just by showing what's possible. A far cry from the "clumsy robot" stereotype, this piece of research involved putting a robot in charge of whole-cell patch clamping, an extremely delicate procedure that requires maximum precision and is used to record information from neurons in the living brain of anesthetized laboratory mice.
Whole-cell patch clamping involves bringing a tiny hollow glass pipette in contact with the cell membrane of a neuron, then opening up a small pore in the membrane to record the electrical activity within the cell.
"It's a sequence of motor skills that must be performed with exquisite temporal registration, coupled to a sensory intuition for when a cell is nearby," Ed Boyden, associate professor of biological engineering and brain and cognitive sciences at MIT explained to us.
Using this technique, scientists could classify the thousands of different types of cells in the brain and understand how they interact. The method could be particularly useful in studying brain disorders such as schizophrenia, Parkinson's disease, autism and epilepsy, by helping describe how those diseases alter specific molecules within specific cells of the living brain.
The team reduced the complex manual process to a four-step algorithm. As it moves toward the cerebral cortex in tiny two-micrometer steps, the tip of the pipette first monitors electrical impedance to detect contact with a cell; a surge in impedance signals that a cell was detected, at which point the pipette stops instantly, preventing it from poking through the membrane; then, suction is applied to form a seal with the cellular membrane; and finally, the electrode can break through the membrane to record the neuron's electrical activity.
This system can detect cells with 90 percent accuracy and establish a connection with the detected cells about 40 percent of the time. "A very good human operator might be able to work with such accuracy for a short time. But the robot can do it continuously. And a single human can control many robots. So we anticipate that as the technology matures, a single human controlling a robot could do as much work as perhaps 10-20 people," Boyden commented.
By injecting a dye into the cell to determine its shape and using the device to extract the cell's nucleus and read its genetic profile, the researchers are working on building a "catalog" of the thousands of different types of neurons found within the brain.
The team is now also working on increasing the number of electrodes so they can record from multiple neurons at a time, potentially allowing them to determine how different parts of the brain are connected.
"We're still working on this - it's a very active and dynamic area of research," Dr. Boyden added. "But the ability to record connected cells could enable the answering of fundamental questions in neuroscience - such as how neurons work together to compute behavior, or how disease arises from malfunction of communication between cells."
A paper detailing the research efforts appears in the May 6 issue of Nature Methods. Development of the new technology was funded primarily by the National Institutes of Health, the National Science Foundation and the MIT Media Lab and the researchers recently created a startup, Neuromatic Devices, to commercialize the system.
Source: Georgia Tech
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