A way has been devised by researchers led by one of Indian origin, to automate the process of detecting and recording information from neurons in the living brain.
Gaining access to the inner activities of a neuron in the living brain offers a wealth of useful information: its patterns of electrical activity, its shape, even a profile of which genes are turned on at a given moment.
However, achieving this entry is such a painstaking task that it is considered an art form; it is so difficult to learn that only a small number of labs in the world practice it.
But that could soon change: Researchers at MIT and the Georgia Institute of Technology have shown that a robotic arm guided by a cell-detecting computer algorithm can identify and record from neurons in the living mouse brain with better accuracy and speed than a human experimenter.
The new automated process eliminates the need for months of training and provides long-sought information about living cells' activities. Using this technique, scientists could classify the thousands of different types of cells in the brain, map how they connect to each other, and figure out how diseased cells differ from normal cells.
"Our team has been interdisciplinary from the beginning, and this has enabled us to bring the principles of precision machine design to bear upon the study of the living brain," Craig Forest, an assistant professor in the George W. Woodruff School of Mechanical Engineering at Georgia Tech, said.
His graduate student, Suhasa Kodandaramaiah, spent the past two years as a visiting student at MIT, and is the lead author of the study. he method could be particularly useful in studying brain disorders such as schizophrenia, Parkinson's disease, autism and epilepsy, Ed Boyden, associate professor of biological engineering and brain and cognitive sciences at MIT, said.
"In all these cases, a molecular description of a cell that is integrated with [its] electrical and circuit properties ... has remained elusive," said Boyden, who is a member of MIT's Media Lab and McGovern Institute for Brain Research.
"If we could really describe how diseases change molecules in specific cells within the living brain, it might enable better drug targets to be found."
Kodandaramaiah, Boyden and Forest set out to automate a 30-year-old technique known as whole-cell patch clamping, which 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.
Kodandaramaiah and his colleagues built a robotic arm that lowers a glass pipette into the brain of an anesthetized mouse with micrometer accuracy.
As it moves, the pipette monitors a property called electrical impedance - a measure of how difficult it is for electricity to flow out of the pipette. If there are no cells around, electricity flows and impedance is low. When the tip hits a cell, electricity can't flow as well and impedance goes up.
The pipette takes two-micrometer steps, measuring impedance 10 times per second. Once it detects a cell, it can stop instantly, preventing it from poking through the membrane.
"This is something a robot can do that a human can't," Boyden added.nce the pipette finds a cell, it applies suction to form a seal with the cell's membrane. Then, the electrode can break through the membrane to record the cell's internal electrical activity.
The robotic system can detect cells with 90 percent accuracy, and establish a connection with the detected cells about 40 percent of the time.
The researchers also showed that their method can be used to determine the shape of the cell by injecting a dye; they are now working on extracting a cell's contents to read its genetic profile.
The study has been published in Nature Methods.