Electronic Chip Allows Synaptic Connectivity to Be Mapped at High Level

Scientists from Harvard University say they have developed an electronic chip that can perform high-sensitivity intracellular recording from thousands of connected neurons simultaneously. This advance (“A nanoelectrode array for obtaining intracellular recordings from thousands of connected neurons”), published in Nature Biomedical Engineering, allowed them to map synaptic connectivity at an unprecedented level, identifying hundreds of synaptic connections.

“Current electrophysiological or optical techniques cannot reliably perform simultaneous intracellular recordings from more than a few tens of neurons. Here we report a nanoelectrode array that can simultaneously obtain intracellular recordings from thousands of connected mammalian neurons in vitro. The array consists of 4,096 platinum-black electrodes with nanoscale roughness fabricated on top of a silicon chip that monolithically integrates 4,096 microscale amplifiers, configurable into pseudocurrent-clamp mode (for concurrent current injection and voltage recording) or into pseudovoltage-clamp mode (for concurrent voltage application and current recording),” the investigators wrote.

“We used the array in pseudovoltage-clamp mode to measure the effects of drugs on ion-channel currents. In pseudocurrent-clamp mode, the array intracellularly recorded action potentials and postsynaptic potentials from thousands of neurons. In addition, we mapped over 300 excitatory and inhibitory synaptic connections from more than 1,700 neurons that were intracellularly recorded for 19 minutes. This high-throughput intracellular-recording technology could benefit functional connectome mapping, electrophysiological screening, and other functional interrogations of neuronal networks.”

“Our combination of the sensitivity and parallelism can benefit fundamental and applied neurobiology alike, including functional connectome construction and high-throughput electrophysiological screening,” said Hongkun Park, PhD, the Mark Hyman Jr. professor of chemistry and professor of physics, and co-senior author of the paper.

“The mapping of the biological synaptic network enabled by this long sought-after parallelization of intracellular recording also can provide a new strategy for machine intelligence to build next-generation artificial neural network and neuromorphic processors,” added Donhee Ham, the Gordon McKay professor of applied physics and electrical engineering at the John A. Paulson School of Engineering and Applied Sciences (SEAS), and co-senior author of the paper.

The researchers developed the chip using the same fabrication technology as computer microprocessors. The chip features a dense array of vertically standing nanometer-scale electrodes on its surface, which are operated by the underlying integrated circuit. Coated with platinum powder, each nanoelectrode has a rough surface texture, which improves its ability to pass signals.

Neurons are cultured directly on the chip. The integrated circuit sends a current to each coupled neuron through the nanoelectrode to open tiny holes in its membrane, creating intracellular access. Simultaneously, the same integrated circuit also amplifies the voltage signals from the neuron picked up by the nanoelectrode through the holes.

“In this way, we combined the high sensitivity of intracellular recording and the parallelism of the modern electronic chip,” said Jeffrey Abbott, PhD, a postdoctoral fellow in the department of chemistry and chemical biology and SEAS, and the first author of the paper.

In experiments, the array intracellularly recorded more than 1,700 rat neurons. Twenty minutes of recording gave researchers a look at the neuronal network and allowed them to map more than 300 synaptic connections.

“We also used this high-throughput, high-precision chip to measure the effects of drugs on synaptic connections across the rat neuronal network, and now we are developing a wafer-scale system for high-throughput drug screening for neurological disorders such as schizophrenia, Parkinson’s disease, autism, Alzheimer’s disease, and addiction,” said Abbott.