Tel Aviv U. researchers define brain's neural hierarchy

MANHASSET, NY -- A research team at Tel Aviv University has developed a lab-on-a-chip that may help neuroscientists understand how neuronal networks communicate and work together.

The team has applied advanced mathematical and engineering techniques to connect neurons with electronics which they hope will let them understand how neuronal networks communicate.

The researchers wanted to see what is happening to well-defined neural circuits under different conditions by using engineered brain tissue in a Petri dish. They started to look for patterns in bigger networks of neurons, to see if there are any basic elements for information coding.

Using network engineering techniques, the scientists cultured different sized networks of neuronal clusters, which gave them results otherwise not predicted from what scientists know about single neurons.

The researchers were also able to measure patterns from nerve activity, at nodes where a number of nerves converged into networks. These neural networks have a hierarchical structure with large networks composed of smaller sub-networks. This observation, and a unique setup using electrodes and living nerves, allowed them to create hierarchical networks in a dish.

The brain's circuits work like codes. They can see the patterns in the networks and simplify them, or control connectivity between cells to see how the neuronal network responds to various chemicals and conditions, the scientists report.

One theory is that the human brain stores memories like a holograph of an image: small neural networks contain information about the whole brain, but only at a very low resolution.

So far the researchers are able to reveal that clusters of as few as 40 cells can serve as a minimal but sufficient functional network. This cluster is capable of sustaining neural network activity and communicating with other clusters.

The research was led by Mark Shein of Tel Aviv University's School of Electrical Engineering and his supervisors, prof. Yael Hanein of the School of Electrical Engineering and prof. Eshel Ben-Jacob of the School of Physics and Astronomy.

The team recently described the work in a recent issue of the journal PLoS ONE.