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Biological memory chip hints at cyborg machines

Posted: 22 Nov 2007 ?? ?Print Version ?Bookmark and Share

Keywords:neuromemory chip? cyborg machine? electrical signal?

Researchers at Tel Aviv University in Israel are developing a hybrid biological-solid state memory that could be linked to conventional computer hardware to create cyborg machines.

The possibility of growing biological memory on silicon or glass substrates and making electrical connection to wires has been demonstrated before. The Israeli team has now demonstrated that networks of neurons cultured outside the brain can be imprinted with multiple rudimentary memories that persist for days without interfering with or wiping out others.

At present the electrical connections to the biological network are used for observation and measurement but a next stage could be to develop functioning biological networks that could interact with a conventional computer.

"The main achievement was the fact that we used the inhibition of the inhibitory neurons to stimulate the memory patterns," said physicist Eshel Ben-Jacob, senior author of a paper on the findings published in the May issue of Physical Review. "We probably made [the cell culture] trigger the collective mode of activity that... [is]...possible."

'Flawed' experiments
Ben-Jacob said that previous attempts to imprint memories on brain cell culturesneurons along with their supporting and insulating glial cellshave often involved stimulating the synapsesnerve cell connections. The so-called excitatory neurons, which amplify brain activity, account for nearly 80 percent of the neurons in the brain; while inhibitory neurons, which dampen activity, make up the remaining 20 percent. Stimulating excitatory cells with chemicals or electric pulses causes them to fire, or to send electrical signals of their own to neighboring neurons.

In addition, previous attempts to trigger the cells to create a repeating pattern of signals sent from neuron to neuron in a population, which neuroscientists believe constitutes the formation of a memory in the context of performing a task, focused on excitatory neurons. These experiments were flawed because they resulted in randomly escalating activity that does not mimic what occurs when new information is learned, Ben-Jabob said.

Different approach
In this research, Ben-Jacob and graduate student Itay Baruchi, who led the study, targeted inhibitory neurons to try to bring some order to their neural network. They mounted the cell culture on a polymer panel studded with electrodes, which enabled Ben-Jacob and Baruchi to monitor the patterns created by firing neurons. All of the cells on the electrode array came from the cortex, the outermost layer of the brain known for its role in memory formation.

Initially, when a group of neurons is clustered in a network, merely linking them will cause a spontaneous pattern of activity. Ben-Jacob and Baruchi sought to imprint a memory by injecting a chemical suppressor into a synapse between inhibitory neurons. Their goal: to disrupt the restrictive function of those cells, essentially causing the brakes they put on the excitatory members in the network to loosen.

"This is like teaching by liberation," Ben-Jacob says. "We liberate the excitatory neurons to do what they want to do."

Other neurons in the culture began to fire one by one as they received an electrical signal from one of their neighbors. This continued in the same pattern, which repeated for over a day. This new sequence of activity coexisted with the electrical pattern that was spontaneously generated when the neural culture was initially linked.

A day later, they imprinted a third pattern starting at a different inhibitory synapse. Again, it was able to coexist with the other motifs. "The surprising thing is it doesn't affect the other patterns that the network had before," said Ben-Jacob.

"These findings hint chemical signaling mechanisms might play a crucial role in memory and learning in task performing in vivo networks," the authors said.

- Amir Ben-Artzi
EE Times




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