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Nano multi-electrode detecting neuronal circuit activity

The rendering of the nano multi-electrode on the left and its electron microscope photograph. Credit: D. Schwartz et al./Nature Communications

In the quest to unravel the way the brain works (any brain, we can learn a lot from a mouse brain that applies to our own brain) researchers are looking for better and better ways to detect electrical signals exchanged by neurones. Indeed, the electrical activity is crucial to brain data processing. We know a lot on the way a single neurone processes an electrical stimulus and how this leads the neurones to generate other electrical stimuli towards many neurones it reaches through synaptic contacts.
We also know that neurones are organised in circuits, similarly to the way transistors are organised in circuits in a chip to perform a specific function. The problem with neural circuits is that it is much more difficult to isolate and therefore identify them. There are so many connections, in the order of a thousands per neurone (Purkinje neurones, found in the cerebellum, have up to hundred thousands synapses), that it gets mind boggling to follow the connections of a few hundreds neurones, such as those that may form a neuronal circuits (in case of transistors we may say that a hundred transistors forming a circuit do so through a hundred connections!).

It is even more complicated! Neurones that are connected not necessarily are part of the same functional circuit (unlike transistors). Hence, the map created by the Connectome project does not help in the identification of neuronal circuits (mind you: in order to be part of a neural circuit two neurones need to be connected one another or through a chain of other neurones, but two neurones that are connected are not necessarily involved in the processing of a signal – carry out a function).
In order to detect neuronal circuits you need to detect which neurones “fire” in response to a signal (a stimulus). And this requires detecting their electrical activity. The problem is finding a way to detect such activity with a good precision identifying the neurones involved.
Current probes (electrodes) can capture an electrical activity but the cannot pinpoint the source and it is not possibile to capture the activity of hundreds of neurones in parallel separating the activity of one from the other.

This is the issue that has been addressed by neuroscientists at the Francis Crick Institute by creating a nano probe called nanoengineered electroporation micro-electrodes, NEMs for short. You can see its shape in the picture. The tip of the probe is about 5µm thick and 30 µm in length. It accommodates some 20 “pores” detecting electromagnetic field. By analysing the different values of the field detected in the different pores the neuroscientists have been able to map the activity of the neural circuits processing olfactory stimuli in a mouse brain. That circuit consists of about 250 neurones that are contained in a space of 50µm, about the length of the probe tip.

The neuroscientists tested the NEM technique with a specific microcircuit, the olfactory bulb glomerulus (which detects smells). They were able to identify detailed, long-range, complex anatomical features (scale bar = 100 micrometers). Credit: D. Schwartz et al./Nature Communications

The next decade has been labelled “the decade of the brain”: the availability of new technologies, like this one, will help in the understanding the brain’s work at neuronal circuits level, a first step towards understanding the brain working as a whole.

About Roberto Saracco

Roberto Saracco fell in love with technology and its implications long time ago. His background is in math and computer science. Until April 2017 he led the EIT Digital Italian Node and then was head of the Industrial Doctoral School of EIT Digital up to September 2018. Previously, up to December 2011 he was the Director of the Telecom Italia Future Centre in Venice, looking at the interplay of technology evolution, economics and society. At the turn of the century he led a World Bank-Infodev project to stimulate entrepreneurship in Latin America. He is a senior member of IEEE where he leads the New Initiative Committee and co-chairs the Digital Reality Initiative. He is a member of the IEEE in 2050 Ad Hoc Committee. He teaches a Master course on Technology Forecasting and Market impact at the University of Trento. He has published over 100 papers in journals and magazines and 14 books.