What Should Systems Neuroscience Do Next? Voltage Imaging
By: Mark Humphries
Tags: Neuroscience, Psychology, Artificial Intelligence, Machine Learning, Science

What Should Systems Neuroscience Do Next? Voltage Imaging

The firing and the wiring at the same time

Credit: Pixabay

The best thing about being a neuroscientist is that neuroscience never stands still. Barely a week passes without some new major result, a sparkling technological breakthrough, a provoking theoretical idea. And the sheer complexity of brains means the questions available are practically infinite. So even if your specific corners of brain research have briefly slowed their breathless pace, there is always more to learn. Always new questions to tackle. Indeed, there are whole regions of the mammalian brain whose mysteries have barely been probed, and which will no doubt turn out to be crucial for our understanding. My money’s on the zona incerta, the globus pallidus, and the septum. Exciting times.

The worst thing about being a neuroscientist is that neuroscience never stands still. Barely a week passes without some new result, breakthrough, or theory that you don’t have time to read; that ends up filed for later, destined never to be opened; or to be skimmed and not assimilated. And the sheer complexity of brains means the questions available are practically infinite. So even if you’re lucky enough that your specific corners of brain research have briefly slowed their breathless pace, there is always more to learn. Always new questions to tackle. Indeed, there are whole regions of the mammalian brain whose mysteries have barely been probed, and which will no doubt turn out to be crucial for our understanding. Worrying times.

Paradoxically, this best and worst of all possible worlds in mind research is created by mindless churn. Of doing whatever can or could be done next. Not what should be done next. So, hubristically, I thought I’d plant my feet against the torrent and take a stab at separating the should from the could. A series of occasional pieces that set out to answer the question: what should systems neuroscience do next?

In this first piece, we start with the very definition of systems neuroscience. It is at heart the study of the activity of multiple individual neurons, of the messages they are sending. Everything we see, do, or think in the moment is through neurons sending spikes to each other. So a clear priority for systems neuroscience is to make the best recordings of the output of the most neurons, and with as much metadata about those neurons — where they are, how many there are, what type they are — as possible.

We have two mainstream ways of recording the output of individual neurons: insert electrodes to record spikes, or image calcium fluxes in the neurons’ bodies as a proxy for spikes. Both have unique strengths, both are constantly evolving in the white-heat of technology (and cash), but both have problems that are solved by the other. So our first “should”: we should find a recording method that combines the strengths of both. The great news is that we already know the answer. The answer is voltage imaging.

And if we get it solved, voltage imaging comes with a massive bonus prize, something neither electrodes nor calcium imaging can buy us: live connectomics.