Skip to Content

Tracking Information Flow in the Brain

A tiny sensor that tracks calcium levels may one day provide clearer pictures of the brain at work.
October 12, 2006

Scientists at MIT have engineered a nano-sized calcium sensor that may eventually shed light on the intricate cell-to-cell communications that make up human thought. Alan Jasanoff and his team at the Francis Bitter Magnet Lab and McGovern Institute of Brain Research have found that tracking calcium, a key messenger in the brain, may be a more precise way of measuring neural activity, compared with current imaging techniques, such as traditional functional magnetic resonance imaging (fMRI).

When a neuron fires, it releases calcium. Alan Jasanoff at the McGovern Institute at MIT used this observation to develop a new way to visualize brain activity using fMRI. Superparamagnetic nanoparticles (illustrated here) are covered with proteins (red and green) that aggregate when calcium is released by the neuron. Aggregation of these particles can be detected by the MRI magnet.

FMRI uses powerful magnets to detect blood flow in the brain, allowing researchers to watch the human brain in action. Through a rapid series of snapshots, scientists can observe key areas of a person’s brain lighting up in response to a given task or command. The technology has been used to pinpoint the brain areas involved in everything from basic motor and verbal skills to murkier cognitive states like jealousy, deception, and morality.

Unfortunately, fMRI, as it is used today, has a major drawback: it measures blood flow, or hemodynamics, which is an indirect measure of neural cell activity. “It turns out hemodynamics basically introduces a delay of five seconds,” says Jasanoff. “It keeps you from being able to detect fast variation [in neural activity].”

Since neurons typically fire on the order of milliseconds, current fMRI techniques provide only a rough estimate of what the brain is doing at any given moment. FMRI scans also have a relatively low spatial resolution, measuring activity in areas of 100 microns, a volume that typically contains 10,000 neurons, each with varying activation patterns.

Efforts to fine-tune fMRI have focused on developing stronger magnets and a better understanding of blood flow and its relationship to brain activity.

But Jasanoff believes there’s a better, more precise way of tracking neural activity. He and his team are looking at calcium as a direct measure of neuronal firing. When a neuron sends an electrical impulse to another neuron, calcium-specific channels in the neuron’s membrane instantaneously open up, letting calcium flow into the cell. “It’s a very dramatic signal change,” says Jasanoff.

Fluorescent calcium sensors are already used in superficial optical imaging, but haven’t yet been applied to the deeper brain tissues that are accessible via the powerful magnets of fMRI machines. To that end, Jasanoff’s lab set about designing a calcium sensor that would be detectable via fMRI. To do this, they combined the sensor with a superparamagnetic iron oxide nanoparticle–essentially, a molecular-sized magnet that can be picked up by fMRI as high-contrast images.

The sensor itself is composed of two separate nanoparticles, each coated with a different protein: calmodulin and M13. In the presence of calcium, these two proteins bind together. “Essentially…we created two sets of Velcro balls,” says Jasanoff. “One has hooks and one has loops, and they only become Velcro balls in the presence of calcium.” The proteins come apart when calcium disappears, a property that might be useful in interpreting the flow of electrical activity in a circuit of neurons during a given task–something that’s not possible with today’s fMRI.

Jasanoff’s research is only a first step toward that goal. So far, he has tested the sensor in test-tube solutions with and without calcium, scanning the interactions with MRI. The initial results, published in a recent issue of the Proceedings of the National Academies of Sciences, are promising: scans were able to pick up high-contrast images of the Velcro-like balls clustering in the presence of calcium. Although the images were only visible after many seconds, or even minutes, Jasanoff says the sensor is highly tweakable, and he plans to improve its time response in future trials. For now, he plans to inject calcium sensors into single cells of flies and eventually rats.

Outsider observers like Greg Sorensen of Harvard Medical School are cautiously optimistic about this new generation of brain imaging, particularly for human applications. Sorensen, an associate professor of radiology, is focused on applying novel imaging techniques to the treatment of neurological diseases.

“Intracellular iron oxide particles have in some studies had an unfavorable safety profile in humans,” Sorensen says. “If we learned that this method had some risks but in exchange could identify the best treatment for, say, schizophrenia, then the risk may well be worth the benefit.”

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

Google’s Gemini is now in everything. Here’s how you can try it out.

Gmail, Docs, and more will now come with Gemini baked in. But Europeans will have to wait before they can download the app.

This baby with a head camera helped teach an AI how kids learn language

A neural network trained on the experiences of a single young child managed to learn one of the core components of language: how to match words to the objects they represent.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.