Researcher: Alan Jasanoff

Reevaluating an approach to functional brain imaging

by Jennifer Michalowski |

A new way of imaging the brain with magnetic resonance imaging (MRI) does not directly detect neural activity as originally reported, according to scientists at MIT’s McGovern Institute. The method, first described in 2022, generated excitement within the neuroscience community as a potentially transformative approach. But a study from the lab of McGovern Associate Investigator Alan Jasanoff, reported March 27, 2024, in the journal Science Advances, demonstrates that MRI signals produced by the new method are generated in large part by the imaging process itself, not neuronal activity.

A man stands with his arms crossed in front of a board with mathematical equations written on it.
Alan Jasanoff, associate member of the McGovern Institute, and a professor of brain and cognitive sciences, biological engineering, and nuclear science and engineering at MIT. Photo: Justin Knight

Jasanoff explains that having a noninvasive means of seeing neuronal activity in the brain is a long-sought goal for neuroscientists. The functional MRI methods that researchers currently use to monitor brain activity don’t actually detect neural signaling. Instead, they use blood flow changes triggered by brain activity as a proxy. This reveals which parts of the brain are engaged during imaging, but it cannot pinpoint neural activity to precise locations, and it is too slow to truly track neurons’ rapid-fire communications.

So when a team of scientists reported in Science a new MRI method called DIANA, for “direct imaging of neuronal activity,” neuroscientists paid attention. The authors claimed that DIANA detected MRI signals in the brain that corresponded to the electrical signals of neurons, and that it acquired signals far faster than the methods now used for functional MRI.

“Everyone wants this,” Jasanoff says. “If we could look at the whole brain and follow its activity with millisecond precision and know that all the signals that we’re seeing have to do with cellular activity, this would be just wonderful. It could tell us all kinds of things about how the brain works and what goes wrong in disease.”

Jasanoff adds that from the initial report, it was not clear what brain changes DIANA was detecting to produce such a rapid readout of neural activity. Curious, he and his team began to experiment with the method. “We wanted to reproduce it, and we wanted to understand how it worked,” he says.

Decoding DIANA

Recreating the MRI procedure reported by DIANA’s developers, postdoctoral researcher Valerie Doan Phi Van imaged the brain of a rat as an electric stimulus was delivered to one paw. Phi Van says she was excited to see an MRI signal appear in the brain’s sensory cortex, exactly when and where neurons were expected to respond to the sensation on the paw. “I was able to reproduce it,” she says. “I could see the signal.”

With further tests of the system, however, her enthusiasm waned. To investigate the source of the signal, she disconnected the device used to stimulate the animal’s paw, then repeated the imaging. Again, signals showed up in the sensory processing part of the brain. But this time, there was no reason for neurons in that area to be activated. In fact, Phi Van found, the MRI produced the same kinds of signals when the animal inside the scanner was replaced with a tube of water. It was clear DIANA’s functional signals were not arising from neural activity.

Phi Van traced the source of the specious signals to the pulse program that directs DIANA’s imaging process, detailing the sequence of steps the MRI scanner uses to collect data. Embedded within DIANA’s pulse program was a trigger for the device that delivers sensory input to the animal inside the scanner. That synchronizes the two processes, so the stimulation occurs at a precise moment during data acquisition. That trigger appeared to be causing signals that DIANA’s developers had concluded indicated neural activity.

It was clear DIANA’s functional signals were not arising from neural activity.

Phi Van altered the pulse program, changing the way the stimulator was triggered. Using the updated program, the MRI scanner detected no functional signal in the brain in response to the same paw stimulation that had produced a signal before. “If you take this part of the code out, then the signal will also be gone. So that means the signal we see is an artifact of the trigger,” she says.

Jasanoff and Phi Van went on to find reasons why other researchers have struggled to reproduce the results of the original DIANA report, noting that the trigger-generated signals can disappear with slight variations in the imaging process. With their postdoctoral colleague Sajal Sen, they also found evidence that cellular changes that DIANA’s developers had proposed might give rise to a functional MRI signal were not related to neuronal activity.

Jasanoff and Phi Van say it was important to share their findings with the research community, particularly as efforts continue to develop new neuroimaging methods. “If people want to try to repeat any part of the study or implement any kind of approach like this, they have to avoid falling into these pits,” Jasanoff says. He adds that they admire the authors of the original study for their ambition: “The community needs scientists who are willing to take risks to move the field ahead.”

Nature: An unexpected source of innovative tools to study the brain

by Jennifer Michalowski |

This story originally appeared in the Fall 2023 issue of BrainScan.

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Scientist holds 3D printed phage over a natural background.
Genetic engineer Joseph Kreitz looks to the microscopic world for inspiration in Feng Zhang’s lab at the McGovern Institute. Photo: Steph Steve

In their quest to deepen their understanding of the brain, McGovern scientists take inspiration wherever it comes — and sometimes it comes from surprising sources. To develop new tools for research and innovative strategies for treating disease, they’ve drawn on proteins that organisms have been making for billions of years as well as sophisticated materials engineered for modern technology.

For McGovern investigator Feng Zhang, the natural world provides a rich source of molecules with remarkable and potentially useful functions.

Zhang is one of the pioneers of CRISPR, a programmable system for gene editing that is built from the components of a bacterial adaptive immune system. Scientists worldwide use CRISPR to modify genetic sequences in their labs, and many CRISPR-based therapies, which aim to treat disease through gene editing, are now in development. Meanwhile, Zhang and his team have continued to explore CRISPR-like systems beyond the bacteria in which they were originally discovered.

Turning to nature

This year, the search for evolutionarily related systems led Zhang’s team to a set of enzymes made by more complex organisms, including single-celled algae and hard-shell clams. Like the enzymes that power CRISPR, these newly discovered enzymes, called Fanzors, can be directed to cut DNA at specific sites by programming an RNA molecule as a guide.

Rhiannon Macrae, a scientific advisor in Zhang’s lab, says the discovery was surprising because Fanzors don’t seem to play the same role in immunity that CRISPR systems do. In fact, she says it’s not clear what Fanzors do at all. But as programmable gene editors, Fanzors might have an important advantage over current CRISPR tools — particularly for clinical applications. “Fanzor proteins are much smaller than the workhorse CRISPR tool, Cas9,” Macrae says. “This really matters when you actually want to be able to use one of these tools in a patient, because the bigger the tool, the harder it is to package and deliver to patients’ cells.”

Cryo-EM map of a Fanzor protein (gray, yellow, light blue, and pink) in complex with ωRNA (purple) and its target DNA (red). Non-target DNA strand in blue. Image: Zhang lab

Zhang’s team has thought a lot about how to get therapies to patients’ cells, and size is only one consideration. They’ve also been looking for ways to direct drugs, gene-editing tools, or other therapies to specific cells and tissues in the body. One of the lab’s leading strategies comes from another unexpected natural source: a microscopic syringe produced by certain insect-infecting bacteria.

In their search for an efficient system for targeted drug delivery, Zhang and graduate student Joseph Kreitz first considered the injection systems of bacteria-infecting viruses: needle-like structures that pierce the outer membrane of their host to deliver their own genetic material. But these viral injection systems can’t easily be freed from the rest of the virus.

Then Zhang learned that some bacteria have injection systems of their own, which they release inside their hosts after packing them with toxins. They reengineered the bacterial syringe, devising a delivery system that works on human cells. Their current system can be programmed to inject proteins — including those used for gene editing — directly into specified cell types. With further development, Zhang hopes it will work with other types of therapies, as well.

Magnetic imaging

In McGovern Associate Investigator Alan Jasanoff’s lab, researchers are designing sensors that can track the activity of specific neurons or molecules in the brain, using magnetic resonance imaging (MRI) or related forms of non-invasive imaging. These tools are essential for understanding how the brain’s cells and circuits work together to process information. “We want to give MRI a suite of metaphorical colors: sensitivities that enable us to dissect the different kinds of mechanistically significant contributors to neural activity,” he explains.

Jasanoff can tick off a list of molecules with notable roles in biology and industry that his lab has repurposed to glean more information from brain imaging. These include manganese — a metal once used to tint ancient glass; nitric oxide synthase — the enzyme that causes blushing; and iron oxide nanoparticles — tiny magnets that enable compact data storage inside computers. But Jasanoff says none of these should be considered out of place in the imaging world. “Most are pretty logical choices,” he says. “They all do different things and we use them in pretty different ways, but they are either magnetic or interact with magnetic molecules to serve our purposes for brain imaging.”

Close-up picture of manganese metal
Manganese, a metal that interacts weakly with magnetic fields, is a key component in new MRI sensors being developed in Alan Jasanoff’s lab at the McGovern Institute.

The enzyme nitric oxide synthase, for example, plays an important role in most functional MRI scans. The enzyme produces nitric oxide, which causes blood vessels to expand. This can bring a blush to the cheeks, but in the brain, it increases blood flow to bring more oxygen to busy neurons. MRI can detect this change because it is sensitive to the magnetic properties of blood.

By using blood flow as a proxy for neural activity, functional MRI scans light up active regions of the brain, but they can’t pinpoint the activity of specific cells. So Jasanoff and his team devised a more informative MRI sensor by reengineering nitric oxide synthase. Their modified enzyme, which they call NOSTIC, can be introduced into a select group of cells, where it will produce nitric oxide in response to neural activity — triggering increased blood flow and strengthening the local MRI signal. Researchers can deliver it to specific kinds of brain cells, or they can deliver it exclusively to neurons that communicate directly with one another. Then they can watch for an elevated MRI signal when those cells fire. This lets them see how information flows through the brain and tie specific cells to particular tasks.

Miranda Dawson, a graduate student in Jasanoff’s lab, is using NOSTIC to study the brain circuits that fuel addiction. She’s interested in the involvement of a brain region called the insula, which may mediate the physical sensations that people with addiction experience during drug cravings or withdrawal. With NOSTIC, Dawson can follow how the insula communicates to other parts of the brain as a rat experiences these MITstages of addiction. “We give our sensor to the insula, and then it projects to anatomically connected brain regions,” she explains. “So we’re able to delineate what circuits are being activated at different points in the addiction cycle.”

Scientist with folded arms next to a picture of a brain
Miranda Dawson uses her lab’s novel MRI sensor, NOSTIC, to illuminate the brain circuits involved in fentanyl craving and withdrawal. Photo: Steph Stevens; MRI scan: Nan Li, Souparno Ghosh, Jasanoff lab

Mining biodiversity

McGovern investigators know that good ideas and useful tools can come from anywhere. Sometimes, the key to harnessing those tools is simply recognizing their potential. But there are also opportunities for a more deliberate approach to finding them.

McGovern Investigator Ed Boyden is leading a program that aims to accelerate the discovery of valuable natural products. Called the Biodiversity Network (BioNet), the project is collecting biospecimens from around the world and systematically analyzing them, looking for molecular tools that could be applied to major challenges in science and medicine, from brain research to organ preservation. “The idea behind BioNet,” Boyden explains, “is rather than wait for chance to give us these discoveries, can we go look for them on purpose?”

New sensor uses MRI to detect light deep in the brain

Anne Trafton |

Using a specialized MRI sensor, MIT researchers have shown that they can detect light deep within tissues such as the brain.

Imaging light in deep tissues is extremely difficult because as light travels into tissue, much of it is either absorbed or scattered. The MIT team overcame that obstacle by designing a sensor that converts light into a magnetic signal that can be detected by MRI (magnetic resonance imaging).

This type of sensor could be used to map light emitted by optical fibers implanted in the brain, such as the fibers used to stimulate neurons during optogenetic experiments. With further development, it could also prove useful for monitoring patients who receive light-based therapies for cancer, the researchers say.

“We can image the distribution of light in tissue, and that’s important because people who use light to stimulate tissue or to measure from tissue often don’t quite know where the light is going, where they’re stimulating, or where the light is coming from. Our tool can be used to address those unknowns,” says Alan Jasanoff, an MIT professor of biological engineering, brain and cognitive sciences, and nuclear science and engineering.

Jasanoff, who is also an associate investigator at MIT’s McGovern Institute for Brain Research, is the senior author of the study, which appears today in Nature Biomedical Engineering. Jacob Simon PhD ’21 and MIT postdoc Miriam Schwalm are the paper’s lead authors, and Johannes Morstein and Dirk Trauner of New York University are also authors of the paper.

A light-sensitive probe

Scientists have been using light to study living cells for hundreds of years, dating back to the late 1500s, when the light microscope was invented. This kind of microscopy allows researchers to peer inside cells and thin slices of tissue, but not deep inside an organism.

“One of the persistent problems in using light, especially in the life sciences, is that it doesn’t do a very good job penetrating many materials,” Jasanoff says. “Biological materials absorb light and scatter light, and the combination of those things prevents us from using most types of optical imaging for anything that involves focusing in deep tissue.”

To overcome that limitation, Jasanoff and his students decided to design a sensor that could transform light into a magnetic signal.

“We wanted to create a magnetic sensor that responds to light locally, and therefore is not subject to absorbance or scattering. Then this light detector can be imaged using MRI,” he says.

Jasanoff’s lab has previously developed MRI probes that can interact with a variety of molecules in the brain, including dopamine and calcium. When these probes bind to their targets, it affects the sensors’ magnetic interactions with the surrounding tissue, dimming or brightening the MRI signal.

To make a light-sensitive MRI probe, the researchers decided to encase magnetic particles in a nanoparticle called a liposome. The liposomes used in this study are made from specialized light-sensitive lipids that Trauner had previously developed. When these lipids are exposed to a certain wavelength of light, the liposomes become more permeable to water, or “leaky.” This allows the magnetic particles inside to interact with water and generate a signal detectable by MRI.

The particles, which the researchers called liposomal nanoparticle reporters (LisNR), can switch from permeable to impermeable depending on the type of light they’re exposed to. In this study, the researchers created particles that become leaky when exposed to ultraviolet light, and then become impermeable again when exposed to blue light. The researchers also showed that the particles could respond to other wavelengths of light.

“This paper shows a novel sensor to enable photon detection with MRI through the brain. This illuminating work introduces a new avenue to bridge photon and proton-driven neuroimaging studies,” says Xin Yu, an assistant professor radiology at Harvard Medical School, who was not involved in the study.

Mapping light

The researchers tested the sensors in the brains of rats — specifically, in a part of the brain called the striatum, which is involved in planning movement and responding to reward. After injecting the particles throughout the striatum, the researchers were able to map the distribution of light from an optical fiber implanted nearby.

The fiber they used is similar to those used for optogenetic stimulation, so this kind of sensing could be useful to researchers who perform optogenetic experiments in the brain, Jasanoff says.

“We don’t expect that everybody doing optogenetics will use this for every experiment — it’s more something that you would do once in a while, to see whether a paradigm that you’re using is really producing the profile of light that you think it should be,” Jasanoff says.

In the future, this type of sensor could also be useful for monitoring patients receiving treatments that involve light, such as photodynamic therapy, which uses light from a laser or LED to kill cancer cells.

The researchers are now working on similar probes that could be used to detect light emitted by luciferases, a family of glowing proteins that are often used in biological experiments. These proteins can be used to reveal whether a particular gene is activated or not, but currently they can only be imaged in superficial tissue or cells grown in a lab dish.

Jasanoff also hopes to use the strategy used for the LisNR sensor to design MRI probes that can detect stimuli other than light, such as neurochemicals or other molecules found in the brain.

“We think that the principle that we use to construct these sensors is quite broad and can be used for other purposes too,” he says.

The research was funded by the National Institutes of Health, the G. Harold and Leila Y. Mathers Foundation, a Friends of the McGovern Fellowship from the McGovern Institute for Brain Research, the MIT Neurobiological Engineering Training Program, and a Marie Curie Individual Fellowship from the European Commission.

New MRI probe can reveal more of the brain’s inner workings

Anne Trafton |

Using a novel probe for functional magnetic resonance imaging (fMRI), MIT biological engineers have devised a way to monitor individual populations of neurons and reveal how they interact with each other.

Similar to how the gears of a clock interact in specific ways to turn the clock’s hands, different parts of the brain interact to perform a variety of tasks, such as generating behavior or interpreting the world around us. The new MRI probe could potentially allow scientists to map those networks of interactions.

“With regular fMRI, we see the action of all the gears at once. But with our new technique, we can pick up individual gears that are defined by their relationship to the other gears, and that’s critical for building up a picture of the mechanism of the brain,” says Alan Jasanoff, an MIT professor of biological engineering, brain and cognitive sciences, and nuclear science and engineering.

Using this technique, which involves genetically targeting the MRI probe to specific populations of cells in animal models, the researchers were able to identify neural populations involved in a circuit that responds to rewarding stimuli. The new MRI probe could also enable studies of many other brain circuits, the researchers say.

Jasanoff, who is also an associate investigator at the McGovern Institute, is the senior author of the study, which appears today in Nature Neuroscience. The lead authors of the paper are recent MIT PhD recipient Souparno Ghosh and former MIT research scientist Nan Li.

Tracing connections

Traditional fMRI imaging measures changes to blood flow in the brain, as a proxy for neural activity. When neurons receive signals from other neurons, it triggers an influx of calcium, which causes a diffusible gas called nitric oxide to be released. Nitric oxide acts in part as a vasodilator that increases blood flow to the area.

Imaging calcium directly can offer a more precise picture of brain activity, but that type of imaging usually requires fluorescent chemicals and invasive procedures. The MIT team wanted to develop a method that could work across the brain without that type of invasiveness.

“If we want to figure out how brain-wide networks of cells and brain-wide mechanisms function, we need something that can be detected deep in tissue and preferably across the entire brain at once,” Jasanoff says. “The way that we chose to do that in this study was to essentially hijack the molecular basis of fMRI itself.”

The researchers created a genetic probe, delivered by viruses, that codes for a protein that sends out a signal whenever the neuron is active. This protein, which the researchers called NOSTIC (nitric oxide synthase for targeting image contrast), is an engineered form of an enzyme called nitric oxide synthase. The NOSTIC protein can detect elevated calcium levels that arise during neural activity; it then generates nitric oxide, leading to an artificial fMRI signal that arises only from cells that contain NOSTIC.

The probe is delivered by a virus that is injected into a particular site, after which it travels along axons of neurons that connect to that site. That way, the researchers can label every neural population that feeds into a particular location.

“When we use this virus to deliver our probe in this way, it causes the probe to be expressed in the cells that provide input to the location where we put the virus,” Jasanoff says. “Then, by performing functional imaging of those cells, we can start to measure what makes input to that region take place, or what types of input arrive at that region.”

Turning the gears

In the new study, the researchers used their probe to label populations of neurons that project to the striatum, a region that is involved in planning movement and responding to reward. In rats, they were able to determine which neural populations send input to the striatum during or immediately following a rewarding stimulus — in this case, deep brain stimulation of the lateral hypothalamus, a brain center that is involved in appetite and motivation, among other functions.

One question that researchers have had about deep brain stimulation of the lateral hypothalamus is how wide-ranging the effects are. In this study, the MIT team showed that several neural populations, located in regions including the motor cortex and the entorhinal cortex, which is involved in memory, send input into the striatum following deep brain stimulation.

“It’s not simply input from the site of the deep brain stimulation or from the cells that carry dopamine. There are these other components, both distally and locally, that shape the response, and we can put our finger on them because of the use of this probe,” Jasanoff says.

During these experiments, neurons also generate regular fMRI signals, so in order to distinguish the signals that are coming specifically from the genetically altered neurons, the researchers perform each experiment twice: once with the probe on, and once following treatment with a drug that inhibits the probe. By measuring the difference in fMRI activity between these two conditions, they can determine how much activity is present in probe-containing cells specifically.

The researchers now hope to use this approach, which they call hemogenetics, to study other networks in the brain, beginning with an effort to identify some of the regions that receive input from the striatum following deep brain stimulation.

“One of the things that’s exciting about the approach that we’re introducing is that you can imagine applying the same tool at many sites in the brain and piecing together a network of interlocking gears, which consist of these input and output relationships,” Jasanoff says. “This can lead to a broad perspective on how the brain works as an integrated whole, at the level of neural populations.”

The research was funded by the National Institutes of Health and the MIT Simons Center for the Social Brain.

The craving state

by Jennifer Michalowski |

This story originally appeared in the Winter 2022 issue of BrainScan.

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For people struggling with substance use disorders — and there are about 35 million of them worldwide — treatment options are limited. Even among those who seek help, relapse is common. In the United States, an epidemic of opioid addiction has been declared a public health emergency.

A 2019 survey found that 1.6 million people nationwide had an opioid use disorder, and the crisis has surged since the start of the COVID-19 pandemic. The Centers for Disease Control and Prevention estimates that more than 100,000 people died of drug overdose between April 2020 and April 2021 — nearly 30 percent more overdose deaths than occurred during the same period the previous year.

In the United States, an epidemic of opioid addiction has been declared a public health emergency.

A deeper understanding of what addiction does to the brain and body is urgently needed to pave the way to interventions that reliably release affected individuals from its grip. At the McGovern Institute, researchers are turning their attention to addiction’s driving force: the deep, recurring craving that makes people prioritize drug use over all other wants and needs.

McGovern Institute co-founder, Lore Harp McGovern.

“When you are in that state, then it seems nothing else matters,” says McGovern Investigator Fan Wang. “At that moment, you can discard everything: your relationship, your house, your job, everything. You only want the drug.”

With a new addiction initiative catalyzed by generous gifts from Institute co-founder Lore Harp McGovern and others, McGovern scientists with diverse expertise have come together to begin clarifying the neurobiology that underlies the craving state. They plan to dissect the neural transformations associated with craving at every level — from the drug-induced chemical changes that alter neuronal connections and activity to how these modifications impact signaling brain-wide. Ultimately, the McGovern team hopes not just to understand the craving state, but to find a way to relieve it — for good.

“If we can understand the craving state and correct it, or at least relieve a little bit of the pressure,” explains Wang, who will help lead the addiction initiative, “then maybe we can at least give people a chance to use their top-down control to not take the drug.”

The craving cycle

For individuals suffering from substance use disorders, craving fuels a cyclical pattern of escalating drug use. Following the euphoria induced by a drug like heroin or cocaine, depression sets in, accompanied by a drug craving motivated by the desire to relieve that suffering. And as addiction progresses, the peaks and valleys of this cycle dip lower: the pleasant feelings evoked by the drug become weaker, while the negative effects a person experiences in its absence worsen. The craving remains, and increasing use of the drug are required to relieve it.

By the time addiction sets in, the brain has been altered in ways that go beyond a drug’s immediate effects on neural signaling.

These insidious changes leave individuals susceptible to craving — and the vulnerable state endures. Long after the physical effects of withdrawal have subsided, people with substance use disorders can find their craving returns, triggered by exposure to a small amount of the drug, physical or social cues associated with previous drug use, or stress. So researchers will need to determine not only how different parts of the brain interact with one another during craving and how individual cells and the molecules within them are affected by the craving state — but also how things change as addiction develops and progresses.

Circuits, chemistry and connectivity

One clear starting point is the circuitry the brain uses to control motivation. Thanks in part to decades of research in the lab of McGovern Investigator Ann Graybiel, neuroscientists know a great deal about how these circuits learn which actions lead to pleasure and which lead to pain, and how they use that information to establish habits and evaluate the costs and benefits of complex decisions.

Graybiel’s work has shown that drugs of abuse strongly activate dopamine-responsive neurons in a part of the brain called the striatum, whose signals promote habit formation. By increasing the amount of dopamine that neurons release, these drugs motivate users to prioritize repeated drug use over other kinds of rewards, and to choose the drug in spite of pain or other negative effects. Her group continues to investigate the naturally occurring molecules that control these circuits, as well as how they are hijacked by drugs of abuse.

Distribution of opioid receptors targeted by morphine (shown in blue) in two regions in the dorsal striatum and nucleus accumbens of the mouse brain. Image: Ann Graybiel

In Fan Wang’s lab, work investigating the neural circuits that mediate the perception of physical pain has led her team to question the role of emotional pain in craving. As they investigated the source of pain sensations in the brain, they identified neurons in an emotion-regulating center called the central amygdala that appear to suppress physical pain in animals. Now, Wang wants to know whether it might be possible to modulate neurons involved in emotional pain to ameliorate the negative state that provokes drug craving.

These animal studies will be key to identifying the cellular and molecular changes that set the brain up for recurring cravings. And as McGovern scientists begin to investigate what happens in the brains of rodents that have been trained to self-administer addictive drugs like fentanyl or cocaine, they expect to encounter tremendous complexity.

McGovern Associate Investigator Polina Anikeeva, whose lab has pioneered new technologies that will help the team investigate the full spectrum of changes that underlie craving, says it will be important to consider impacts on the brain’s chemistry, firing patterns, and connectivity. To that end, multifunctional research probes developed in her lab will be critical to monitoring and manipulating neural circuits in animal models.

Imaging technology developed by investigator Ed Boyden will also enable nanoscale protein visualization brain-wide. An important goal will be to identify a neural signature of the craving state. With such a signal, researchers can begin to explore how to shut off that craving — possibly by directly modulating neural signaling.

Targeted treatments

“One of the reasons to study craving is because it’s a natural treatment point,” says McGovern Associate Investigator Alan Jasanoff. “And the dominant kind of approaches that people in our team think about are approaches that relate to neural circuits — to the specific connections between brain regions and how those could be changed.” The hope, he explains, is that it might be possible to identify a brain region whose activity is disrupted during the craving state, then use clinical brain stimulation methods to restore normal signaling — within that region, as well as in other connected parts of the brain.

To identify the right targets for such a treatment, it will be crucial to understand how the biology uncovered in laboratory animals reflects what’s happens in people with substance use disorders. Functional imaging in John Gabrieli’s lab can help bridge the gap between clinical and animal research by revealing patterns of brain activity associated with the craving state in both humans and rodents. A new technique developed in Jasanoff’s lab makes it possible to focus on the activity between specific regions of an animal’s brain. “By doing that, we hope to build up integrated models of how information passes around the brain in craving states, and of course also in control states where we’re not experiencing craving,” he explains.

In delving into the biology of the craving state, McGovern scientists are embarking on largely unexplored territory — and they do so with both optimism and urgency. “It’s hard to not appreciate just the size of the problem, and just how devastating addiction is,” says Anikeeva. “At this point, it just seems almost irresponsible to not work on it, especially when we do have the tools and we are interested in the general brain regions that are important for that problem. I would say that there’s almost a civic duty.”

Two MIT Brain and Cognitive Sciences faculty members earn funding from the G. Harold and Leila Y. Mathers Foundation

by David Orenstein |

Two MIT neuroscientists have received grants from the G. Harold and Leila Y. Mathers Foundation to screen for genes that could help brain cells withstand Parkinson’s disease and to map how gene expression changes in the brain in response to drugs of abuse.

Myriam Heiman, an associate professor in MIT’s Department of Brain and Cognitive Sciences and a core member of the Picower Institute for Learning and Memory and the Broad Institute of MIT and Harvard, and Alan Jasanoff, who is also a professor in biological engineering, brain and cognitive sciences, nuclear science and engineering and an associate investigator at the McGovern Institute for Brain Research, each received three-year awards that formally begin January 1, 2021.

Jasanoff, who also directs MIT’s Center for Neurobiological Engineering, is known for developing sensors that monitor molecular hallmarks of neural activity in the living brain, in real time, via noninvasive MRI brain scanning. One of the MRI-detectable sensors that he has developed is for dopamine, a neuromodulator that is key to learning what behaviors and contexts lead to reward. Addictive drugs artificially drive dopamine release, thereby hijacking the brain’s reward prediction system. Studies have shown that dopamine and drugs of abuse activate gene transcription in specific brain regions, and that this gene expression changes as animals are repeatedly exposed to drugs. Despite the important implications of these neuroplastic changes for the process of addiction, in which drug-seeking behaviors become compulsive, there are no effective tools available to measure gene expression across the brain in real time.

Cerebral vasculature in mouse brain. The Jasanoff lab hopes to develop a method for mapping gene expression the brain with related labeling characteristics .
Image: Alan Jasanoff

With the new Mathers funding, Jasanoff is developing new MRI-detectable sensors for gene expression. With these cutting-edge tools, Jasanoff proposes to make an activity atlas of how the brain responds to drugs of abuse, both upon initial exposure and over repeated doses that simulate the experiences of drug addicted individuals.

“Our studies will relate drug-induced brain activity to longer term changes that reshape the brain in addiction,” says Jasanoff. “We hope these studies will suggest new biomarkers or treatments.”

Dopamine-producing neurons in a brain region called the substantia nigra are known to be especially vulnerable to dying in Parkinson’s disease, leading to the severe motor difficulties experienced during the progression of the incurable, chronic neurodegenerative disorder. The field knows little about what puts specific cells at such dire risk, or what molecular mechanisms might help them resist the disease. In her research on Huntington’s disease, another incurable neurodegenerative disorder in which a specific neuron population in the striatum is especially vulnerable, Heiman has been able to use an innovative method her lab pioneered to discover genes whose expression promotes neuron survival, yielding potential new drug targets. The technique involves conducting an unbiased screen in which her lab knocks out each of the 22,000 genes expressed in the mouse brain one by one in neurons in disease model mice and healthy controls. The technique allows her to determine which genes, when missing, contribute to neuron death amid disease and therefore which genes are particularly needed for survival. The products of those genes can then be evaluated as drug targets. With the new Mathers award, Heiman plans to apply the method to study Parkinson’s disease.

An immunofluorescence image taken in a brain region called the substantia nigra (SN) highlights tyrosine hydroxylase, a protein expressed by dopamine neurons. This type of neuron in the SN is especially vulnerable to neurodegeneration in Parkinson’s disease. Image: Preston Ge/Heiman Lab

“There is currently no molecular explanation for the brain cell loss seen in Parkinson’s disease or a cure for this devastating disease,” Heiman said. “This award will allow us to perform unbiased, genome-wide genetic screens in the brains of mouse models of Parkinson’s disease, probing for genes that allow brain cells to survive the effects of cellular perturbations associated with Parkinson’s disease. I’m extremely grateful for this generous support and recognition of our work from the Mathers Foundation, and hope that our study will elucidate new therapeutic targets for the treatment and even prevention of Parkinson’s disease.”

How dopamine drives brain activity

Anne Trafton |

Using a specialized magnetic resonance imaging (MRI) sensor, MIT neuroscientists have discovered how dopamine released deep within the brain influences both nearby and distant brain regions.

Dopamine plays many roles in the brain, most notably related to movement, motivation, and reinforcement of behavior. However, until now it has been difficult to study precisely how a flood of dopamine affects neural activity throughout the brain. Using their new technique, the MIT team found that dopamine appears to exert significant effects in two regions of the brain’s cortex, including the motor cortex.

“There has been a lot of work on the immediate cellular consequences of dopamine release, but here what we’re looking at are the consequences of what dopamine is doing on a more brain-wide level,” says Alan Jasanoff, an MIT professor of biological engineering, brain and cognitive sciences, and nuclear science and engineering. Jasanoff is also an associate member of MIT’s McGovern Institute for Brain Research and the senior author of the study.

The MIT team found that in addition to the motor cortex, the remote brain area most affected by dopamine is the insular cortex. This region is critical for many cognitive functions related to perception of the body’s internal states, including physical and emotional states.

MIT postdoc Nan Li is the lead author of the study, which appears today in Nature.

Tracking dopamine

Like other neurotransmitters, dopamine helps neurons to communicate with each other over short distances. Dopamine holds particular interest for neuroscientists because of its role in motivation, addiction, and several neurodegenerative disorders, including Parkinson’s disease. Most of the brain’s dopamine is produced in the midbrain by neurons that connect to the striatum, where the dopamine is released.

For many years, Jasanoff’s lab has been developing tools to study how molecular phenomena such as neurotransmitter release affect brain-wide functions. At the molecular scale, existing techniques can reveal how dopamine affects individual cells, and at the scale of the entire brain, functional magnetic resonance imaging (fMRI) can reveal how active a particular brain region is. However, it has been difficult for neuroscientists to determine how single-cell activity and brain-wide function are linked.

“There have been very few brain-wide studies of dopaminergic function or really any neurochemical function, in large part because the tools aren’t there,” Jasanoff says. “We’re trying to fill in the gaps.”

About 10 years ago, his lab developed MRI sensors that consist of magnetic proteins that can bind to dopamine. When this binding occurs, the sensors’ magnetic interactions with surrounding tissue weaken, dimming the tissue’s MRI signal. This allows researchers to continuously monitor dopamine levels in a specific part of the brain.

In their new study, Li and Jasanoff set out to analyze how dopamine released in the striatum of rats influences neural function both locally and in other brain regions. First, they injected their dopamine sensors into the striatum, which is located deep within the brain and plays an important role in controlling movement. Then they electrically stimulated a part of the brain called the lateral hypothalamus, which is a common experimental technique for rewarding behavior and inducing the brain to produce dopamine.

Then, the researchers used their dopamine sensor to measure dopamine levels throughout the striatum. They also performed traditional fMRI to measure neural activity in each part of the striatum. To their surprise, they found that high dopamine concentrations did not make neurons more active. However, higher dopamine levels did make the neurons remain active for a longer period of time.

“When dopamine was released, there was a longer duration of activity, suggesting a longer response to the reward,” Jasanoff says. “That may have something to do with how dopamine promotes learning, which is one of its key functions.”

Long-range effects

After analyzing dopamine release in the striatum, the researchers set out to determine this dopamine might affect more distant locations in the brain. To do that, they performed traditional fMRI imaging on the brain while also mapping dopamine release in the striatum. “By combining these techniques we could probe these phenomena in a way that hasn’t been done before,” Jasanoff says.

The regions that showed the biggest surges in activity in response to dopamine were the motor cortex and the insular cortex. If confirmed in additional studies, the findings could help researchers understand the effects of dopamine in the human brain, including its roles in addiction and learning.

“Our results could lead to biomarkers that could be seen in fMRI data, and these correlates of dopaminergic function could be useful for analyzing animal and human fMRI,” Jasanoff says.

The research was funded by the National Institutes of Health and a Stanley Fahn Research Fellowship from the Parkinson’s Disease Foundation.

MRI sensor images deep brain activity

by Anne Trafton |

Calcium is a critical signaling molecule for most cells, and it is especially important in neurons. Imaging calcium in brain cells can reveal how neurons communicate with each other; however, current imaging techniques can only penetrate a few millimeters into the brain.

MIT researchers have now devised a new way to image calcium activity that is based on magnetic resonance imaging (MRI) and allows them to peer much deeper into the brain. Using this technique, they can track signaling processes inside the neurons of living animals, enabling them to link neural activity with specific behaviors.

“This paper describes the first MRI-based detection of intracellular calcium signaling, which is directly analogous to powerful optical approaches used widely in neuroscience but now enables such measurements to be performed in vivo in deep tissue,” says Alan Jasanoff, an MIT professor of biological engineering, brain and cognitive sciences, and nuclear science and engineering, and an associate member of MIT’s McGovern Institute for Brain Research.

Jasanoff is the senior author of the paper, which appears in the Feb. 22 issue of Nature Communications. MIT postdocs Ali Barandov and Benjamin Bartelle are the paper’s lead authors. MIT senior Catherine Williamson, recent MIT graduate Emily Loucks, and Arthur Amos Noyes Professor Emeritus of Chemistry Stephen Lippard are also authors of the study.

Getting into cells

In their resting state, neurons have very low calcium levels. However, when they fire an electrical impulse, calcium floods into the cell. Over the past several decades, scientists have devised ways to image this activity by labeling calcium with fluorescent molecules. This can be done in cells grown in a lab dish, or in the brains of living animals, but this kind of microscopy imaging can only penetrate a few tenths of a millimeter into the tissue, limiting most studies to the surface of the brain.

“There are amazing things being done with these tools, but we wanted something that would allow ourselves and others to look deeper at cellular-level signaling,” Jasanoff says.

To achieve that, the MIT team turned to MRI, a noninvasive technique that works by detecting magnetic interactions between an injected contrast agent and water molecules inside cells.

Many scientists have been working on MRI-based calcium sensors, but the major obstacle has been developing a contrast agent that can get inside brain cells. Last year, Jasanoff’s lab developed an MRI sensor that can measure extracellular calcium concentrations, but these were based on nanoparticles that are too large to enter cells.

To create their new intracellular calcium sensors, the researchers used building blocks that can pass through the cell membrane. The contrast agent contains manganese, a metal that interacts weakly with magnetic fields, bound to an organic compound that can penetrate cell membranes. This complex also contains a calcium-binding arm called a chelator.

Once inside the cell, if calcium levels are low, the calcium chelator binds weakly to the manganese atom, shielding the manganese from MRI detection. When calcium flows into the cell, the chelator binds to the calcium and releases the manganese, which makes the contrast agent appear brighter in an MRI image.

“When neurons, or other brain cells called glia, become stimulated, they often experience more than tenfold increases in calcium concentration. Our sensor can detect those changes,” Jasanoff says.

Precise measurements

The researchers tested their sensor in rats by injecting it into the striatum, a region deep within the brain that is involved in planning movement and learning new behaviors. They then used potassium ions to stimulate electrical activity in neurons of the striatum, and were able to measure the calcium response in those cells.

Jasanoff hopes to use this technique to identify small clusters of neurons that are involved in specific behaviors or actions. Because this method directly measures signaling within cells, it can offer much more precise information about the location and timing of neuron activity than traditional functional MRI (fMRI), which measures blood flow in the brain.

“This could be useful for figuring out how different structures in the brain work together to process stimuli or coordinate behavior,” he says.

In addition, this technique could be used to image calcium as it performs many other roles, such as facilitating the activation of immune cells. With further modification, it could also one day be used to perform diagnostic imaging of the brain or other organs whose functions rely on calcium, such as the heart.

The research was funded by the National Institutes of Health and the MIT Simons Center for the Social Brain.

Alan Jasanoff

Next Generation Brain Imaging

One of the greatest challenges of modern neuroscience is to relate high-level operations of the brain and mind to well-defined biological processes that arise from molecules and cells. The Jasanoff lab is creating a suite of experimental approaches designed to achieve this by permitting brain-wide dynamics of neural signaling and plasticity to be imaged for the first time, with molecular specificity. These potentially transformative approaches use novel probes detectable by magnetic resonance imaging (MRI) and other noninvasive readouts. The probes afford qualitatively new ways to study healthy and pathological aspects of integrated brain function in mechanistically-informative detail, in animals and possibly also people.

Monitoring electromagnetic signals in the brain with MRI

Anne Trafton |

Researchers commonly study brain function by monitoring two types of electromagnetism — electric fields and light. However, most methods for measuring these phenomena in the brain are very invasive.

MIT engineers have now devised a new technique to detect either electrical activity or optical signals in the brain using a minimally invasive sensor for magnetic resonance imaging (MRI).

MRI is often used to measure changes in blood flow that indirectly represent brain activity, but the MIT team has devised a new type of MRI sensor that can detect tiny electrical currents, as well as light produced by luminescent proteins. (Electrical impulses arise from the brain’s internal communications, and optical signals can be produced by a variety of molecules developed by chemists and bioengineers.)

“MRI offers a way to sense things from the outside of the body in a minimally invasive fashion,” says Aviad Hai, an MIT postdoc and the lead author of the study. “It does not require a wired connection into the brain. We can implant the sensor and just leave it there.”

This kind of sensor could give neuroscientists a spatially accurate way to pinpoint electrical activity in the brain. It can also be used to measure light, and could be adapted to measure chemicals such as glucose, the researchers say.

Alan Jasanoff, an MIT professor of biological engineering, brain and cognitive sciences, and nuclear science and engineering, and an associate member of MIT’s McGovern Institute for Brain Research, is the senior author of the paper, which appears in the Oct. 22 issue of Nature Biomedical Engineering. Postdocs Virginia Spanoudaki and Benjamin Bartelle are also authors of the paper.

Detecting electric fields

Jasanoff’s lab has previously developed MRI sensors that can detect calcium and neurotransmitters such as serotonin and dopamine. In this paper, they wanted to expand their approach to detecting biophysical phenomena such as electricity and light. Currently, the most accurate way to monitor electrical activity in the brain is by inserting an electrode, which is very invasive and can cause tissue damage. Electroencephalography (EEG) is a noninvasive way to measure electrical activity in the brain, but this method cannot pinpoint the origin of the activity.

To create a sensor that could detect electromagnetic fields with spatial precision, the researchers realized they could use an electronic device — specifically, a tiny radio antenna.

MRI works by detecting radio waves emitted by the nuclei of hydrogen atoms in water. These signals are usually detected by a large radio antenna within an MRI scanner. For this study, the MIT team shrank the radio antenna down to just a few millimeters in size so that it could be implanted directly into the brain to receive the radio waves generated by water in the brain tissue.

The sensor is initially tuned to the same frequency as the radio waves emitted by the hydrogen atoms. When the sensor picks up an electromagnetic signal from the tissue, its tuning changes and the sensor no longer matches the frequency of the hydrogen atoms. When this happens, a weaker image arises when the sensor is scanned by an external MRI machine.

The researchers demonstrated that the sensors can pick up electrical signals similar to those produced by action potentials (the electrical impulses fired by single neurons), or local field potentials (the sum of electrical currents produced by a group of neurons).

“We showed that these devices are sensitive to biological-scale potentials, on the order of millivolts, which are comparable to what biological tissue generates, especially in the brain,” Jasanoff says.

The researchers performed additional tests in rats to study whether the sensors could pick up signals in living brain tissue. For those experiments, they designed the sensors to detect light emitted by cells engineered to express the protein luciferase.

Normally, luciferase’s exact location cannot be determined when it is deep within the brain or other tissues, so the new sensor offers a way to expand the usefulness of luciferase and more precisely pinpoint the cells that are emitting light, the researchers say. Luciferase is commonly engineered into cells along with another gene of interest, allowing researchers to determine whether the genes have been successfully incorporated by measuring the light produced.

Smaller sensors

One major advantage of this sensor is that it does not need to carry any kind of power supply, because the radio signals that the external MRI scanner emits are enough to power the sensor.

Hai, who will be joining the faculty at the University of Wisconsin at Madison in January, plans to further miniaturize the sensors so that more of them can be injected, enabling the imaging of light or electrical fields over a larger brain area. In this paper, the researchers performed modeling that showed that a 250-micron sensor (a few tenths of a millimeter) should be able to detect electrical activity on the order of 100 millivolts, similar to the amount of current in a neural action potential.

Jasanoff’s lab is interested in using this type of sensor to detect neural signals in the brain, and they envision that it could also be used to monitor electromagnetic phenomena elsewhere in the body, including muscle contractions or cardiac activity.

“If the sensors were on the order of hundreds of microns, which is what the modeling suggests is in the future for this technology, then you could imagine taking a syringe and distributing a whole bunch of them and just leaving them there,” Jasanoff says. “What this would do is provide many local readouts by having sensors distributed all over the tissue.”

The research was funded by the National Institutes of Health.