Research Area: Cellular & Molecular Neuroscience

​synapses, vesicles, electrophysiology, protein complexes, signaling, small molecules, disease-linked genes, dendrites, cell death, brain disorders, neurodevelopment

Electrical properties of dendrites help explain our brain’s unique computing power

Anne Trafton |

Neurons in the human brain receive electrical signals from thousands of other cells, and long neural extensions called dendrites play a critical role in incorporating all of that information so the cells can respond appropriately.

Using hard-to-obtain samples of human brain tissue, MIT neuroscientists have now discovered that human dendrites have different electrical properties from those of other species. Their studies reveal that electrical signals weaken more as they flow along human dendrites, resulting in a higher degree of electrical compartmentalization, meaning that small sections of dendrites can behave independently from the rest of the neuron.

These differences may contribute to the enhanced computing power of the human brain, the researchers say.

“It’s not just that humans are smart because we have more neurons and a larger cortex. From the bottom up, neurons behave differently,” says Mark Harnett, the Fred and Carole Middleton Career Development Assistant Professor of Brain and Cognitive Sciences. “In human neurons, there is more electrical compartmentalization, and that allows these units to be a little bit more independent, potentially leading to increased computational capabilities of single neurons.”

Harnett, who is also a member of MIT’s McGovern Institute for Brain Research, and Sydney Cash, an assistant professor of neurology at Harvard Medical School and Massachusetts General Hospital, are the senior authors of the study, which appears in the Oct. 18 issue of Cell. The paper’s lead author is Lou Beaulieu-Laroche, a graduate student in MIT’s Department of Brain and Cognitive Sciences.

Neural computation

Dendrites can be thought of as analogous to transistors in a computer, performing simple operations using electrical signals. Dendrites receive input from many other neurons and carry those signals to the cell body. If stimulated enough, a neuron fires an action potential — an electrical impulse that then stimulates other neurons. Large networks of these neurons communicate with each other to generate thoughts and behavior.

The structure of a single neuron often resembles a tree, with many branches bringing in information that arrives far from the cell body. Previous research has found that the strength of electrical signals arriving at the cell body depends, in part, on how far they travel along the dendrite to get there. As the signals propagate, they become weaker, so a signal that arrives far from the cell body has less of an impact than one that arrives near the cell body.

Dendrites in the cortex of the human brain are much longer than those in rats and most other species, because the human cortex has evolved to be much thicker than that of other species. In humans, the cortex makes up about 75 percent of the total brain volume, compared to about 30 percent in the rat brain.

Although the human cortex is two to three times thicker than that of rats, it maintains the same overall organization, consisting of six distinctive layers of neurons. Neurons from layer 5 have dendrites long enough to reach all the way to layer 1, meaning that human dendrites have had to elongate as the human brain has evolved, and electrical signals have to travel that much farther.

In the new study, the MIT team wanted to investigate how these length differences might affect dendrites’ electrical properties. They were able to compare electrical activity in rat and human dendrites, using small pieces of brain tissue removed from epilepsy patients undergoing surgical removal of part of the temporal lobe. In order to reach the diseased part of the brain, surgeons also have to take out a small chunk of the anterior temporal lobe.

With the help of MGH collaborators Cash, Matthew Frosch, Ziv Williams, and Emad Eskandar, Harnett’s lab was able to obtain samples of the anterior temporal lobe, each about the size of a fingernail.

Evidence suggests that the anterior temporal lobe is not affected by epilepsy, and the tissue appears normal when examined with neuropathological techniques, Harnett says. This part of the brain appears to be involved in a variety of functions, including language and visual processing, but is not critical to any one function; patients are able to function normally after it is removed.

Once the tissue was removed, the researchers placed it in a solution very similar to cerebrospinal fluid, with oxygen flowing through it. This allowed them to keep the tissue alive for up to 48 hours. During that time, they used a technique known as patch-clamp electrophysiology to measure how electrical signals travel along dendrites of pyramidal neurons, which are the most common type of excitatory neurons in the cortex.

These experiments were performed primarily by Beaulieu-Laroche. Harnett’s lab (and others) have previously done this kind of experiment in rodent dendrites, but his team is the first to analyze electrical properties of human dendrites.

Unique features

The researchers found that because human dendrites cover longer distances, a signal flowing along a human dendrite from layer 1 to the cell body in layer 5 is much weaker when it arrives than a signal flowing along a rat dendrite from layer 1 to layer 5.

They also showed that human and rat dendrites have the same number of ion channels, which regulate the current flow, but these channels occur at a lower density in human dendrites as a result of the dendrite elongation. They also developed a detailed biophysical model that shows that this density change can account for some of the differences in electrical activity seen between human and rat dendrites, Harnett says.

Nelson Spruston, senior director of scientific programs at the Howard Hughes Medical Institute Janelia Research Campus, described the researchers’ analysis of human dendrites as “a remarkable accomplishment.”

“These are the most carefully detailed measurements to date of the physiological properties of human neurons,” says Spruston, who was not involved in the research. “These kinds of experiments are very technically demanding, even in mice and rats, so from a technical perspective, it’s pretty amazing that they’ve done this in humans.”

The question remains, how do these differences affect human brainpower? Harnett’s hypothesis is that because of these differences, which allow more regions of a dendrite to influence the strength of an incoming signal, individual neurons can perform more complex computations on the information.

“If you have a cortical column that has a chunk of human or rodent cortex, you’re going to be able to accomplish more computations faster with the human architecture versus the rodent architecture,” he says.

There are many other differences between human neurons and those of other species, Harnett adds, making it difficult to tease out the effects of dendritic electrical properties. In future studies, he hopes to explore further the precise impact of these electrical properties, and how they interact with other unique features of human neurons to produce more computing power.

The research was funded by the National Sciences and Engineering Research Council of Canada, the Dana Foundation David Mahoney Neuroimaging Grant Program, and the National Institutes of Health.

Mark Harnett’s “Holy Grail” experiment

by Julie Pryor |

Neurons in the human brain receive electrical signals from thousands of other cells, and long neural extensions called dendrites play a critical role in incorporating all of that information so the cells can respond appropriately.

Using hard-to-obtain samples of human brain tissue, McGovern neuroscientist Mark Harnett has now discovered that human dendrites have different electrical properties from those of other species. Their studies reveal that electrical signals weaken more as they flow along human dendrites, resulting in a higher degree of electrical compartmentalization, meaning that small sections of dendrites can behave independently from the rest of the neuron.

These differences may contribute to the enhanced computing power of the human brain, the researchers say.

Mark Harnett named Vallee Foundation Scholar

Anne Trafton |

The Bert L and N Kuggie Vallee Foundation has named McGovern Institute investigator Mark Harnett a 2018 Vallee Scholar. The Vallee Scholars Program recognizes original, innovative, and pioneering work by early career scientists at a critical juncture in their careers and provides $300,000 in discretionary funds to be spent over four years for basic biomedical research. Harnett is among five researchers named to this year’s Vallee Scholars Program.

Harnett, who is also the Fred and Carole Middleton Career Development Assistant Professor in the Department of Brain and Cognitive Sciences, is being recognized for his work exploring how the biophysical features of neurons give rise to the computational power of the brain. By exploiting new technologies and approaches at the interface of biophysics and systems neuroscience, research in the Harnett lab aims to provide a new understanding of the biology underlying how mammalian brains learn. This may open new areas of research into brain disorders characterized by atypical learning and memory (such as dementia and schizophrenia) and may also have important implications for designing new, brain-inspired artificial neural networks.

The Vallee Foundation was established in 1996 by Bert and Kuggie Vallee to foster originality, creativity, and leadership within biomedical scientific research and medical education. The foundation’s goal to fund originality, innovation, and pioneering work “recognizes the future promise of these scientists who are dedicated to understanding fundamental biological processes.” Harnett joins a list of 24 Vallee Scholars, including McGovern investigator Feng Zhang, who have been appointed to the program since its inception in 2013.

Biologists discover function of gene linked to familial ALS

Anne Trafton |

MIT biologists have discovered a function of a gene that is believed to account for up to 40 percent of all familial cases of amyotrophic lateral sclerosis (ALS). Studies of ALS patients have shown that an abnormally expanded region of DNA in a specific region of this gene can cause the disease.

In a study of the microscopic worm Caenorhabditis elegans, the researchers found that the gene has a key role in helping cells to remove waste products via structures known as lysosomes. When the gene is mutated, these unwanted substances build up inside cells. The researchers believe that if this also happens in neurons of human ALS patients, it could account for some of those patients’ symptoms.

“Our studies indicate what happens when the activities of such a gene are inhibited — defects in lysosomal function. Certain features of ALS are consistent with their being caused by defects in lysosomal function, such as inflammation,” says H. Robert Horvitz, the David H. Koch Professor of Biology at MIT, a member of the McGovern Institute for Brain Research and the Koch Institute for Integrative Cancer Research, and the senior author of the study.

Mutations in this gene, known as C9orf72, have also been linked to another neurodegenerative brain disorder known as frontotemporal dementia (FTD), which is estimated to affect about 60,000 people in the United States.

“ALS and FTD are now thought to be aspects of the same disease, with different presentations. There are genes that when mutated cause only ALS, and others that cause only FTD, but there are a number of other genes in which mutations can cause either ALS or FTD or a mixture of the two,” says Anna Corrionero, an MIT postdoc and the lead author of the paper, which appears in the May 3 issue of the journal Current Biology.

Genetic link

Scientists have identified dozens of genes linked to familial ALS, which occurs when two or more family members suffer from the disease. Doctors believe that genetics may also be a factor in nonfamilial cases of the disease, which are much more common, accounting for 90 percent of cases.

Of all ALS-linked mutations identified so far, the C9orf72 mutation is the most prevalent, and it is also found in about 25 percent of frontotemporal dementia patients. The MIT team set out to study the gene’s function in C. elegans, which has an equivalent gene known as alfa-1.

In studies of worms that lack alfa-1, the researchers discovered that defects became apparent early in embryonic development. C. elegans embryos have a yolk that helps to sustain them before they hatch, and in embryos missing alfa-1, the researchers found “blobs” of yolk floating in the fluid surrounding the embryos.

This led the researchers to discover that the gene mutation was affecting the lysosomal degradation of yolk once it is absorbed into the cells. Lysosomes, which also remove cellular waste products, are cell structures which carry enzymes that can break down many kinds of molecules.

When lysosomes degrade their contents — such as yolk — they are reformed into tubular structures that split, after which they are able to degrade other materials. The MIT team found that in cells with the alfa-1 mutation and impaired lysosomal degradation, lysosomes were unable to reform and could not be used again, disrupting the cell’s waste removal process.

“It seems that lysosomes do not reform as they should, and material accumulates in the cells,” Corrionero says.

For C. elegans embryos, that meant that they could not properly absorb the nutrients found in yolk, which made it harder for them to survive under starvation conditions. The embryos that did survive appeared to be normal, the researchers say.

Robert Brown, chair of the Department of Neurology at the University of Massachusetts Medical School, describes the study as a major contribution to scientists’ understanding of the normal function of the C9orf72 gene.

“They used the power of worm genetics to dissect very fully the stages of vesicle maturation at which this gene seems to play a major role,” says Brown, who was not involved in the study.

Neuronal effects

The researchers were able to partially reverse the effects of alfa-1 loss in the C. elegans embryos by expressing the human protein encoded by the C9orf72 gene. “This suggests that the worm and human proteins are performing the same molecular function,” Corrionero says.

If loss of C9orf72 affects lysosome function in human neurons, it could lead to a slow, gradual buildup of waste products in those cells. ALS usually affects cells of the motor cortex, which controls movement, and motor neurons in the spinal cord, while frontotemporal dementia affects the frontal areas of the brain’s cortex.

“If you cannot degrade things properly in cells that live for very long periods of time, like neurons, that might well affect the survival of the cells and lead to disease,” Corrionero says.

Many pharmaceutical companies are now researching drugs that would block the expression of the mutant C9orf72. The new study suggests certain possible side effects to watch for in studies of such drugs.

“If you generate drugs that decrease C9orf72 expression, you might cause problems in lysosomal homeostasis,” Corrionero says. “In developing any drug, you have to be careful to watch for possible side effects. Our observations suggest some things to look for in studying drugs that inhibit C9orf72 in ALS/FTD patients.”

The research was funded by an EMBO postdoctoral fellowship, an ALS Therapy Alliance grant, a gift from Rose and Douglas Barnard ’79 to the McGovern Institute, and a gift from the Halis Family Foundation to the MIT Aging Brain Initiative.

Viral tool traces long-term neuron activity

Anne Trafton |

For the past decade, neuroscientists have been using a modified version of the rabies virus to label neurons and trace the connections between them. Although this technique has proven very useful, it has one major drawback: The virus is toxic to cells and can’t be used for studies longer than about two weeks.

Researchers at MIT and the Allen Institute for Brain Science have now developed a new version of this virus that stops replicating once it infects a cell, allowing it to deliver its genetic cargo without harming the cell. Using this technique, scientists should be able to study the infected neurons for several months, enabling longer-term studies of neuron functions and connections.

“With the first-generation vectors, the virus is replicating like crazy in the infected neurons, and that’s not good for them,” says Ian Wickersham, a principal research scientist at MIT’s McGovern Institute for Brain Research and the senior author of the new study. “With the second generation, infected cells look normal and act normal for at least four months — which was as long as we tracked them — and probably for the lifetime of the animal.”

Soumya Chatterjee of the Allen Institute is the lead author of the paper, which appears in the March 5 issue of Nature Neuroscience.

Viral tracing

Rabies viruses are well-suited for tracing neural connections because they have evolved to spread from neuron to neuron through junctions known as synapses. The viruses can also spread from the terminals of axons back to the cell body of the same neuron. Neuroscientists can engineer the viruses to carry genes for fluorescent proteins, which are useful for imaging, or for light-sensitive proteins that can be used to manipulate neuron activity.

In 2007, Wickersham demonstrated that a modified version of the rabies virus could be used to trace synapses between only directly connected neurons. Before that, researchers had been using the rabies virus for similar studies, but they were unable to keep it from spreading throughout the entire brain.

By deleting one of the virus’ five genes, which codes for a glycoprotein normally found on the surface of infected cells, Wickersham was able to create a version that can only spread to neurons in direct contact with the initially infected cell. This 2007 modification enabled scientists to perform “monosynaptic tracing,” a technique that allows them to identify connections between the infected neuron and any neuron that provides input to it.

This first generation of the modified rabies virus is also used for a related technique known as retrograde targeting, in which the virus can be injected into a cluster of axon terminals and then travel back to the cell bodies of those axons. This can help researchers discover the location of neurons that send impulses to the site of the virus injection.

Researchers at MIT have used retrograde targeting to identify populations of neurons of the basolateral amygdala that project to either the nucleus accumbens or the central medial amygdala. In that type of study, researchers can deliver optogenetic proteins that allow them to manipulate the activity of each population of cells. By selectively stimulating or shutting off these two separate cell populations, researchers can determine their functions.

Reduced toxicity

To create the second-generation version of this viral tool, Wickersham and his colleagues deleted the gene for the polymerase enzyme, which is necessary for transcribing viral genes. Without this gene, the virus becomes less harmful and infected cells can survive much longer. In the new study, the researchers found that neurons were still functioning normally for up to four months after infection.

“The second-generation virus enters a cell with its own few copies of the polymerase protein and is able to start transcribing its genes, including the transgene that we put into it. But then because it’s not able to make more copies of the polymerase, it doesn’t have this exponential takeover of the cell, and in practice it seems to be totally nontoxic,” Wickersham says.

The lack of polymerase also greatly reduces the expression of whichever gene the researchers engineer into the virus, so they need to employ a little extra genetic trickery to achieve their desired outcome. Instead of having the virus deliver a gene for a fluorescent or optogenetic protein, they engineer it to deliver a gene for an enzyme called Cre recombinase, which can delete target DNA sequences in the host cell’s genome.

This virus can then be used to study neurons in mice whose genomes have been engineered to include a gene that is turned on when the recombinase cuts out a small segment of DNA. Only a small amount of recombinase enzyme is needed to turn on the target gene, which could code for a fluorescent protein or another type of labeling molecule. The second-generation viruses can also work in regular mice if the researchers simultaneously inject another virus carrying a recombinase-activated gene for a fluorescent protein.

The new paper shows that the second-generation virus works well for retrograde labeling, not tracing synapses between cells, but the researchers have also now begun using it for monosynaptic tracing.

The research was funded by the National Institute of Mental Health, the National Institute on Aging, and the National Eye Institute.

Seeing the brain’s electrical activity

Anne Trafton |

Neurons in the brain communicate via rapid electrical impulses that allow the brain to coordinate behavior, sensation, thoughts, and emotion. Scientists who want to study this electrical activity usually measure these signals with electrodes inserted into the brain, a task that is notoriously difficult and time-consuming.

MIT researchers have now come up with a completely different approach to measuring electrical activity in the brain, which they believe will prove much easier and more informative. They have developed a light-sensitive protein that can be embedded into neuron membranes, where it emits a fluorescent signal that indicates how much voltage a particular cell is experiencing. This could allow scientists to study how neurons behave, millisecond by millisecond, as the brain performs a particular function.

“If you put an electrode in the brain, it’s like trying to understand a phone conversation by hearing only one person talk,” says Edward Boyden, an associate professor of biological engineering and brain and cognitive sciences at MIT. “Now we can record the neural activity of many cells in a neural circuit and hear them as they talk to each other.”

Boyden, who is also a member of MIT’s Media Lab, McGovern Institute for Brain Research, and Koch Institute for Integrative Cancer Research, and an HHMI-Simons Faculty Scholar, is the senior author of the study, which appears in the Feb. 26 issue of Nature Chemical Biology. The paper’s lead authors are MIT postdocs Kiryl Piatkevich and Erica Jung.

Imaging voltage

For the past two decades, scientists have sought a way to monitor electrical activity in the brain through imaging instead of recording with electrodes. Finding fluorescent molecules that can be used for this kind of imaging has been difficult; not only do the proteins have to be very sensitive to changes in voltage, they must also respond quickly and be resistant to photobleaching (fading that can be caused by exposure to light).

Boyden and his colleagues came up with a new strategy for finding a molecule that would fulfill everything on this wish list: They built a robot that could screen millions of proteins, generated through a process called directed protein evolution, for the traits they wanted.

“You take a gene, then you make millions and millions of mutant genes, and finally you pick the ones that work the best,” Boyden says. “That’s the way that evolution works in nature, but now we’re doing it in the lab with robots so we can pick out the genes with the properties we want.”

The researchers made 1.5 million mutated versions of a light-sensitive protein called QuasAr2, which was previously engineered by Adam Cohen’s lab at Harvard University. (That work, in turn, was based on the molecule Arch, which the Boyden lab reported in 2010.) The researchers put each of those genes into mammalian cells (one mutant per cell), then grew the cells in lab dishes and used an automated microscope to take pictures of the cells. The robot was able to identify cells with proteins that met the criteria the researchers were looking for, the most important being the protein’s location within the cell and its brightness.

The research team then selected five of the best candidates and did another round of mutation, generating 8 million new candidates. The robot picked out the seven best of these, which the researchers then narrowed down to one top performer, which they called Archon1.

Mapping the brain

A key feature of Archon1 is that once the gene is delivered into a cell, the Archon1 protein embeds itself into the cell membrane, which is the best place to obtain an accurate measurement of a cell’s voltage.

Using this protein, the researchers were able to measure electrical activity in mouse brain tissue, as well as in brain cells of zebrafish larvae and the worm Caenorhabditis elegans. The latter two organisms are transparent, so it is easy to expose them to light and image the resulting fluorescence. When the cells are exposed to a certain wavelength of reddish-orange light, the protein sensor emits a longer wavelength of red light, and the brightness of the light corresponds to the voltage of that cell at a given moment in time.

The researchers also showed that Archon1 can be used in conjunction with light-sensitive proteins that are commonly used to silence or stimulate neuron activity — these are known as optogenetic proteins — as long as those proteins respond to colors other than red. In experiments with C. elegans, the researchers demonstrated that they could stimulate one neuron using blue light and then use Archon1 to measure the resulting effect in neurons that receive input from that cell.

Cohen, the Harvard professor who developed the predecessor to Archon1, says the new MIT protein brings scientists closer to the goal of imaging millisecond-timescale electrical activity in live brains.

“Traditionally, it has been excruciatingly labor-intensive to engineer fluorescent voltage indicators, because each mutant had to be cloned individually and then tested through a slow, manual patch-clamp electrophysiology measurement. The Boyden lab developed a very clever high-throughput screening approach to this problem,” says Cohen, who was not involved in this study. “Their new reporter looks really great in fish and worms and in brain slices. I’m eager to try it in my lab.”

The researchers are now working on using this technology to measure brain activity in mice as they perform various tasks, which Boyden believes should allow them to map neural circuits and discover how they produce specific behaviors.

“We will be able to watch a neural computation happen,” he says. “Over the next five years or so we’re going to try to solve some small brain circuits completely. Such results might take a step toward understanding what a thought or a feeling actually is.”

The research was funded by the HHMI-Simons Faculty Scholars Program, the IET Harvey Prize, the MIT Media Lab, the New York Stem Cell Foundation Robertson Award, the Open Philanthropy Project, John Doerr, the Human Frontier Science Program, the Department of Defense, the National Science Foundation, and the National Institutes of Health, including an NIH Director’s Pioneer Award.

Study reveals molecular mechanisms of memory formation

Anne Trafton |

MIT neuroscientists have uncovered a cellular pathway that allows specific synapses to become stronger during memory formation. The findings provide the first glimpse of the molecular mechanism by which long-term memories are encoded in a region of the hippocampus called CA3.

The researchers found that a protein called Npas4, previously identified as a master controller of gene expression triggered by neuronal activity, controls the strength of connections between neurons in the CA3 and those in another part of the hippocampus called the dentate gyrus. Without Npas4, long-term memories cannot form.

“Our study identifies an experience-dependent synaptic mechanism for memory encoding in CA3, and provides the first evidence for a molecular pathway that selectively controls it,” says Yingxi Lin, an associate professor of brain and cognitive sciences and a member of MIT’s McGovern Institute for Brain Research.

Lin is the senior author of the study, which appears in the Feb. 8 issue of Neuron. The paper’s lead author is McGovern Institute research scientist Feng-Ju (Eddie) Weng.

Synaptic strength

Neuroscientists have long known that the brain encodes memories by altering the strength of synapses, or connections between neurons. This requires interactions of many proteins found in both presynaptic neurons, which send information about an event, and postsynaptic neurons, which receive the information.

Neurons in the CA3 region play a critical role in the formation of contextual memories, which are memories that link an event with the location where it took place, or with other contextual information such as timing or emotions. These neurons receive synaptic inputs from three different pathways, and scientists have hypothesized that one of these inputs, from the dentate gyrus, is critical for encoding new contextual memories. However, the mechanism of how this information is encoded was not known.

In a study published in 2011, Lin and colleagues found that Npas4, a gene that is turned on immediately following new experiences, appears to act as a master controller of the program of gene expression required for long-term memory formation. They also found that Npas4 is most active in the CA3 region of the hippocampus during learning. This activity was already known to be required for fast contextual learning, such is required during a type of task known as contextual fear conditioning. During the conditioning, mice receive a mild electric shock when they enter and explore a specific chamber. Within minutes, the mice learn to fear the chamber, and the next time they enter it, they freeze.

When the researchers knocked out the Npas4 gene, they found that mice could not remember the fearful event. They also found the same effect when they knocked out the gene just in the CA3 region of the hippocampus. Knocking it out in other parts of the hippocampus, however, had no effect on memory.

In the new study, the researchers explored in further detail how Npas4 exerts its effects. Lin’s lab had previously developed a method that makes it possible to fluorescently label CA3 neurons that are activated during this fear conditioning. Using the same fear conditioning process, the researchers showed that during learning, certain synaptic inputs to CA3 neurons are strengthened, but not others. Furthermore, this strengthening requires Npas4.

The inputs that are selectively strengthened come from another part of the hippocampus called the dentate gyrus. These signals convey information about the location where the fearful experience took place.

Without Npas4, synapses coming from the dentate gyrus to CA3 failed to strengthen, and the mice could not form memories of the event. Further experiments revealed that this strengthening is required specifically for memory encoding, not for retrieving memories already formed. The researchers also found that Npas4 loss did not affect synaptic inputs that CA3 neurons receive from other sources.

Kimberly Raab-Graham, an associate professor of physiology and pharmacology at Wake Forest University School of Medicine, says the researchers used an impressive variety of techniques to unequivocally show that contextual memory formation is tightly controlled by Npas4.

“The major finding of the study is that contextual memory is driven by a single circuit and comes down to a single transcription factor,” says Raab-Graham, who was not involved in the study. “When they knocked out the transcription factor, they removed contextual memory formation, and they could restore it by adding the transcription factor.”

Synapse maintenance

The researchers also identified one of the genes that Npas4 controls to exert this effect on synapse strength. This gene, known as plk2, is involved in shrinking postsynaptic structures. Npas4 turns on plk2, thereby reducing synapse size and strength. This suggests that Npas4 itself does not strengthen synapses, but maintains synapses in a state that allows them to be strengthened when necessary. Without Npas4, synapses become too strong and therefore cannot be induced to encode memories by further strengthening them.

“When you take out Npas4, the synaptic strength is almost saturated,” Lin says. “And then when learning takes place, although the memory-encoding cells can be fluorescently labeled, you no longer see the strengthening of those connections.”

In future work, Lin hopes to study how the circuit connecting the dentate gyrus to CA3 interacts with other pathways required for memory retrieval. “Somehow there’s some crosstalk between different pathways so that once the information is stored, it can be retrieved by the other inputs,” she says.

The research was funded by the National Institutes of Health, the James H. Ferry Fund, and a Swedish Brain Foundation Research Fellowship.

Listening to neurons

Anne Trafton |

When McGovern Investigator Mark Harnett gets a text from his collaborator at Massachusetts General Hospital, it’s time to stock up on Red Bull and coffee.

Because very soon—sometimes within a few hours—a chunk of living human brain will arrive at the lab, marking the start of an epic session recording the brain’s internal dialogue. And it continues non-stop until the neurons die.

“That first time, we went for 54 hours straight,” Harnett says.

Now two years old, his lab is trying to answer fundamental questions about how the brain’s basic calculations lead to the experience of daily life. Most neuroscientists consider the neuron to be the brain’s basic computational unit, but Harnett is focusing on the internal workings of individual neurons, and in particular, the role of dendrites, the elaborate branching structures that are the most distinctive feature of these cells.

Years ago, scientists viewed dendrites as essentially passive structures, receiving neurochemical information that they translated into electrical signals and sent to the cell body, or soma. The soma was the calculator, summing up the data and deciding whether or not to produce an output signal, known as an action potential. Now though, evidence has accumulated showing dendrites to be capable of processing information themselves, leading to a new and more expansive view in which each individual neuron contains multiple computational elements.

Due to the enormous technical challenge such work demands, however, scientists still don’t fully understand the biophysical mechanisms behind dendritic computations.

They understand even less how these mechanisms operate in and contribute to an awake, thinking brain—nor how much the mouse models that have defined the field translate to the vastly more powerful computational abilities of the human brain.

Harnett is in an ideal position to untangle some of these questions, owing to a rare combination of the technology and skills needed to record from dendrites—a feat in itself—as well as access to animals and human tissue, and a lab eager for a challenge.

Human interest

Most previous research on dendrites has been done in rats or mice, and Harnett’s collaboration with MGH addresses a deceptively simple question: are the brain cells of rodents really equivalent to those of humans?

Researchers have generally assumed that they are similar, but no one has studied the question in depth. It is known, however, that human dendrites are longer and more structurally complex, and Harnett suspects that these shape differences may reflect the existence of additional computational mechanisms.

To investigate this question, Harnett reached out to Sydney Cash, a neurologist at MGH and Harvard Medical School. Cash was intrigued. He’d been studying epilepsy patients with electrodes implanted in their brains to locate seizures before brain surgery, and he was seeing odd quirks in his data. The neurons seemed to be more connected than animal data would suggest, but he had no way to investigate. “And so I thought this collaboration would be fantastic,” he says. “The amazing electrophysiology that Mark’s group can do would be able to give us that insight into the behavior of these individual human neurons.”

So Cash arranged for Harnett to receive tissue from the brains of patients undergoing lobe resections—removal of chunks of tissue associated with seizures, which often works for patients for whom other treatments have failed.

Logistics were challenging—how to get a living piece of brain from one side of the Charles River to the other before it dies? Harnett initially wanted to use a drone; the legal department shot down that idea. Then he wanted to preserve the delicate tissue in bubbling oxygenated solution. But carting cylinders of hazardous compressed gas around the city was also a non-starter. “So, on the first one, we said to heck with it, we’ll just see if it works at all,” Harnett says. “We threw the brain into a bottle of ice-cold solution, screwed the top on, and told an Uber driver to go fast.”

When the cargo reaches the lab, the team starts the experiments immediately to collect as much data as possible before the neurons fail. This process involves the kind of arduous work that Harnett’s first graduate student, Lou Beaulieu-Laroche, relishes. Indeed, it’s why the young Quebecois wanted to join Harnett’s lab in the first place. “Every time I get to do this recording, I get so excited I don’t even need to sleep,” he says.

First, Beaulieu-Laroche places the precious tissue into a nutrient solution, carefully slicing it at the correct angle to reveal the neurons of interest. Then he begins patch clamp recordings, placing a tiny glass pipette to the surface of a single neuron in order to record its electrical activity. Most labs patch the larger soma; few can successfully patch the far finer dendrites. Beaulieu-Laroche can record two locations on a single dendrite simultaneously.

“It’s tricky experiment on top of tricky experiment,” Harnett says. “If you don’t succeed at every step, you get nothing out of it.” But do it right, and it’s a human neuron laid bare, whirring calculations visible in real-time.

The lab has collected samples from just seven surgeries so far, but a fascinating picture is emerging. For instance, spikes of activity in some human dendrites don’t seem to show up in the main part of the cell, a peculiar decoupling mice don’t show. What it means is still unclear, but it may be a sign of Harnett’s theorized intermediary computations between the distant dendrites and the cell body.

“It could be that the dendrite network of a human neuron is a little more complicated—maybe a little bit smarter,” Beaulieu-Laroche speculates. “And maybe that contributes to our intelligence.”

Active questioning

The human work is inherently limited to studying cells in a dish, and that gets to Harnett’s real focus. “A huge amount of time and effort has been spent identifying what dendrites are capable of doing in brain slices,” he says. Far less effort has gone into studying what they do in the behaving brain. It’s like exhaustively examining a set of tires on a car without ever testing its performance on the road.

To get at this problem, Harnett studies spatial navigation in mice, a task that requires the mouse brain to combine information about vision, motion, and self-orientation into a holistic experience. Scientists don’t know how this integration happens, but Harnett thinks it is an ideal test bed for exploring how dendritic processes contribute to complex behavioral computations. “We know the different types of information must eventually converge, but we think each type could be processed separately in the dendrites before being combined in the cell body,” he says.

The difficult part is catching neurons in the act of computing. This requires a two-pronged approach combining finegrained dendritic biophysics—like what Beaulieu-Laroche does in human cells— with behavioral studies and imaging in awake mice.

Marie-Sophie van der Goes, Harnett’s second graduate student, took up the challenge when she joined the lab in early 2016. From previous work, she knew spatial integration happened in a structure called the retrosplenial cortex, but the region was not well studied.

“We didn’t know where the information entering the RSC came from, or how it was organized,” she explains.

She and laboratory technician Derrick Barnagian used reverse tracing methods to identify inputs to the RSC, and teamed up with postdoc Mathieu Lafourcade to figure out how that information was organized and processed. Vision, motor and orientation systems are all connected to the region, as expected, but the inputs are segregated, with visual and motor information, for example, arriving at different locations within the dendritic tree. According to the patch clamp data, this is likely to be very important, since different dendrites appear to process information in different ways.

The next step for Van der Goes will be to record from neurons as mice perform a navigation task in a virtual maze. Two other postdocs, Jakob Voigts and Lukas Fischer, have already begun looking at similar questions. Working with mice genetically engineered so that their neurons light up when activated, the researchers implant a small glass window in the skull, directly over the RSC. Peering in with a two-photon microscope, they can watch, in real time, the activity of individual neurons and dendrites, as the animal processes different stimuli, including visual cues, sugar-water reward, and the sensation of its feet running along the ground.

It’s not a perfect system; the mouse’s head has to be held absolutely still for the scope to work. For now, they use a virtual reality maze and treadmill, although thanks to an ingenious rig Voigts invented, the set-up is poised to undergo a key improvement to make it feel more life-like for the mouse, and thus more accurate for the researchers.

Human questions

As much as the lab has accomplished so far, Harnett considers the people his greatest achievement. “Lab culture’s critical, in my opinion,” Harnett says. “How it manifests can really affect who wants to join your particular pirate crew.”

And his lab, he says, “is a wonderful environment and my team is incredibly successful in getting hard things to work.”

Everyone works on each other’s projects, coming in on Friday nights and weekend mornings, while ongoing jokes, lab memes, and shared meals bind the team together. Even Harnett prefers to bring his laptop to the crowded student and postdoc office rather than work in his own spacious quarters. With only three Americans in the lab—including Harnett —the space is rich in languages and friendly jabs. Canadian Beaulieu-Laroche says France-born Lafourcade speaks French like his grandmother; Lafourcade insists he speaks the best French—and the best Spanish. “But the Germans never speak German,” he wonders.

And there’s another uniting factor as well—a passion for asking big questions in life. Perhaps it is because many of the lab members are internationally educated and have studied more philosophy and literature than a typical science student. “Marie randomly dropped a Marcus Aurelius quote on me the other day,” Harnett says. He’d been flabbergasted, “But then I wondered, what is it about the fact that they’ve ended up here and we work together so incredibly well? I think it’s that we all think about this stuff—it gives us a shared humanism in the laboratory.”

Next-generation optogenetic molecules control single neurons

Anne Trafton |

Researchers at MIT and Paris Descartes University have developed a new optogenetic technique that sculpts light to target individual cells bearing engineered light-sensitive molecules, so that individual neurons can be precisely stimulated.

Until now, it has been challenging to use optogenetics to target single cells with such precise control over both the timing and location of the activation. This new advance paves the way for studies of how individual cells, and connections among those cells, generate specific behaviors such as initiating a movement or learning a new skill.

“Ideally what you would like to do is play the brain like a piano. You would want to control neurons independently, rather than having them all march in lockstep the way traditional optogenetics works, but which normally the brain doesn’t do,” says Ed Boyden, an associate professor of brain and cognitive sciences and biological engineering at MIT, and a member of MIT’s Media Lab and McGovern Institute for Brain Research.

The new technique relies on a new type of light-sensitive protein that can be embedded in neuron cell bodies, combined with holographic light-shaping that can focus light on a single cell.

Boyden and Valentina Emiliani, a research director at France’s National Center for Scientific Research (CNRS) and director of the Neurophotonics Laboratory at Paris Descartes University, are the senior authors of the study, which appears in the Nov. 13 issue of Nature Neuroscience. The lead authors are MIT postdoc Or Shemesh and CNRS postdocs Dimitrii Tanese and Valeria Zampini.

Precise control

More than 10 years ago, Boyden and his collaborators first pioneered the use of light-sensitive proteins known as microbial opsins to manipulate neuron electrical activity. These opsins can be embedded into the membranes of neurons, and when they are exposed to certain wavelengths of light, they silence or stimulate the cells.

Over the past decade, scientists have used this technique to study how populations of neurons behave during brain tasks such as memory recall or habit formation. Traditionally, many cells are targeted simultaneously because the light shining into the brain strikes a relatively large area. However, as Boyden points out, neurons may have different functions even when they are near each other.

“Two adjacent cells can have completely different neural codes. They can do completely different things, respond to different stimuli, and play different activity patterns during different tasks,” he says.

To achieve independent control of single cells, the researchers combined two new advances: a localized, more powerful opsin and an optimized holographic light-shaping microscope.

For the opsin, the researchers used a protein called CoChR, which the Boyden lab discovered in 2014. They chose this molecule because it generates a very strong electric current in response to light (about 10 times stronger than that produced by channelrhodopsin-2, the first protein used for optogenetics).

They fused CoChR to a small protein that directs the opsin into the cell bodies of neurons and away from axons and dendrites, which extend from the neuron body. This helps to prevent crosstalk between neurons, since light that activates one neuron can also strike axons and dendrites of other neurons that intertwine with the target neuron.

Boyden then worked with Emiliani to combine this approach with a light-stimulation technique that she had previously developed, known as two-photon computer-generated holography (CGH). This can be used to create three-dimensional sculptures of light that envelop a target cell.

Traditional holography is based on reproducing, with light, the shape of a specific object, in the absence of that original object. This is achieved by creating an “interferogram” that contains the information needed to reconstruct an object that was previously illuminated by a reference beam. In computer generated holography, the interferogram is calculated by a computer without the need of any original object. Years ago, Emiliani’s research group demonstrated that combined with two-photon excitation, CGH can be used to refocus laser light to precisely illuminate a cell or a defined group of cells in the brain.

In the new study, by combining this approach with new opsins that cluster in the cell body, the researchers showed they could stimulate individual neurons with not only precise spatial control but also great control over the timing of the stimulation. When they target a specific neuron, it responds consistently every time, with variability that is less than one millisecond, even when the cell is stimulated many times in a row.

“For the first time ever, we can bring the precision of single-cell control toward the natural timescales of neural computation,” Boyden says.

Mapping connections

Using this technique, the researchers were able to stimulate single neurons in brain slices and then measure the responses from cells that are connected to that cell. This paves the way for possible diagramming of the connections of the brain, and analyzing how those connections change in real time as the brain performs a task or learns a new skill.

One possible experiment, Boyden says, would be to stimulate neurons connected to each other to try to figure out if one is controlling the others or if they are all receiving input from a far-off controller.

“It’s an open question,” he says. “Is a given function being driven from afar, or is there a local circuit that governs the dynamics and spells out the exact chain of command within a circuit? If you can catch that chain of command in action and then use this technology to prove that that’s actually a causal link of events, that could help you explain how a sensation, or movement, or decision occurs.”

As a step toward that type of study, the researchers now plan to extend this approach into living animals. They are also working on improving their targeting molecules and developing high-current opsins that can silence neuron activity.

Kirill Volynski, a professor at the Institute of Neurology at University College London, who was not involved in the research, plans to use the new technology in his studies of diseases caused by mutations of proteins involved in synaptic communication between neurons.

“This gives us a very nice tool to study those mutations and those disorders,” Volynski says. “We expect this to enable a major improvement in the specificity of stimulating neurons that have mutated synaptic proteins.”

The research was funded by the National Institutes of Health, France’s National Research Agency, the Simons Foundation for the Social Brain, the Human Frontiers Science Program, John Doerr, the Open Philanthropy Project, the Howard Hughes Medical Institute, and the Defense Advanced Research Projects Agency.

Robotic system monitors specific neurons

Anne Trafton |

Recording electrical signals from inside a neuron in the living brain can reveal a great deal of information about that neuron’s function and how it coordinates with other cells in the brain. However, performing this kind of recording is extremely difficult, so only a handful of neuroscience labs around the world do it.

To make this technique more widely available, MIT engineers have now devised a way to automate the process, using a computer algorithm that analyzes microscope images and guides a robotic arm to the target cell.

This technology could allow more scientists to study single neurons and learn how they interact with other cells to enable cognition, sensory perception, and other brain functions. Researchers could also use it to learn more about how neural circuits are affected by brain disorders.

“Knowing how neurons communicate is fundamental to basic and clinical neuroscience. Our hope is this technology will allow you to look at what’s happening inside a cell, in terms of neural computation, or in a disease state,” says Ed Boyden, an associate professor of biological engineering and brain and cognitive sciences at MIT, and a member of MIT’s Media Lab and McGovern Institute for Brain Research.

Boyden is the senior author of the paper, which appears in the Aug. 30 issue of Neuron. The paper’s lead author is MIT graduate student Ho-Jun Suk.

Precision guidance

For more than 30 years, neuroscientists have been using a technique known as patch clamping to record the electrical activity of cells. This method, which involves bringing a tiny, hollow glass pipette in contact with the cell membrane of a neuron, then opening up a small pore in the membrane, usually takes a graduate student or postdoc several months to learn. Learning to perform this on neurons in the living mammalian brain is even more difficult.

There are two types of patch clamping: a “blind” (not image-guided) method, which is limited because researchers cannot see where the cells are and can only record from whatever cell the pipette encounters first, and an image-guided version that allows a specific cell to be targeted.

Five years ago, Boyden and colleagues at MIT and Georgia Tech, including co-author Craig Forest, devised a way to automate the blind version of patch clamping. They created a computer algorithm that could guide the pipette to a cell based on measurements of a property called electrical impedance — which reflects how difficult it is for electricity to flow out of the pipette. If there are no cells around, electricity flows and impedance is low. When the tip hits a cell, electricity can’t flow as well and impedance goes up.

Once the pipette detects a cell, it can stop moving instantly, preventing it from poking through the membrane. A vacuum pump then applies suction to form a seal with the cell’s membrane. Then, the electrode can break through the membrane to record the cell’s internal electrical activity.

The researchers achieved very high accuracy using this technique, but it still could not be used to target a specific cell. For most studies, neuroscientists have a particular cell type they would like to learn about, Boyden says.

“It might be a cell that is compromised in autism, or is altered in schizophrenia, or a cell that is active when a memory is stored. That’s the cell that you want to know about,” he says. “You don’t want to patch a thousand cells until you find the one that is interesting.”

To enable this kind of precise targeting, the researchers set out to automate image-guided patch clamping. This technique is difficult to perform manually because, although the scientist can see the target neuron and the pipette through a microscope, he or she must compensate for the fact that nearby cells will move as the pipette enters the brain.

“It’s almost like trying to hit a moving target inside the brain, which is a delicate tissue,” Suk says. “For machines it’s easier because they can keep track of where the cell is, they can automatically move the focus of the microscope, and they can automatically move the pipette.”

By combining several imaging processing techniques, the researchers came up with an algorithm that guides the pipette to within about 25 microns of the target cell. At that point, the system begins to rely on a combination of imagery and impedance, which is more accurate at detecting contact between the pipette and the target cell than either signal alone.

The researchers imaged the cells with two-photon microscopy, a commonly used technique that uses a pulsed laser to send infrared light into the brain, lighting up cells that have been engineered to express a fluorescent protein.

Using this automated approach, the researchers were able to successfully target and record from two types of cells — a class of interneurons, which relay messages between other neurons, and a set of excitatory neurons known as pyramidal cells. They achieved a success rate of about 20 percent, which is comparable to the performance of highly trained scientists performing the process manually.

Unraveling circuits

This technology paves the way for in-depth studies of the behavior of specific neurons, which could shed light on both their normal functions and how they go awry in diseases such as Alzheimer’s or schizophrenia. For example, the interneurons that the researchers studied in this paper have been previously linked with Alzheimer’s. In a recent study of mice, led by Li-Huei Tsai, director of MIT’s Picower Institute for Learning and Memory, and conducted in collaboration with Boyden, it was reported that inducing a specific frequency of brain wave oscillation in interneurons in the hippocampus could help to clear amyloid plaques similar to those found in Alzheimer’s patients.

“You really would love to know what’s happening in those cells,” Boyden says. “Are they signaling to specific downstream cells, which then contribute to the therapeutic result? The brain is a circuit, and to understand how a circuit works, you have to be able to monitor the components of the circuit while they are in action.”

This technique could also enable studies of fundamental questions in neuroscience, such as how individual neurons interact with each other as the brain makes a decision or recalls a memory.

Bernardo Sabatini, a professor of neurobiology at Harvard Medical School, says he is interested in adapting this technique to use in his lab, where students spend a great deal of time recording electrical activity from neurons growing in a lab dish.

“It’s silly to have amazingly intelligent students doing tedious tasks that could be done by robots,” says Sabatini, who was not involved in this study. “I would be happy to have robots do more of the experimentation so we can focus on the design and interpretation of the experiments.”

To help other labs adopt the new technology, the researchers plan to put the details of their approach on their web site, autopatcher.org.

Other co-authors include Ingrid van Welie, Suhasa Kodandaramaiah, and Brian Allen. The research was funded by Jeremy and Joyce Wertheimer, the National Institutes of Health (including the NIH Single Cell Initiative and the NIH Director’s Pioneer Award), the HHMI-Simons Faculty Scholars Program, and the New York Stem Cell Foundation-Robertson Award.