Researcher: Mark Harnett

Study finds a striking difference between neurons of humans and other mammals

Anne Trafton |

McGovern Institute Investigator Mark Harnett. Photo: Justin Knight

Neurons communicate with each other via electrical impulses, which are produced by ion channels that control the flow of ions such as potassium and sodium. In a surprising new finding, MIT neuroscientists have shown that human neurons have a much smaller number of these channels than expected, compared to the neurons of other mammals.

The researchers hypothesize that this reduction in channel density may have helped the human brain evolve to operate more efficiently, allowing it to divert resources to other energy-intensive processes that are required to perform complex cognitive tasks.

“If the brain can save energy by reducing the density of ion channels, it can spend that energy on other neuronal or circuit processes,” says Mark Harnett, an associate professor of brain and cognitive sciences, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the study.

Harnett and his colleagues analyzed neurons from 10 different mammals, the most extensive electrophysiological study of its kind, and identified a “building plan” that holds true for every species they looked at — except for humans. They found that as the size of neurons increases, the density of channels found in the neurons also increases.

However, human neurons proved to be a striking exception to this rule.

“Previous comparative studies established that the human brain is built like other mammalian brains, so we were surprised to find strong evidence that human neurons are special,” says former MIT graduate student Lou Beaulieu-Laroche.

Beaulieu-Laroche is the lead author of the study, which appears today in Nature.

A building plan

Neurons in the mammalian brain can receive electrical signals from thousands of other cells, and that input determines whether or not they will fire an electrical impulse called an action potential. In 2018, Harnett and Beaulieu-Laroche discovered that human and rat neurons differ in some of their electrical properties, primarily in parts of the neuron called dendrites — tree-like antennas that receive and process input from other cells.

One of the findings from that study was that human neurons had a lower density of ion channels than neurons in the rat brain. The researchers were surprised by this observation, as ion channel density was generally assumed to be constant across species. In their new study, Harnett and Beaulieu-Laroche decided to compare neurons from several different mammalian species to see if they could find any patterns that governed the expression of ion channels. They studied two types of voltage-gated potassium channels and the HCN channel, which conducts both potassium and sodium, in layer 5 pyramidal neurons, a type of excitatory neurons found in the brain’s cortex.

 

Former McGovern Institute graduate student Lou Beaulieu-Laroche is the lead author of the 2021 Nature paper.

They were able to obtain brain tissue from 10 mammalian species: Etruscan shrews (one of the smallest known mammals), gerbils, mice, rats, Guinea pigs, ferrets, rabbits, marmosets, and macaques, as well as human tissue removed from patients with epilepsy during brain surgery. This variety allowed the researchers to cover a range of cortical thicknesses and neuron sizes across the mammalian kingdom.

The researchers found that in nearly every mammalian species they looked at, the density of ion channels increased as the size of the neurons went up. The one exception to this pattern was in human neurons, which had a much lower density of ion channels than expected.

The increase in channel density across species was surprising, Harnett says, because the more channels there are, the more energy is required to pump ions in and out of the cell. However, it started to make sense once the researchers began thinking about the number of channels in the overall volume of the cortex, he says.

In the tiny brain of the Etruscan shrew, which is packed with very small neurons, there are more neurons in a given volume of tissue than in the same volume of tissue from the rabbit brain, which has much larger neurons. But because the rabbit neurons have a higher density of ion channels, the density of channels in a given volume of tissue is the same in both species, or any of the nonhuman species the researchers analyzed.

“This building plan is consistent across nine different mammalian species,” Harnett says. “What it looks like the cortex is trying to do is keep the numbers of ion channels per unit volume the same across all the species. This means that for a given volume of cortex, the energetic cost is the same, at least for ion channels.”

Energy efficiency

The human brain represents a striking deviation from this building plan, however. Instead of increased density of ion channels, the researchers found a dramatic decrease in the expected density of ion channels for a given volume of brain tissue.

The researchers believe this lower density may have evolved as a way to expend less energy on pumping ions, which allows the brain to use that energy for something else, like creating more complicated synaptic connections between neurons or firing action potentials at a higher rate.

“We think that humans have evolved out of this building plan that was previously restricting the size of cortex, and they figured out a way to become more energetically efficient, so you spend less ATP per volume compared to other species,” Harnett says.

He now hopes to study where that extra energy might be going, and whether there are specific gene mutations that help neurons of the human cortex achieve this high efficiency. The researchers are also interested in exploring whether primate species that are more closely related to humans show similar decreases in ion channel density.

The research was funded by the Natural Sciences and Engineering Research Council of Canada, a Friends of the McGovern Institute Fellowship, the National Institute of General Medical Sciences, the Paul and Daisy Soros Fellows Program, the Dana Foundation David Mahoney Neuroimaging Grant Program, the National Institutes of Health, the Harvard-MIT Joint Research Grants Program in Basic Neuroscience, and Susan Haar.

Other authors of the paper include Norma Brown, an MIT technical associate; Marissa Hansen, a former post-baccalaureate scholar; Enrique Toloza, a graduate student at MIT and Harvard Medical School; Jitendra Sharma, an MIT research scientist; Ziv Williams, an associate professor of neurosurgery at Harvard Medical School; Matthew Frosch, an associate professor of pathology and health sciences and technology at Harvard Medical School; Garth Rees Cosgrove, director of epilepsy and functional neurosurgery at Brigham and Women’s Hospital; and Sydney Cash, an assistant professor of neurology at Harvard Medical School and Massachusetts General Hospital.

Nine MIT students awarded 2021 Paul and Daisy Soros Fellowships for New Americans

by Julia Mongo | Office of Distinguished Fellowships |

An MIT senior and eight MIT graduate students are among the 30 recipients of this year’s P.D. Soros Fellowships for New Americans. In addition to senior Fiona Chen, MIT’s newest Soros winners include graduate students Aziza Almanakly, Alaleh Azhir, Brian Y. Chang PhD ’18, James Diao, Charlie ChangWon Lee, Archana Podury, Ashwin Sah ’20, and Enrique Toloza. Six of the recipients are enrolled at the Harvard-MIT Program in Health Sciences and Technology.

P.D. Soros Fellows receive up to $90,000 to fund their graduate studies and join a lifelong community of new Americans from different backgrounds and fields. The 2021 class was selected from a pool of 2,445 applicants, marking the most competitive year in the fellowship’s history.

The Paul & Daisy Soros Fellowships for New Americans program honors the contributions of immigrants and children of immigrants to the United States. As Fiona Chen says, “Being a new American has required consistent confrontation with the struggles that immigrants and racial minorities face in the U.S. today. It has meant frequent difficulties with finding security and comfort in new contexts. But it has also meant continual growth in learning to love the parts of myself — the way I look; the things that my family and I value — that have marked me as different, or as an outsider.”

Students interested in applying to the P.D. Soros fellowship should contact Kim Benard, assistant dean of distinguished fellowships in Career Advising and Professional Development.

Aziza Almanakly

Aziza Almanakly, a PhD student in electrical engineering and computer science, researches microwave quantum optics with superconducting qubits for quantum communication under Professor William Oliver in the Department of Physics. Almanakly’s career goal is to engineer multi-qubit systems that push boundaries in quantum technology.

Born and raised in northern New Jersey, Almanakly is the daughter of Syrian immigrants who came to the United States in the early 1990s in pursuit of academic opportunities. As the civil war in Syria grew dire, more of her relatives sought asylum in the U.S. Almanakly grew up around extended family who built a new version of their Syrian home in New Jersey.

Following in the footsteps of her mathematically minded father, Almanakly studied electrical engineering at The Cooper Union for the Advancement of Science and Art. She also pursued research opportunities in experimental quantum computing at Princeton University, the City University of New York, New York University, and Caltech.

Almanakly recognizes the importance of strong mentorship in diversifying engineering. She uses her unique experience as a New American and female engineer to encourage students from underrepresented backgrounds to enter STEM fields.

Alaleh Azhir

Alaleh Azhir grew up in Iran, where she pursued her passion for mathematics. She immigrated with her mother to the United States at age 14. Determined to overcome strict gender roles she had witnessed for women, Azhir is dedicated to improving health care for them.

Azhir graduated from Johns Hopkins University in 2019 with a perfect GPA as a triple major in biomedical engineering, computer science, and applied mathematics and statistics. A Rhodes and Barry Goldwater Scholar, she has developed many novel tools for visualization and analysis of genomics data at Johns Hopkins University, Harvard University, MIT, the National Institutes of Health, and laboratories in Switzerland.

After completing a master’s in statistical science at Oxford University, Azhir began her MD studies in the Harvard-MIT Program in Health Sciences and Technology. Her thesis focuses on the role of X and Y sex chromosomes on disease manifestations. Through medical training, she aims to build further computational tools specifically for preventive care for women. She has also founded and directs the nonprofit organization, Frappa, aimed at mentoring women living in Iran and helping them to immigrate abroad through the graduate school application process.

Brian Y. Chang PhD ’18

Born in Johnson City, New York, Brian Y. Chang PhD ’18 is the son of immigrants from the Shanghai municipality and Shandong Province in China. He pursued undergraduate and master’s degrees in mechanical engineering at Carnegie Mellon University, graduating in a combined four years with honors.

In 2018, Chang completed a PhD in medical engineering at MIT. Under the mentorship of Professor Elazer Edelman, Chang developed methods that make advanced cardiac technologies more accessible. The resulting approaches are used in hospitals around the world. Chang has published extensively and holds five patents.

With the goal of harnessing the power of engineering to improve patient care, Chang co-founded X-COR Therapeutics, a seed-funded medical device startup developing a more accessible treatment for lung failure with the potential to support patients with severe Covid-19 and chronic obstructive pulmonary disease.

After spending time in the hospital connecting with patients and teaching cardiovascular pathophysiology to medical students, Chang decided to attend medical school. He is currently a medical student in the Harvard-MIT Program in Health Sciences and Technology. Chang hopes to advance health care through medical device innovation and education as a future physician-scientist, entrepreneur, and educator.

Fiona Chen

MIT senior Fiona Chen was born in Cedar Park, Texas, the daughter of immigrants from China. Witnessing how her own and many other immigrant families faced significant difficulties finding work and financial stability sparked her interest in learning about poverty and economic inequality.

At MIT, Chen has pursued degrees in economics and mathematics. Her economics research projects have examined important policy issues — social isolation among students, global development and poverty, universal health-care systems, and the role of technology in shaping the labor market.

An active member of the MIT community, Chen has served as the officer on governance and officer on policy of the Undergraduate Association, MIT’s student government; the opinion editor of The Tech student newspaper; the undergraduate representative of several Institute-wide committees, including MIT’s Corporation Joint Advisory Committee; and one of the founding members of MIT Students Against War. In each of these roles, she has worked to advocate for policies to support underrepresented groups at MIT.

As a Soros fellow, Chen will pursue a PhD in economics to deepen her understanding of economic policy. Her ultimate goal is to become a professor who researches poverty and economic inequality, and applies her findings to craft policy solutions.

James Diao

James Diao graduated from Yale University with degrees in statistics and biochemistry and is currently a medical student at the Harvard-MIT Program in Health Sciences and Technology. He aspires to give voice to patient perspectives in the development and evaluation of health-care technology.

Diao grew up in Houston’s Chinatown, and spent summers with his extended family in Jiangxian. Diao’s family later moved to Fort Bend, Texas, where he found a pediatric oncologist mentor who introduced him to the wonders of modern molecular biology.

Diao’s interests include the responsible development of technology. At Apple, he led projects to validate wearable health features in diverse populations; at PathAI, he built deep learning models to broaden access to pathologist services; at Yale, where he worked on standardizing analyses of exRNA biomarkers; and at Harvard, he studied the impacts of clinical guidelines on marginalized groups.

Diao’s lead author research in the New England Journal of Medicine and JAMA systematically compared race-based and race-free equations for kidney function, and demonstrated that up to 1 million Black Americans may receive unequal kidney care due to their race. He has also published articles on machine learning and precision medicine.

Charlie ChangWon Lee

Born in Seoul, South Korea, Charlie ChangWon Lee was 10 when his family immigrated to the United States and settled in Palisades Park, New Jersey. The stress of his parents’ lack of health coverage ignited Lee’s determination to study the reasons for the high cost of health care in the U.S. and learn how to care for uninsured families like his own.

Lee graduated summa cum laude in integrative biology from Harvard College, winning the Hoopes Prize for his thesis on the therapeutic potential of human gut microbes. Lee’s research on novel therapies led him to question how newly approved, and expensive, medications could reach more patients.

At the Program on Regulation, Therapeutics, and Law (PORTAL) at Brigham and Women’s Hospital, Lee studied policy issues involving pharmaceutical drug pricing, drug development, and medication use and safety. His articles have appeared in JAMA, Health Affairs, and Mayo Clinic Proceedings.

As a first-year medical student at the Harvard-MIT Health Sciences and Technology program, Lee is investigating policies to incentivize vaccine and biosimilar drug development. He hopes to find avenues to bridge science and policy and translate medical innovations into accessible, affordable therapies.

Archana Podury

The daughter of Indian immigrants, Archana Podury was born in Mountain View, California. As an undergraduate at Cornell University, she studied the neural circuits underlying motor learning. Her growing interest in whole-brain dynamics led her to the Princeton Neuroscience Institute and Neuralink, where she discovered how brain-machine interfaces could be used to understand diffuse networks in the brain.

While studying neural circuits, Podury worked at a syringe exchange in Ithaca, New York, where she witnessed firsthand the mechanics of court-based drug rehabilitation. Now, as an MD student in the Harvard-MIT Health Sciences and Technology program, Podury is interested in combining computational and social approaches to neuropsychiatric disease.

In the Boyden Lab at the MIT McGovern Institute for Brain Research, Podury is developing human brain organoid models to better characterize circuit dysfunction in neurodevelopmental disorders. Concurrently, her work in the Dhand Lab at Brigham and Women’s Hospital applies network science tools to understand how patients’ social environments influence their health outcomes following acute neurological injury.

Podury hopes that focusing on both neural and social networks can lead toward a more comprehensive, and compassionate, approach to health and disease.

Ashwin Sah ’20

Ashwin Sah ’20 was born and raised in Portland, Oregon, the son of Indian immigrants. He developed a passion for mathematics research as an undergraduate at MIT, where he conducted research under Professor Yufei Zhao, as well as at the Duluth and Emory REU (Research Experience for Undergraduates) programs.

Sah has given talks on his work at multiple professional venues. His undergraduate research in varied areas of combinatorics and discrete mathematics culminated in the Barry Goldwater Scholarship and the Frank and Brennie Morgan Prize for Outstanding Research in Mathematics by an Undergraduate Student. Additionally, his work on diagonal Ramsey numbers was recently featured in Quanta Magazine.

Beyond research, Sah has pursued opportunities to give back to the math community, helping to organize or grade competitions such as the Harvard-MIT Mathematics Tournament and the USA Mathematical Olympiad. He has also been a grader at the Mathematical Olympiad Program, a camp for talented high-school students in the United States, and an instructor for the Monsoon Math Camp, a virtual program aimed at teaching higher mathematics to high school students in India.

Sah is currently a PhD student in mathematics at MIT, where he continues to work with Zhao.

Enrique Toloza

Enrique Toloza was born in Los Angeles, California, the child of two immigrants: one from Colombia who came to the United States for a PhD and the other from the Philippines who grew up in California and went on to medical school. Their literal marriage of science and medicine inspired Toloza to become a physician-scientist.

Toloza majored in physics and Spanish literature at the University of North Carolina at Chapel Hill. He eventually settled on an interest in theoretical neuroscience after a summer research internship at MIT and completing an honors thesis on noninvasive brain stimulation.

After college, Toloza joined Professor Mark Harnett’s laboratory at MIT for a year. He went on to enroll in the Harvard-MIT MD/PhD program, studying within the Health Sciences and Technology MD curriculum at Harvard and the PhD program at MIT. For his PhD, Toloza rejoined Harnett to conduct research on the biophysics of dendritic integration and the contribution of dendrites to cortical computations in the brain.

Toloza is passionate about expanding health care access to immigrant populations. In college, he led the interpreting team at the University of North Carolina at Chapel Hill’s student-run health clinic; at Harvard Medical School, he has worked with Spanish-speaking patients as a student clinician.

How the brain encodes landmarks that help us navigate

Anne Trafton |

When we move through the streets of our neighborhood, we often use familiar landmarks to help us navigate. And as we think to ourselves, “OK, now make a left at the coffee shop,” a part of the brain called the retrosplenial cortex (RSC) lights up.

While many studies have linked this brain region with landmark-based navigation, exactly how it helps us find our way is not well-understood. A new study from MIT neuroscientists now reveals how neurons in the RSC use both visual and spatial information to encode specific landmarks.

“There’s a synthesis of some of these signals — visual inputs and body motion — to represent concepts like landmarks,” says Mark Harnett, an assistant professor of brain and cognitive sciences and a member of MIT’s McGovern Institute for Brain Research. “What we went after in this study is the neuron-level and population-level representation of these different aspects of spatial navigation.”

In a study of mice, the researchers found that this brain region creates a “landmark code” by combining visual information about the surrounding environment with spatial feedback of the mice’s own position along a track. Integrating these two sources of information allowed the mice to learn where to find a reward, based on landmarks that they saw.

“We believe that this code that we found, which is really locked to the landmarks, and also gives the animals a way to discriminate between landmarks, contributes to the animals’ ability to use those landmarks to find rewards,” says Lukas Fischer, an MIT postdoc and the lead author of the study.

Harnett is the senior author of the study, which appears today in the journal eLife. Other authors are graduate student Raul Mojica Soto-Albors and recent MIT graduate Friederike Buck.

Encoding landmarks

Previous studies have found that people with damage to the RSC have trouble finding their way from one place to another, even though they can still recognize their surroundings. The RSC is also one of the first areas affected in Alzheimer’s patients, who often have trouble navigating.

The RSC is wedged between the primary visual cortex and the motor cortex, and it receives input from both of those areas. It also appears to be involved in combining two types of representations of space — allocentric, meaning the relationship of objects to each other, and egocentric, meaning the relationship of objects to the viewer.

“The evidence suggests that RSC is really a place where you have a fusion of these different frames of reference,” Harnett says. “Things look different when I move around in the room, but that’s because my vantage point has changed. They’re not changing with respect to one another.”

In this study, the MIT team set out to analyze the behavior of individual RSC neurons in mice, including how they integrate multiple inputs that help with navigation. To do that, they created a virtual reality environment for the mice by allowing them to run on a treadmill while they watch a video screen that makes it appear they are running along a track. The speed of the video is determined by how fast the mice run.

At specific points along the track, landmarks appear, signaling that there’s a reward available a certain distance beyond the landmark. The mice had to learn to distinguish between two different landmarks, and to learn how far beyond each one they had to run to get the reward.

Once the mice learned the task, the researchers recorded neural activity in the RSC as the animals ran along the virtual track. They were able to record from a few hundred neurons at a time, and found that most of them anchored their activity to a specific aspect of the task.

There were three primary anchoring points: the beginning of the trial, the landmark, and the reward point. The majority of the neurons were anchored to the landmarks, meaning that their activity would consistently peak at a specific point relative to the landmark, say 50 centimeters before it or 20 centimeters after it.

Most of those neurons responded to both of the landmarks, but a small subset responded to only one or the other. The researchers hypothesize that those strongly selective neurons help the mice to distinguish between the landmarks and run the correct distance to get the reward.

When the researchers used optogenetics (a tool that can turn off neuron activity) to block activity in the RSC, the mice’s performance on the task became much worse.

Combining inputs

The researchers also did an experiment in which the mice could choose to run or not while the video played at a constant speed, unrelated to the mice’s movement. The mice could still see the landmarks, but the location of the landmarks was no longer linked to a reward or to the animals’ own behavior. In that situation, RSC neurons did respond to the landmarks, but not as strongly as they did when the mice were using them for navigation.

Further experiments allowed the researchers to tease out just how much neuron activation is produced by visual input (seeing the landmarks) and by feedback on the mouse’s own movement. However, simply adding those two numbers yielded totals much lower than the neuron activity seen when the mice were actively navigating the track.

“We believe that is evidence for a mechanism of nonlinear integration of these inputs, where they get combined in a way that creates a larger response than what you would get if you just added up those two inputs in a linear fashion,” Fischer says.

The researchers now plan to analyze data that they have already collected on how neuron activity evolves over time as the mice learn the task. They also hope to perform further experiments in which they could try to separately measure visual and spatial inputs into different locations within RSC neurons.

The research was funded by the National Institutes of Health, the McGovern Institute, the NEC Corporation Fund for Research in Computers and Communications at MIT, and the Klingenstein-Simons Fellowship in Neuroscience.

Single neurons can encode distinct landmarks

by Sabbi Lall |

The organization of many neurons wired together in a complex circuit gives the brain its ability to perform powerful calculations. Work from the Harnett lab recently showed that even single neurons can process more information than previously thought, representing distinct variables at the subcellular level during behavior.

McGovern Investigator Mark Harnett and postdoc Jakob Voigts conducted an extremely delicate and intricate imaging experiment on different parts of the same neuron in the mouse retinosplenial cortex during 2-D navigation. Their set up allowed 2-photon imaging of neuronal sub-compartments during free 2-D navigation with head rotation, the latter being important to follow neural activity during naturalistic, complex behavior.

Recording computation by subcompartments in neurons.

 

In the work, published recently in Neuron, the authors used Ca2+-imaging to show that the soma in a single neuron was consistently active when mice were at particular landmarks as they navigated in an arena. The dendrites (tree-like antennas that receive input from other neurons) of exactly the same neuron were robustly active independent of the soma at distinct positions and orientations in the arena. This strongly suggests that the dendrites encode distinct information compared to their parent soma, in this case spatial variables during navigation, laying the foundation for studying sub-cellular processes during complex behaviors.

 

Mark Harnett receives a 2019 McKnight Scholar Award

Anne Trafton |

McGovern Institute investigator Mark Harnett is one of six young researchers selected to receive a prestigious 2019 McKnight Scholar Award. The award supports his research “studying how dendrites, the antenna-like input structures of neurons, contribute to computation in neural networks.”

Harnett examines the biophysical properties of single neurons, ultimately aiming to understand how these relate to the complex computations that underlie behavior. His lab was the first to examine the biophysical properties of human dendrites. The Harnett lab found that human neurons have distinct properties, including increased dendritic compartmentalization that could allow more complex computations within single neurons. His lab recently discovered that such dendritic computations are not rare, or confined to specific behaviors, but are a widespread and general feature of neuronal activity.

“As a young investigator, it is hard to prioritize so many exciting directions and ideas,” explains Harnett. “I really want to thank the McKnight Foundation, both for the support, but also for the hard work the award committee puts into carefully thinking about and giving feedback on proposals. It means a lot to get this type of endorsement from a seriously committed and distinguished committee, and their support gives even stronger impetus to pursue this research direction.”

The McKnight Foundation has supported neuroscience research since 1977, and provides three prominent awards, with the Scholar award aimed at supporting young scientists, and drawing applications from the strongest young neuroscience faculty across the US. William L. McKnight (1887-1979) was an early leader of the 3M Company and had a personal interest in memory and brain diseases. The McKnight Foundation was established with this focus in mind, and the Scholar Award provides $75,000 per year for three years to support cutting edge neuroscience research.

 

Antenna-like inputs unexpectedly active in neural computation

Anne Trafton |

Most neurons have many branching extensions called dendrites that receive input from thousands of other neurons. Dendrites aren’t just passive information-carriers, however. According to a new study from MIT, they appear to play a surprisingly large role in neurons’ ability to translate incoming signals into electrical activity.

Neuroscientists had previously suspected that dendrites might be active only rarely, under specific circumstances, but the MIT team found that dendrites are nearly always active when the main cell body of the neuron is active.

“It seems like dendritic spikes are an intrinsic feature of how neurons in our brain can compute information. They’re not a rare event,” says Lou Beaulieu-Laroche, an MIT graduate student and the lead author of the study. “All the neurons that we looked at had these dendritic spikes, and they had dendritic spikes very frequently.”

The findings suggest that the role of dendrites in the brain’s computational ability is much larger than had previously been thought, says Mark Harnett, who is the Fred and Carole Middleton Career Development Assistant Professor of Brain and Cognitive Sciences, a member of the McGovern Institute for Brain Research, and the senior author of the paper.

“It’s really quite different than how the field had been thinking about this,” he says. “This is evidence that dendrites are actively engaged in producing and shaping the outputs of neurons.”

Graduate student Enrique Toloza and technical associate Norma Brown are also authors of the paper, which appears in Neuron on June 6.

“A far-flung antenna”

Dendrites receive input from many other neurons and carry those signals to the cell body, also called the soma. If stimulated enough, a neuron fires an action potential — an electrical impulse that spreads to other neurons. Large networks of these neurons communicate with each other to perform complex cognitive tasks such as producing speech.

Through imaging and electrical recording, neuroscientists have learned a great deal about the anatomical and functional differences between different types of neurons in the brain’s cortex, but little is known about how they incorporate dendritic inputs and decide whether to fire an action potential. Dendrites give neurons their characteristic branching tree shape, and the size of the “dendritic arbor” far exceeds the size of the soma.

“It’s an enormous, far-flung antenna that’s listening to thousands of synaptic inputs distributed in space along that branching structure from all the other neurons in the network,” Harnett says.

Some neuroscientists have hypothesized that dendrites are active only rarely, while others thought it possible that dendrites play a more central role in neurons’ overall activity. Until now, it has been difficult to test which of these ideas is more accurate, Harnett says.

To explore dendrites’ role in neural computation, the MIT team used calcium imaging to simultaneously measure activity in both the soma and dendrites of individual neurons in the visual cortex of the brain. Calcium flows into neurons when they are electrically active, so this measurement allowed the researchers to compare the activity of dendrites and soma of the same neuron. The imaging was done while mice performed simple tasks such as running on a treadmill or watching a movie.

Unexpectedly, the researchers found that activity in the soma was highly correlated with dendrite activity. That is, when the soma of a particular neuron was active, the dendrites of that neuron were also active most of the time. This was particularly surprising because the animals weren’t performing any kind of cognitively demanding task, Harnett says.

“They weren’t engaged in a task where they had to really perform and call upon cognitive processes or memory. This is pretty simple, low-level processing, and already we have evidence for active dendritic processing in almost all the neurons,” he says. “We were really surprised to see that.”

Evolving patterns

The researchers don’t yet know precisely how dendritic input contributes to neurons’ overall activity, or what exactly the neurons they studied are doing.

“We know that some of those neurons respond to some visual stimuli, but we don’t necessarily know what those individual neurons are representing. All we can say is that whatever the neuron is representing, the dendrites are actively participating in that,” Beaulieu-Laroche says.

While more work remains to determine exactly how the activity in the dendrites and the soma are linked, “it is these tour-de-force in vivo measurements that are critical for explicitly testing hypotheses regarding electrical signaling in neurons,” says Marla Feller, a professor of neurobiology at the University of California at Berkeley, who was not involved in the research.

The MIT team now plans to investigate how dendritic activity contributes to overall neuronal function by manipulating dendrite activity and then measuring how it affects the activity of the cell body, Harnett says. They also plan to study whether the activity patterns they observed evolve as animals learn a new task.

“One hypothesis is that dendritic activity will actually sharpen up for representing features of a task you taught the animals, and all the other dendritic activity, and all the other somatic activity, is going to get dampened down in the rest of the cortical cells that are not involved,” Harnett says.

The research was funded by the Natural Sciences and Engineering Research Council of Canada and the U.S. National Institutes of Health.

Mark Harnett

Listening to Neurons

Mark Harnett studies how the biophysical features of individual neurons, including ion channels, receptors, and membrane electrical properties, endow neural circuits with the ability to process information and perform the complex computations that underlie behavior. As part of this work, the Harnett lab was the first to describe the physiological properties of human dendrites, the elaborate tree-like structures through which neurons receive the vast majority of their synaptic inputs. Harnett also examines how computations are instantiated in neural circuits to produce complex behaviors such as spatial navigation.

Virtual Tour of Harnett Lab

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.