brain mapping, functional connectivity, fMRI, EEG, MEG, predictive imaging, precision interventions, contrast agents, theory of mind, the developing brain, learning
The Society for Neuroscience will present its highest honor, the Ralph W. Gerard Prize in Neuroscience, to McGovern Institute Director Robert Desimone at its annual meeting today.
The Gerard Prize is named for neuroscientist Ralph W. Gerard who helped establish the Society for Neuroscience, and honors “outstanding scientists who have made significant contributions to neuroscience throughout their careers.” Desimone will share the $30,000 prize with Vanderbilt University neuroscientist Jon Kaas.
Desimone is being recognized for his career contributions to understanding cortical function in the visual system. His seminal work on attention spans decades, including the discovery of a neural basis for covert attention in the temporal cortex and the creation of the biased competition model, suggesting that attention is biased towards material relevant to the task. More recent work revealed how synchronized brain rhythms help enhance visual processing. Desimone also helped discover both face cells and neural populations that identify objects even when the size or location of the object changes. His long list of contributions includes mapping the extrastriate visual cortex, publishing the first report of columns for motion processing outside the primary visual cortex, and discovering how the temporal cortex retains memories. Desimone’s work has moved the field from broad strokes of input and output to a more nuanced understanding of cortical function that allows the brain to make sense of the environment.
At its annual meeting, beginning today, the Society will honor Desimone and other leading researchers who have made significant contributions to neuroscience — including the understanding of cognitive processes, drug addiction, neuropharmacology, and theoretical models — with this year’s Outstanding Achievement Awards.
“The Society is honored to recognize this year’s awardees, whose groundbreaking research has revolutionized our understanding of the brain, from the level of the synapse to the structure and function of the cortex, shedding light on how vision, memory, perception of touch and pain, and drug
addiction are organized in the brain,” SfN President Barry Everitt, said. “This exceptional group of neuroscientists has made fundamental discoveries, paved the way for new therapeutic approaches, and introduced new tools that will lay the foundation for decades of research to come.”
The lateral prefrontal cortex is a particularly well-connected part of the brain. Neurons there communicate with processing centers throughout the rest of the brain, gathering information and sending commands to implement executive control over behavior. Now, scientists at MIT’s McGovern Institute have mapped these connections and revealed an unexpected order within them: The lateral prefrontal cortex, they’ve found, contains maps of other major parts of the brain’s cortex.
The researchers, led by postdoctoral researcher Rui Xu and McGovern Institute Director Robert Desimone, report that the lateral prefrontal cortex contains a set of maps that represent the major processing centers in the other parts of the cortex, including the temporal and parietal lobes. Their organization likely supports the lateral prefrontal cortex’s roles managing complex functions such as attention and working memory, which require integrating information from multiple sources and coordinating activity elsewhere in the brain. The findings are published November 4, 2021, in the journal Neuron.
Topographic maps
The layout of the maps, which allows certain regions of the lateral prefrontal cortex to directly interact with multiple areas across the brain, indicates that this part of the brain is particularly well positioned for its role. “This function of integrating and then sending back control signals to appropriate levels in the processing hierarchies of the brain is clearly one of the reasons that prefrontal cortex is so important for cognition and executive control,” says Desimone.
In many parts of the brain, neurons’ physical organization has been found to reflect the information represented there. For example, individual neurons’ positions within the visual cortex mirror the layout of the cells in the retina from which they receive input, such that the spatial pattern of neuronal activity in this part of the brain provides an approximate view of the image seen by the eyes. For example, if you fixate on the first letter of a word, the next letters in the word will map to sequential locations in the visual cortex. Likewise, the arm and hand are mapped to adjacent locations in the somatic cortex, where the brain receives sensory information from the skin.
Topographic maps such as these, which have been found primarily in brain regions involved in sensory and motor processing, offer clues about how information is stored and processed in the brain. Neuroscientists have hoped that topographic maps within the lateral prefrontal cortex will provide insight into the complex cognitive processes that are carried out there—but such maps have been elusive.
Previous anatomical studies had given little indication how different parts of the brain communicate preferentially to specific locations within the prefrontal cortex to give rise to regional specialization of cognitive functions. Recently, however, the Desimone lab identified two areas within the lateral prefrontal cortex of monkeys with specific roles in focusing an animal’s visual attention. Knowing that some spots within the lateral prefrontal cortex were wired for specific functions, they wondered if others were, too. They decided they needed a detailed map of the connections emanating from this part of the brain, and devised a plan to plot connectivity from hundreds of points within the lateral prefrontal cortex.
Cortical connectome
To generate a wiring diagram, or connectome, Xu used functional MRI to monitor activity throughout a monkey’s brain as he stimulated specific points within its lateral prefrontal cortex. He moved systematically through the brain region, stimulating points spaced as close as one millimeter apart, and noting which parts of the brain lit up in response. Ultimately, the team collected data from about 100 sites for each of two monkeys.
As the data accumulated, clear patterns emerged. Different regions within the lateral prefrontal cortex formed orderly connections with each of five processing centers throughout the brain. Points within each of these maps connected to sites with the same relative positions in the distant processing centers. Because some parts of the lateral prefrontal cortex are wired to interact with more than one processing centers, these maps overlap, positioning the prefrontal cortex to integrate information from different sources.
The team found significant overlap, for example, between the maps of the temporal cortex, a part of the brain that uses visual information to recognize objects, and the parietal cortex, which computes the spatial relationships between objects. “It is mapping objects and space together in a way that would integrate the two systems,” explains Desimone. “And then on top of that, it has other maps of other brain systems that are partially overlapping with that—so they’re all sort of coming together.”
Desimone and Xu say the new connectome will help guide further investigations of how the prefrontal cortex orchestrates complex cognitive processes. “I think this really gives us a direction for the future, because we now need to understand the cognitive concepts that are mapped there,” Desimone says.
Already, they say, the connectome offers encouragement that a deeper understanding of complex cognition is within reach. “This topographic connectivity gives the lateral prefrontal some specific advantage to serve its function,” says Xu. “This suggests that lateral prefrontal cortex has a fine organization, just like the more studied parts of the brain, so the approaches that have been used to study these other regions may also benefit the studies of high-level cognition.”
In the past few years, artificial intelligence models of language have become very good at certain tasks. Most notably, they excel at predicting the next word in a string of text; this technology helps search engines and texting apps predict the next word you are going to type.
The most recent generation of predictive language models also appears to learn something about the underlying meaning of language. These models can not only predict the word that comes next, but also perform tasks that seem to require some degree of genuine understanding, such as question answering, document summarization, and story completion.
Such models were designed to optimize performance for the specific function of predicting text, without attempting to mimic anything about how the human brain performs this task or understands language. But a new study from MIT neuroscientists suggests the underlying function of these models resembles the function of language-processing centers in the human brain.
Computer models that perform well on other types of language tasks do not show this similarity to the human brain, offering evidence that the human brain may use next-word prediction to drive language processing.
“The better the model is at predicting the next word, the more closely it fits the human brain,” says Nancy Kanwisher, the Walter A. Rosenblith Professor of Cognitive Neuroscience, a member of MIT’s McGovern Institute for Brain Research and Center for Brains, Minds, and Machines (CBMM), and an author of the new study. “It’s amazing that the models fit so well, and it very indirectly suggests that maybe what the human language system is doing is predicting what’s going to happen next.”
Joshua Tenenbaum, a professor of computational cognitive science at MIT and a member of CBMM and MIT’s Artificial Intelligence Laboratory (CSAIL); and Evelina Fedorenko, the Frederick A. and Carole J. Middleton Career Development Associate Professor of Neuroscience and a member of the McGovern Institute, are the senior authors of the study, which appears this week in the Proceedings of the National Academy of Sciences.
Martin Schrimpf, an MIT graduate student who works in CBMM, is the first author of the paper.
Making predictions
The new, high-performing next-word prediction models belong to a class of models called deep neural networks. These networks contain computational “nodes” that form connections of varying strength, and layers that pass information between each other in prescribed ways.
Over the past decade, scientists have used deep neural networks to create models of vision that can recognize objects as well as the primate brain does. Research at MIT has also shown that the underlying function of visual object recognition models matches the organization of the primate visual cortex, even though those computer models were not specifically designed to mimic the brain.
In the new study, the MIT team used a similar approach to compare language-processing centers in the human brain with language-processing models. The researchers analyzed 43 different language models, including several that are optimized for next-word prediction. These include a model called GPT-3 (Generative Pre-trained Transformer 3), which, given a prompt, can generate text similar to what a human would produce. Other models were designed to perform different language tasks, such as filling in a blank in a sentence.
As each model was presented with a string of words, the researchers measured the activity of the nodes that make up the network. They then compared these patterns to activity in the human brain, measured in subjects performing three language tasks: listening to stories, reading sentences one at a time, and reading sentences in which one word is revealed at a time. These human datasets included functional magnetic resonance (fMRI) data and intracranial electrocorticographic measurements taken in people undergoing brain surgery for epilepsy.
They found that the best-performing next-word prediction models had activity patterns that very closely resembled those seen in the human brain. Activity in those same models was also highly correlated with measures of human behavioral measures such as how fast people were able to read the text.
“We found that the models that predict the neural responses well also tend to best predict human behavior responses, in the form of reading times. And then both of these are explained by the model performance on next-word prediction. This triangle really connects everything together,” Schrimpf says.
“A key takeaway from this work is that language processing is a highly constrained problem: The best solutions to it that AI engineers have created end up being similar, as this paper shows, to the solutions found by the evolutionary process that created the human brain. Since the AI network didn’t seek to mimic the brain directly — but does end up looking brain-like — this suggests that, in a sense, a kind of convergent evolution has occurred between AI and nature,” says Daniel Yamins, an assistant professor of psychology and computer science at Stanford University, who was not involved in the study.
Game changer
One of the key computational features of predictive models such as GPT-3 is an element known as a forward one-way predictive transformer. This kind of transformer is able to make predictions of what is going to come next, based on previous sequences. A significant feature of this transformer is that it can make predictions based on a very long prior context (hundreds of words), not just the last few words.
Scientists have not found any brain circuits or learning mechanisms that correspond to this type of processing, Tenenbaum says. However, the new findings are consistent with hypotheses that have been previously proposed that prediction is one of the key functions in language processing, he says.
“One of the challenges of language processing is the real-time aspect of it,” he says. “Language comes in, and you have to keep up with it and be able to make sense of it in real time.”
The researchers now plan to build variants of these language processing models to see how small changes in their architecture affect their performance and their ability to fit human neural data.
“For me, this result has been a game changer,” Fedorenko says. “It’s totally transforming my research program, because I would not have predicted that in my lifetime we would get to these computationally explicit models that capture enough about the brain so that we can actually leverage them in understanding how the brain works.”
The researchers also plan to try to combine these high-performing language models with some computer models Tenenbaum’s lab has previously developed that can perform other kinds of tasks such as constructing perceptual representations of the physical world.
“If we’re able to understand what these language models do and how they can connect to models which do things that are more like perceiving and thinking, then that can give us more integrative models of how things work in the brain,” Tenenbaum says. “This could take us toward better artificial intelligence models, as well as giving us better models of how more of the brain works and how general intelligence emerges, than we’ve had in the past.”
The research was funded by a Takeda Fellowship; the MIT Shoemaker Fellowship; the Semiconductor Research Corporation; the MIT Media Lab Consortia; the MIT Singleton Fellowship; the MIT Presidential Graduate Fellowship; the Friends of the McGovern Institute Fellowship; the MIT Center for Brains, Minds, and Machines, through the National Science Foundation; the National Institutes of Health; MIT’s Department of Brain and Cognitive Sciences; and the McGovern Institute.
Other authors of the paper are Idan Blank PhD ’16 and graduate students Greta Tuckute, Carina Kauf, and Eghbal Hosseini.
A deepening understanding of the brain has created unprecedented opportunities to alleviate the challenges posed by disability. Scientists and engineers are taking design cues from biology itself to create revolutionary technologies that restore the function of bodies affected by injury, aging, or disease – from prosthetic limbs that effortlessly navigate tricky terrain to digital nervous systems that move the body after a spinal cord injury.
With the establishment of the new K. Lisa Yang Center for Bionics, MIT is pushing forward the development and deployment of enabling technologies that communicate directly with the nervous system to mitigate a broad range of disabilities. The center’s scientists, clinicians, and engineers will work together to create, test, and disseminate bionic technologies that integrate with both the body and mind.
The center is funded by a $24 million gift to MIT’s McGovern Institute for Brain Research from philanthropist Lisa Yang, a former investment banker committed to advocacy for individuals with visible and invisible disabilities.
Philanthropist Lisa Yang is committed to advocacy for individuals with visible and invisible disabilities. Photo: Caitlin Cunningham
“The K. Lisa Yang Center for Bionics will provide a dynamic hub for scientists, engineers and designers across MIT to work together on revolutionary answers to the challenges of disability,” says MIT President L. Rafael Reif. “With this visionary gift, Lisa Yang is unleashing a powerful collaborative strategy that will have broad impact across a large spectrum of human conditions – and she is sending a bright signal to the world that the lives of individuals who experience disability matter deeply.”
An interdisciplinary approach
To develop prosthetic limbs that move as the brain commands or optical devices that bypass an injured spinal cord to stimulate muscles, bionic developers must integrate knowledge from a diverse array of fields—from robotics and artificial intelligence to surgery, biomechanics, and design. The K. Lisa Yang Center for Bionics will be deeply interdisciplinary, uniting experts from three MIT schools: Science, Engineering, and Architecture and Planning. With clinical and surgical collaborators at Harvard Medical School, the center will ensure that research advances are tested rapidly and reach people in need, including those in traditionally underserved communities.
To support ongoing efforts to move toward a future without disability, the center will also provide four endowed fellowships for MIT graduate students working in bionics or other research areas focused on improving the lives of individuals who experience disability.
“I am thrilled to support MIT on this major research effort to enable powerful new solutions that improve the quality of life for individuals who experience disability,” says Yang. “This new commitment extends my philanthropic investment into the realm of physical disabilities, and I look forward to the center’s positive impact on countless lives, here in the US and abroad.”
The center will be led by Hugh Herr, a professor of media arts and sciences at MIT’s Media Lab, and Ed Boyden, the Y. Eva Tan Professor of Neurotechnology at MIT, a professor of biological engineering, brain and cognitive sciences, and media arts and sciences, and an investigator at MIT’s McGovern Institute and the Howard Hughes Medical Institute.
A double amputee himself, Herr is a pioneer in the development of bionic limbs to improve mobility for those with physical disabilities. “The world profoundly needs relief from the disabilities imposed by today’s nonexistent or broken technologies. We must continually strive towards a technological future in which disability is no longer a common life experience,” says Herr. “I am thrilled that the Yang Center for Bionics will help to measurably improve the human experience for so many.”
Boyden, who is a renowned creator of tools to analyze and control the brain, will play a key role in merging bionics technologies with the nervous system. “The Yang Center for Bionics will be a research center unlike any other in the world,” he says. “A deep understanding of complex biological systems, coupled with rapid advances in human-machine bionic interfaces, mean we will soon have the capability to offer entirely new strategies for individuals who experience disability. It is an honor to be part of the center’s founding team.”
Center priorities
In its first four years, the K. Lisa Yang Center for Bionics will focus on developing and testing three bionic technologies:
Digital nervous system: to eliminate movement disorders caused by spinal cord injuries, using computer-controlled muscle activations to control limb movements while simultaneously stimulating spinal cord repair
Brain-controlled limb exoskeletons: to assist weak muscles and enable natural movement for people affected by stroke or musculoskeletal disorders
Bionic limb reconstruction: to restore natural, brain-controlled movements as well as the sensation of touch and proprioception (awareness of position and movement) from bionic limbs
A fourth priority will be developing a mobile delivery system to ensure patients in medically underserved communities have access to prosthetic limb services. Investigators will field test a system that uses a mobile clinic to conduct the medical imaging needed to design personalized, comfortable prosthetic limbs and to fit the prostheses to patients where they live. Investigators plan to initially bring this mobile delivery system to Sierra Leone, where thousands of people suffered amputations during the country’s 11-year civil war. While the population of persons with amputation continues to increase each year in Sierra Leone, today less than 10% of persons in need benefit from functional prostheses. Through the mobile delivery system, a key center objective is to scale up production and access of functional limb prostheses for Sierra Leoneans in dire need.
Philanthropist Lisa Yang (far left) and MIT bionics researcher Hugh Herr (second from left) met with Sierra Leone’s President Julius Maada Bio (second from right) and Chief Innovation Officer for the Directorate of Science, Technology and Innovation, David Moinina Sengeh, to discuss the mobile clinic component of the new K. Lisa Yang Center for Bionics at MIT. Photo: David Moinina Sengeh
“The mobile prosthetics service fueled by the K. Lisa Yang Center for Bionics at MIT is an innovative solution to a global problem,” said Julius Maada Bio, President of Sierra Leone. “I am proud that Sierra Leone will be the first site for deploying this state-of-the-art digital design and fabrication process. As leader of a government that promotes innovative technologies and prioritizes human capital development, I am overjoyed that this pilot project will give Sierra Leoneans (especially in rural areas) access to quality limb prostheses and thus improve their quality of life.”
Together, Herr and Boyden will launch research at the bionics center with three other MIT faculty: Assistant Professor of Media Arts and Sciences Canan Dagdeviren, Walter A. Rosenblith Professor of Cognitive Neuroscience Nancy Kanwisher, and David H. Koch (1962) Institute Professor Robert Langer. They will work closely with three clinical collaborators at Harvard Medical School: orthopedic surgeon Marco Ferrone, plastic surgeon Matthew Carty, and Nancy Oriol, Faculty Associate Dean for Community Engagement in Medical Education.
“Lisa Yang and I share a vision for a future in which each and every person in the world has the right to live without a debilitating disability if they so choose,” adds Herr. “The Yang Center will be a potent catalyst for true innovation and impact in the bionics space, and I am overjoyed to work with my colleagues at MIT, and our accomplished clinical partners at Harvard, to make important steps forward to help realize this vision.”
Jaqueline Lees and Rebecca Saxe have been named associate deans serving in the MIT School of Science. Lees is the Virginia and D.K. Ludwig Professor for Cancer Research and is currently the associate director of the Koch Institute for Integrative Cancer Research, as well as an associate department head and professor in the Department of Biology at MIT. Saxe is the John W. Jarve (1978) Professor in Brain and Cognitive Sciences and the associate head of the Department of Brain and Cognitive Sciences (BCS); she is also an associate investigator in the McGovern Institute for Brain Research.
Lees and Saxe will both contribute to the school’s diversity, equity, inclusion, and justice (DEIJ) activities, as well as develop and implement mentoring and other career-development programs to support the community. From their home departments, Saxe and Lees bring years of DEIJ and mentorship experience to bear on the expansion of school-level initiatives.
Lees currently serves on the dean’s science council in her capacity as associate director of the Koch Institute. In this new role as associate dean for the School of Science, she will bring her broad administrative and programmatic experiences to bear on the next phase for DEIJ and mentoring activities.
Lees joined MIT in 1994 as a faculty member in MIT’s Koch Institute (then the Center for Cancer Research) and Department of Biology. Her research focuses on regulators that control cellular proliferation, terminal differentiation, and stemness — functions that are frequently deregulated in tumor cells. She dissects the role of these proteins in normal cell biology and development, and establish how their deregulation contributes to tumor development and metastasis.
Since 2000, she has served on the Department of Biology’s graduate program committee, and played a major role in expanding the diversity of the graduate student population. Lees also serves on DEIJ committees in her home department, as well as at the Koch Institute.
With co-chair with Boleslaw Wyslouch, director of the Laboratory for Nuclear Science, Lees led the ReseArch Scientist CAreer LadderS (RASCALS) committee tasked to evaluate career trajectories for research staff in the School of Science and make recommendations to recruit and retain talented staff, rewarding them for their contributions to the school’s research enterprise.
“Jackie is a powerhouse in translational research, demonstrating how fundamental work at the lab bench is critical for making progress at the patient bedside,” says Nergis Mavalvala, dean of the School of Science. “With Jackie’s dedicated and thoughtful partnership, we can continue to lead in basic research and develop the recruitment, retention, and mentoring and necessary to support our community.”
Saxe will join Lees in supporting and developing programming across the school that could also provide direction more broadly at the Institute.
“Rebecca is an outstanding researcher in social cognition and a dedicated educator — someone who wants our students not only to learn, but to thrive,” says Mavalvala. “I am grateful that Rebecca will join the dean’s leadership team and bring her mentorship and leadership skills to enhance the school.”
For example, in collaboration with former department head James DiCarlo, the BCS department has focused on faculty mentorship of graduate students; and, in collaboration with Professor Mark Bear, the department developed postdoc salary and benefit standards. Both initiatives have become models at MIT.
With colleague Laura Schulz, Saxe also served as co-chair of the Committee on Medical Leave and Hospitalizations (CMLH), which outlined ways to enhance MIT’s current leave and hospitalization procedures and policies for undergraduate and graduate students. Saxe was also awarded MIT’s Committed to Caring award for excellence in graduate student mentorship, as well as the School of Science’s award for excellence in undergraduate teaching.
In her research, Saxe studies human social cognition, using a combination of behavioral testing and brain imaging technologies. She is best known for her work on brain regions specialized for abstract concepts, such as “theory of mind” tasks that involve understanding the mental states of other people. Her TED Talk, “How we read each other’s minds” has been viewed more than 3 million times. She also studies the development of the human brain during early infancy.
She obtained her PhD from MIT and was a Harvard University junior fellow before joining the MIT faculty in 2006. In 2014, the National Academy of Sciences named her one of two recipients of the Troland Award for investigators age 40 or younger “to recognize unusual achievement and further empirical research in psychology regarding the relationships of consciousness and the physical world.” In 2020, Saxe was named a John Simon Guggenheim Foundation Fellow.
Saxe and Lees will also work closely with Kuheli Dutt, newly hired assistant dean for diversity, equity, and inclusion, and other members of the dean’s science council on school-level initiatives and strategy.
“I’m so grateful that Rebecca and Jackie have agreed to take on these new roles,” Mavalvala says. “And I’m super excited to work with these outstanding thought partners as we tackle the many puzzles that I come across as dean.”
Engaging children in more conversation may be all it takes to strengthen language processing networks in their brains, according to a new study by MIT scientists.
Childhood experiences, including language exposure, have a profound impact on the brain’s development. Now, scientists led by McGovern Institute investigator John Gabrieli have shown that when families change their communication style to incorporate more back-and-forth exchanges between child and adult, key brain regions grow and children’s language abilities advance. Other parts of the brain may be impacted, as well.
In a study of preschool and kindergarten-aged children and their families, Gabrieli, Harvard postdoctoral researcher Rachel Romeo, and colleagues found that increasing conversation had a measurable impact on children’s brain structure and cognition within just a few months. “In just nine weeks, fluctuations in how often parents spoke with their kids appear to make a difference in brain development, language development, and executive function development,” Gabrieli says. The team’s findings are reported in the June issue of the journal Developmental Cognitive Neuroscience.
“We’re excited because this adds a little more evidence to the idea that [the brain] is malleable,” adds Romeo, who is now an assistant professor at the University of Maryland College Park.
“It suggests that in a relatively short period of time, the brain can change in positive ways,” says Romeo.
30 million word gap
In the 1990s, researchers determined that there are dramatic discrepancies in the language that children are exposed to early in life. They found that children from high-income families heard about 30 million more words during their first three years than children from lower-income families—and those exposed to more language tended to do better on tests of language development, vocabulary, and reading comprehension.
In 2018, Gabrieli and Romeo found that it was not the volume of language that made a difference, however, but instead the extent to which children were engaged in conversation. They measured this by counting the number of “conversational turns” that children experienced over a few days—that is, the frequency with which dialogue switched between child and adult. When they compared the brains of children who experienced significantly different levels of these conversational turns, they found structural and functional differences in regions known to be involved in language and speech.
After observing these differences, the researchers wanted to know whether altering a child’s language environment would impact their brain’s future development. To find out, they enrolled the families of fifty-two children between the ages of four and seven in a study, and randomly assigned half of the families to participate in a nine-week parent training program. While the program did not focus exclusively on language, there was an emphasis on improving communication, and parents were encouraged to engage in meaningful dialogues with their children.
Romeo and colleagues sent families home with audio recording devices to capture all of the language children were exposed to over two full days, first at the outset of the program and again after the nine-week training was complete. When they analyzed the recordings, they found that in many families, conversation between children and their parents had increased—and children who experienced the greatest increase in conversational turns showed the greatest improvements in language skills as well as in executive functions—a set of skills that includes memory, attention, and self-control.
Clusters where changes in cortical thickness are significantly correlated with changes in children’s experienced conversational turns. Scatterplots represent the average change in cortical thickness as a function of the pre-to-post changes in conversational turns.
MRI scans showed that over the nine-week study, these children also experienced the most growth in two key brain areas: a sound processing center called the supramarginal gyrus and a region involved in language processing and speech production called Broca’s area. Intriguingly, these areas are very close to parts of the brain involved in executive function and social cognition.
“The brain networks for executive functioning, language, and social cognition are deeply intertwined and going through these really important periods of development during this preschool and transition-to-school period,” Romeo says. “Conversational turns seem to be going beyond just linguistic information. They seem to be about human communication and cognition at a deeper level. I think the brain results are suggestive of that, because there are so many language regions that could pop out, but these happen to be language regions that also are associated with other cognitive functions.”
Talk more
Gabrieli and Romeo say they are interested in exploring simple ways—such a web or smartphone-based tools—to support parents in communicating with their children in ways that foster brain development. It’s particularly exciting, Gabrieli notes, that introducing more conversation can impact brain development when at the age when children are preparing to begin school.
“Kids who arrive to school school-ready in language skills do better in school for years to come,” Gabrieli says. “So I think it’s really exciting to be able to see that the school readiness is so flexible and dynamic in nine weeks of experience.”
“We know this is not a trivial ask of people,” he says. “There’s a lot of factors that go into people’s lives— their own prior experiences, the pressure of their circumstances. But it’s a doable thing. You don’t have to have an expensive tutor or some deluxe pre-K environment. You can just talk more with your kid.”
Cognitive neuroscientist John Gabrieli has been named the 2021 winner of the Samuel Torrey Orton Award, the International Dyslexia Association’s highest honor. The award recognizes achievements of leading researchers and practitioners in the dyslexia field, as well as those of individuals with dyslexia who exhibit leadership and serve as role models in their communities.
“I am grateful to the International Dyslexia Association for this recognition,” said Gabrieli, who is the Grover Hermann Professor of Health Sciences and Technology, a professor of brain and cognitive sciences, and a member of MIT’s McGovern Institute for Brain Research. “The association has been such an advocate for individuals and their families who struggle with dyslexia, and has also been such a champion for the relevant science. I am humbled to join the company of previous recipients of this award who have done so much to help us understand dyslexia and how individuals with dyslexia can be supported to flourish in their growth and development.”
Gabrieli, who is also the director of MIT’s Athinoula A. Martinos Imaging Center, uses neuroimaging and behavioral tests to understand how the human brain powers learning, thinking, and feeling. For the last two decades, Gabrieli has sought to unravel the neuroscience behind learning and reading disabilities and, ultimately, convert that understanding into new and better education interventions—a sort of translational medicine for the classroom.
“We want to get every kid to be an adequate reader by the end of the third grade,” Gabrieli says. “That’s the ultimate goal: to help all children become learners.”
In March of 2018, Gabrieli and the MIT Integrated Learning Initiative—MITili, which he also directs—announced a $30 million-dollar grant from the Chan Zuckerberg Initiative for a collaboration between MIT, the Harvard Graduate School of Education, and Florida State University. This partnership, called “Reach Every Reader” aims to make significant progress on the crisis in early literacy – including tools to identify children at risk for dyslexia and other learning disabilities before they even learn to read.
“John is especially deserving of this award,” says Hugh Catts, Gabrieli’s colleague at Reach Every Reader. Catts is a professor and director of the School of Communications Science and Disorders at Florida State University. “His work has been seminal to our understanding of the neural basis of learning and learning difficulties such as dyslexia. He has been a strong advocate for individuals with dyslexia and a mentor to leading experts in the field,” says Catts, who is also received the Orton Award in 2008.
“It’s a richly deserved honor,”says Sanjay Sarma, the Fred Fort Flowers (1941) and Daniel Fort Flowers (1941) Professor of Mechanical Engineering at MIT. “John’s research is a cornerstone of MIT’s efforts to make education more equitable and accessible for all. His contributions to learning science inform so much of what we do, and his advocacy continues to raise public awareness of dyslexia and helps us better reach the dyslexic community through literacy initiatives such as Reach Every Reader. We’re so pleased that his work has been recognized with the Samuel Torrey Orton Award,” says Sarma, who is also Vice President for Open Learning at MIT.
Gabrieli will deliver the Samuel Torrey Orton and Joan Lyday Orton Memorial Lecture this fall in North Carolina as part of the 2021 International Dyslexia Association’s Annual Reading, Literacy and Learning Conference.
McGovern Investigator Ed Boyden says his lab’s vision is clear.
“We want to understand how our brains take our sensory inputs, generate emotions and memories and decisions, and ultimately result in motor outputs. We want to be able to see the building blocks of life, and how they go into disarray in brain diseases. We want to be able to control the signals of the brain, so we can repair it,” Boyden says.
To get there, he and his team are exploring the brain’s complexity at every scale, from the function and architecture of its neural networks to the molecules that work together to process information.
And when they don’t have the tools to take them where they want to go, they create them, opening new frontiers for neuroscientists everywhere.
Open to discovery
Boyden’s team is highly interdisciplinary and collaborative. Its specialty, Boyden says, is problem solving. Creativity, adaptability, and deep curiosity are essential, because while many of neuroscience’s challenges are clear, the best way to address them is not. In its search for answers, Boyden’s lab is betting that an important path to discovery begins with finding new ways to explore.
They’ve made that possible with an innovative imaging approach called expansion microscopy (ExM). ExM physically enlarges biological samples so that minute details become visible under a standard laboratory microscope, enabling researchers everywhere to peer into spaces that once went unseen (see video below).
To use the technique, researchers permeate a biological sample with an absorbent gel, then add water, causing the components of the gel to spread apart and the tissue to expand.
This year, postdoctoral researcher Ruixuan Gao and graduate student Chih-Chieh (Jay) Yu made the method more precise, with a new material that anchors a sample’s molecules within a crystal-like lattice, better preserving structure during expansion than the irregular mesh-like composition of the original gel. The advance is an important step toward being able to image expanded samples with single-molecule precision, Gao says.
A revealing look
By opening space within the brain, ExM has let Boyden’s team venture into those spaces in new ways.
In work led by Deblina Sarkar (who is now an assistant professor at MIT’s Media Lab), Jinyoung Kang, and Asmamaw (Oz) Wassie, they showed that they can pull apart proteins in densely packed regions like synapses so that it is easier to introduce fluorescent labels, illuminating proteins that were once too crowded to see. The process, called expansion revealing, has made it possible to visualize in intact brain tissue important structures such as ion channels that help transmit signals and fine-scale amyloid clusters in Alzheimer’s model mice.
Another reaction the lab has adapted to the expanded-brain context is RNA sequencing—an important tool for understanding cellular diversity. “Typically, the first thing you do in a sequencing project is you grind up the tissue, and you lose the spatial dimension,” explains Daniel Goodwin, a graduate student in Boyden’s lab. But when sequencing reactions are performed inside cells instead, new information is revealed.
Confocal image showing targeted ExSeq of a 34-panel gene set across a slice of mouse hippocampus. Green indicates YFP, magenta indicates reads identified with ExSeq, and white indicates reads localized within YFP-expressing cells. Image courtesy of the researchers.
Goodwin and fellow Boyden lab members Shahar Alon, Anubhav Sinha, Oz Wassie, and Fei Chen developed expansion sequencing (ExSeq), which copies RNA molecules, nucleotide by nucleotide, directly inside expanded tissue, using fluorescent labels that spell out the molecules’ codes just as they would in a sequencer.
The approach shows researchers which genes are turned on in which cells, as well as where those RNA molecules are—revealing, for example, which genes are active in the neuronal projections that carry out the brain’s communications. A next step, Sinha says, is to integrate expansion sequencing with other technologies to obtain even deeper insights.
That might include combining information revealed with ExSeq with a topographical map of the same cells’ genomes, using a method Boyden’s lab and collaborators Chen (who is now a core member of the Broad Institute) and Jason Buenrostro at Harvard have developed for DNA sequencing. That information is important because the shape of the genome varies across cells and circumstances, and that has consequences for how the genetic code is used.
Using similar techniques to those that make ExSeq possible, graduate students Andrew Payne, Zachary Chiang, and Paul Reginato figured out how to recreate the steps of commercial DNA sequencing within the genome’s natural environment.
By pinpointing the location of specific DNA sequences inside cells, the new method, called in situ genome sequencing (IGS) allows researchers to watch a genome reorganize itself in a developing embryo.
They haven’t yet performed this analysis inside expanded tissue, but Payne says integrating in situ genome sequencing (IGS) with ExM should open up new opportunities to study genomes’ structure.
Signaling clusters
Alongside these efforts, Boyden’s team is working to give researchers better tools to explore how molecules move, change, and interact, including a modular system that lets users assemble sets of sensors into clusters to simultaneously monitor multiple cellular activities.
Molecular sensors use fluorescence to report on certain changes inside cells, such as the calcium that surges into a neuron after it fires. But they come in a limited palette, so in most experiments only one or two things can be seen at once.
Graduate student Shannon Johnson and postdoctoral fellow Changyang Linghu solved this problem by putting different sensors at different points throughout a cell so they can report on different signals. Their technique, called spatial multiplexing, links sensors to molecular scaffolds designed to cling to their own kind. Sensors built on the same scaffold form islands inside cells, so when they light up their signals are distinct from those produced by other sensor islands.
Eventually, as new sensors and scaffolds become available, Johnson says the technique might be used to simultaneously follow dozens of molecular signals in living cells. The more precise information they can help people uncover, the better, Boyden says.
“My dream would be to image the signaling dynamics of the brain, and then perturb the dynamics, and then use expansion methods to make a map of the brain. If we can get those three data sets—the dynamics, the causality, and the molecular organization—I think stitching those together could potentially yield deep insights into how the brain works, and how we can repair it in disease states.”
The cerebellum is named “little brain” for its distinctive structure. Although the cerebellum was long considered only for its role in maintaining the balance and timing of movements, it has become evident that it is also important for balanced thoughts and emotions, belying the diversity of functions that “little brain” implies.
In a new study published in Schizophrenia Bulletin, McGovern Research Affiliate and Northeastern University Professor of Psychiatry Susan Whitfield-Gabrieli shows for the first time that cerebellar dysfunction actually precedes the onset of psychosis in schizophrenia, a brain disorder characterized by severe thought and emotional imbalances.
“This study exemplifies the concept of “neuroprediction,” the discovery of brain-based biomarkers that allow early detection and therefore early intervention for mental disorders,” says Whitfield-Gabrieli.
Cerebellar connectivity and schizophrenia
Early evidence that the cerebellum is involved in more than movement came from numerous reports that people with brain damage originating in the cerebellum can have severely disordered thought processes. Now cerebellar abnormalities have been identified in numerous neurodevelopmental and neuropsychiatric conditions including autism, attention-deficit hyperactivity disorder (ADHD), Alzheimer’s disease, and schizophrenia.
Whitfield-Gabrieli has focused on how symptoms in these disorders correlate with how well the cerebellum is connected to other brain regions, including regions of the cerebral cortex, the characteristically-folded, outer part of the brain. Active connections in the brain of people who are resting or who are engaged in a mental task can be found by functional magnetic resonance imaging (fMRI), a brain scanning technique that detects when and where oxygen is being used by cells. If oxygen usage in two brain regions consistently peaks at the same time while someone is in the scanner, they are considered to be functionally connected.
Connectivity differences prior to psychosis
In her new study, Whitfield-Gabrieli explored whether brain scans could reveal cerebellar abnormalities in people at-risk for schizophrenia.
To do this, she and her colleagues compared cerebellar connectivity among at-risk adolescents and young adults who went on to develop psychosis within the following year versus those that remained stable or improved. The at-risk participants were identified in an international collaboration called the Shanghai At Risk for Psychosis (SHARP) program that recruited people who were seeking help at China’s largest outpatient mental health center. Of the 144 adolescents and young adults at-risk for schizophrenia at the outset of the study, 23 went on to develop the disorder. Notably, this group showed fMRI patterns of cerebellar dysfunction at the outset of the study, before they developed psychosis.
Abnormal brain architecture
All of the brain scans were evaluated to determine the degree to which three specific cerebellar regions were connected to the cerebral cortex, a brain region that does not finish development until young adulthood. The cerebellar regions of interest to Whitfield-Gabrieli are part of the “dentate nuclei,” so named because they look like a set of jagged teeth. Neurons in the dentate nuclei serve to integrate inputs from the rest of the cerebellum and send the compiled information out to the rest of the brain. Whitfield-Gabrieli and colleagues divided the dentate nuclei into three zones according to what parts of the cerebral cortex they are functionally connected to while people are relaxing, doing visual tasks, or engaging in a motor task or receiving some sort of stimulation.
The team found abnormal connectivity for all three zones of the dentate nuclei in the individuals who later went on to develop schizophrenia. Since the connectivity patterns varied across regions within the three zones, with some regions over-connected and others under-connected to the cerebral cortex in the group that developed psychosis, separated high-resolution analyses of the different connections was key.
Previous work established that cerebellar abnormalities are associated with schizophrenia but this study is the first to show that functional connections between the deep cerebellar nuclei and the cerebral cortex might precede disease onset. “Treatments for mental disorders are inherently reactive to suffering and incapacity. A proactive approach by which abnormal brain architecture is identified prior to clinical diagnosis has the potential to prevent suffering by helping people before they become ill, one of my ultimate goals” said Whitfield-Gabrieli.
This study was supported by the Poitras Center for Psychiatric Disorders Research at MIT), US National Institute of Mental Health (R21 MH 093294, R01 MH 101052, R01 MH 111448, and R01 MH 64023), Ministry of Science and Technology of China (2016 YFC 1306803), European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 749201 and by a VA Merit Award.
by Laura Carter | School of Science + Julie Pryor | McGovern Institute |
Omar Rutledge served as a US Army infantryman in the 1st Armored and 25th Infantry Divisions. He was deployed in support of Operation Iraqi Freedom from March 2003 to July 2004. Photo: Omar Rutledge
As an Iraq war veteran, Omar Rutledge is deeply familiar with post-traumatic stress – recurring thoughts and memories that persist long after a danger has passed – and he knows that a brain altered by trauma is not easily fixed. But as a graduate student in the Department of Brain and Cognitive Sciences, Rutledge is determined to change that. He wants to understand exactly how trauma alters the brain – and whether the tools of neuroscience can be used to help fellow veterans with post-traumatic stress disorder (PTSD) heal from their experiences.
“In the world of PTSD research, I look to my left and to my right, and I don’t see other veterans, certainly not former infantrymen,” says Rutledge, who served in the US Army and was deployed to Iraq from March 2003 to July 2004. “If there are so few of us in this space, I feel like I have an obligation to make a difference for all who suffer from the traumatic experiences of war.”
Rutledge is uniquely positioned to make such a difference in the lab of McGovern Investigator John Gabrieli, where researchers use technologies like magnetic resonance imaging (MRI), electroencephalography (EEG), and magnetoencephalography (MEG) to peer into the human brain and explore how it powers our thoughts, memories, and emotions. Rutledge is studying how PTSD weakens the connection between the amygdala, which is responsible for emotions like fear, and the prefrontal cortex, which regulates or controls these emotional responses. He hopes these studies will eventually lead to the development of wearable technologies that can retrain the brain to be less responsive to triggering events.
“I feel like it has been a mission of mine to do this kind of work.”
Though Covid-19 has unexpectedly paused some aspects of his research, Rutledge is pursuing another line of research inspired both by the mandatory social distancing protocols imposed during the lockdown and his own experiences with social isolation. Does chronic social isolation cause physical or chemical changes in the brain similar to those seen in PTSD? And does loneliness exacerbate symptoms of PTSD?
“There’s this hypervigilance that occurs in loneliness, and there’s also something very similar that occurs in PTSD — a heightened awareness of potential threats,” says Rutledge, who is the recipient of Michael Ferrara Graduate Fellowship provided by the Poitras Center, a fellowship made possible by the many friends and family of Michael Ferrara. “The combination of the two may lead to more adverse reactions in people with PTSD.”
In the future, Rutledge hopes to explore whether chronic loneliness impairs reasoning and logic skills and has a deeper impact on veterans who have PTSD.
Although his research tends to resurface painful memories of his own combat experiences, Rutledge says if it can help other veterans heal, it’s worth it. “In the process, it makes me a little bit stronger as well,” he adds.
