Research Bytes

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Research Bytes

Here is a snapshot of the latest research discoveries from BCS faculty and their research teams. To read the stories in full and to get the latest research news, click the links in the titles below.

How the brain switches between different sets of rules

Cognitive flexibility — the brain’s ability to switch between different rules or action plans depending on the context — is key to many of our everyday activities. For example, imagine you’re driving on a highway at 65 miles per hour. When you exit onto a local street, you realize that the situation has changed and you need to slow down. When we move between different contexts like this, our brain holds multiple sets of rules in mind so that it can switch to the appropriate one when necessary. These neural representations of task rules are maintained in the prefrontal cortex, the part of the brain responsible for planning action. A new study published by BCS Prof. Michael Halassa (MIBR) describes a region of the thalamus that is key to the process of switching between the rules required for different contexts. This region, called the mediodorsal thalamus, suppresses representations that are not currently needed. That suppression also protects the representations as a short-term memory that can be reactivated when needed. The findings could help guide the development of better artificial intelligence algorithms, Halassa says. The human brain is very good at learning many different kinds of tasks — singing, walking, talking, etc. However, neural networks (a type of artificial intelligence based on interconnected nodes similar to neurons) usually are good at learning only one thing. These networks are subject to a phenomenon called “catastrophic forgetting” — when they try to learn a new task, previous tasks become overwritten. Halassa and his colleagues now hope to apply their findings to improve neural networks’ ability to store previously learned tasks while learning to perform new ones.

Anne Trafton | MIT News Office

Biologists discover an unusual hallmark of aging in neurons

As we age, neurons in our brains can become damaged by free radicals. In a study co-authored by Prof. Christopher Burge (Biology) and BCS Prof. Myriam Heiman (PILM) describes this type of damage, known as oxidative stress, that produces an unusual pileup of short snippets of RNA in some neurons. This RNA buildup, which the researchers believe may be a marker of neurodegenerative diseases, can reduce protein production. The researchers observed this phenomenon in both mouse and human brains, especially in a part of the brain called the striatum — a site involved in diseases such as Parkinson’s and Huntington’s. For this study, the researchers used a technique developed by Heiman that allows them to isolate and sequence messenger RNA from specific types of cells. Messenger RNA carries protein-building instructions to cell organelles called ribosomes, which read the mRNA and translate the instructions into proteins by stringing together amino acids in the correct sequence.

To the researchers’ surprise, a mysterious result emerged — in D1 neurons from aged mice (but not neurons from young mice or D2 neurons from aged mice), they found hundreds of genes that expressed only a short fragment of the original mRNA sequence. These snippets, known as 3’ untranslated regions (UTRs), were stuck to ribosomes, preventing the ribosomes from assembling normal proteins. The researchers’ findings suggest that the production of these 3' UTRs involves the destruction of normal mRNAs, reducing the amount of protein produced from the affected genes.  This buildup of 3' UTRs with ribosomes stuck to them can also block ribosomes from producing other proteins. While It remains to be seen exactly what effect this would have on those neurons, it is possible that this kind of cellular damage could combine with genetic and environmental factors to produce a general decline in cognitive ability or even neurodegenerative conditions such as Parkinson’s disease. In future studies, the researchers hope to further explore the causes and consequences of the accumulation of 3’ UTRs.

Anne Trafton | MIT News Office

Study reveals how the brain overcomes its own limitations

BCS Prof. Mehrdad Jazayeri (MIBR) and his research team highlighted how the brain tries to compensate for its poor performance in a tasks that require complicated mental transformation, such as using a mirror to guide your hand as you write your name backwards. As it also does in other types of situations where it has little confidence in its own judgments, the brain attempts to overcome its difficulties by relying on previous experiences and according to the researchers, this strategy actually improves overall performance. The results showed that in the version that required difficult mental transformations, people altered their performance using the same strategies that they use to overcome noise in sensory perception and other realms. The new findings led the researchers to hypothesize that when people get very good at a task that requires complex computation, the noise will become smaller and less detrimental to overall performance. That is, people will trust their computations more and stop relying on averages. The researchers now plan to further study whether people’s biases decrease as they learn to perform a complicated task better.

Anne Trafton | MIT News Office

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

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, BCS Prof. Mark Harnett (MIBR) and his research team published findings that demonstrate 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. 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. These differences may contribute to the enhanced computing power of the human brain, the researchers say. Harnett notes that there are many other differences between human neurons and those of other species, 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.

Anne Trafton | MIT News Office

Neuroscientists get at the roots of pessimism

Many patients with neuropsychiatric disorders such as anxiety or depression experience negative moods that lead them to focus on the possible downside of a given situation more than the potential benefit. Institute Professor Ann Graybiel (MIBR) and her team have now pinpointed a brain region that can generate this type of pessimistic mood. In tests in animals, they showed that stimulating this region, known as the caudate nucleus, induced animals to make more negative decisions: They gave far more weight to the anticipated drawback of a situation than its benefit, compared to when the region was not stimulated. This pessimistic decision-making could continue through the day after the original stimulation. The findings could help scientists better understand how some of the crippling effects of depression and anxiety arise, and guide them in developing new treatments.

The researchers also found that brainwave activity in the caudate nucleus was altered when decision-making patterns changed. This change in the beta frequency and might serve as a biomarker to monitor whether animals or patients respond to drug treatment. Graybiel is now working with psychiatrists at McLean Hospital to study patients who suffer from depression and anxiety, to see if their brains show abnormal activity in the neocortex and caudate nucleus during approach-avoidance decision-making. Magnetic resonance imaging (MRI) studies have shown abnormal activity in two regions of the medial prefrontal cortex that connect with the caudate nucleus. The caudate nucleus has within it regions that are connected with the limbic system, which regulates mood, and it sends input to motor areas of the brain as well as dopamine-producing regions. Graybiel and her team believe that the abnormal activity seen in the caudate nucleus in this study could be somehow disrupting dopamine activity.

Anne Trafton | MIT News Office

Testing the limits of artificial visual recognition systems

A new study out of BCS Department Head Jim DiCarlo’s (MIBR) lab showed that artificial object recognition is quickly becoming more primate-like, but still lags behind when scrutinized at higher resolution. The team focused on testing so-called “deep, convolutional neural networks” (DCNNs), and specifically those that had trained on ImageNet, a collection of large-scale category-labeled image sets that have recently been used as a library to train neural networks (called DCNNIC models). These specific models have thus essentially been trained in an intense image recognition boot camp. The models were then pitted against monkeys and humans and asked to differentiate objects in synthetically constructed images. These synthetic images put the object being categorized in unusual backgrounds and orientations. The resulting images (such as the floating camel shown above) evened the playing field for the machine models (humans would ordinarily have a leg up on image categorization based on assessing context, so this was specifically removed as a confounder to allow a pure comparison of specific object categorization). DiCarlo and his team found that humans, monkeys and DCNNIC models all appeared to perform similarly, when examined at a relatively coarse level. This study begins to define more precisely when it is that the leading artificial neural networks start to “trip up”, and highlights a fundamental aspect of their architecture that struggles with categorization of single images that probably cannot be addressed through further brute force training. The work also provides an unprecedented and rich dataset of human (1476 anonymous humans to be exact) and primate behavior that will help act as a quantitative benchmark for improvement of artificial neural networks.

Sabbi Lall | McGovern Institute for Brain Research

As brain extracts meaning from vision, study tracks progression of processing

Here’s the neuroscience of a neglected banana (and a lot of other things in daily life): Whenever you look at its color — green in the store, then yellow, and eventually brown on your countertop — your mind categorizes it as unripe, ripe, and then spoiled. A new study that tracked how the brain turns simple sensory inputs, such as “green,” into meaningful categories, such as “unripe,” shows that the information follows a progression through many regions of the cortex, and not exactly in the way many neuroscientists would predict. The study, led by BCS Professor Earl Miller’s (PILM) lab, undermines the classic belief that separate cortical regions play distinct roles. Instead, as animals in the lab refined what they saw down to a specific understanding relevant to behavior, brain cells in each of six cortical regions operated along a continuum between sensory processing and categorization. To be sure, general patterns were evident for each region, but activity associated with categorization was shared surprisingly widely. The study not only refines neuroscientists’ understanding of a core capability of cognition, it also could inform psychiatrist’s understanding of disorders in which categorization judgements are atypical, such as schizophrenia and autism spectrum disorders, the authors said.

David Orenstein | Picower Institute for Learning and Memory

How music lessons can improve language skills

Many studies have shown that musical training can enhance language skills. However, it was unknown whether music lessons improve general cognitive ability, leading to better language proficiency, or if the effect of music is more specific to language processing. A new study from Rober Desimone, director of MIT’s McGovern Institute for Brain Research, has found that piano lessons have a very specific effect on kindergartners’ ability to distinguish different pitches, which translates into an improvement in discriminating between spoken words. However, the piano lessons did not appear to confer any benefit for overall cognitive ability, as measured by IQ, attention span, and working memory. The study, performed in Beijing, suggests that musical training is at least as beneficial in improving language skills, and possibly more beneficial, than offering children extra reading lessons. The school where the study was performed has continued to offer piano lessons to students, and the researchers hope their findings could encourage other schools to keep or enhance their music offerings. Desimone hopes to delve further into the neurological changes caused by music training. One way to do that is to perform EEG tests before and after a single intense music lesson to see how the brain’s activity has been altered.

Anne Trafton | MIT News Office

MIT scientists discover fundamental rule of brain plasticity

Our brains are famously flexible, or “plastic,” because neurons can do new things by forging new or stronger connections with other neurons. But if some connections strengthen, neuroscientists have reasoned, neurons must compensate lest they become overwhelmed with input. In a new study in Science, researchers at the Picower Institute for Learning and Memory at MIT demonstrate for the first time how this balance is struck: when one connection, called a synapse, strengthens, immediately neighboring synapses weaken based on the action of a crucial protein called Arc. Senior author Mriganka Sur said he was excited but not surprised that his team discovered a simple, fundamental rule at the core of such a complex system as the brain, where 100 billion neurons each have thousands of ever-changing synapses.

No one before had understood why Arc seemed to be upregulated in dendrites undergoing synaptic plasticity, even though it acts to weaken synapses, but now the answer was clear. Strengthening synapses increase Arc to weaken their neighbors. Sur added that the rule helps explain how learning and memory might work at the individual neuron level because it shows how a neuron adjusts to the repeated simulation of another. This finding, he said, provides an explanation of how synaptic strengthening and weakening combine in neurons to produce plasticity. This information allows us to understand not only how neuronal circuits develop and remodel in a physiological setting, but provides clues that will be important in identifying how these processes go awry in various neurological diseases.

 David Orenstein | Picower Institute for Learning and Memory

Neuroscientists discover roles of gene linked to Alzheimer’s

People with a gene variant called APOE4 have a higher risk of developing late-onset Alzheimer’s disease: APOE4 is three times more common among Alzheimer’s patients than it is among the general population. However, little is known about why this version of the APOE gene, which is normally involved in metabolism and transport of fatty molecules such as cholesterol, confers higher risk for Alzheimer’s.

To shed light on this question, Li-Huei Tsai and her research team performed a comprehensive study of APOE4 and the more common form of the gene, APOE3. Studying brain cells derived from a type of induced human stem cells, the researchers found that APOE4 promotes the accumulation of the beta amyloid proteins that cause the characteristic plaques seen in the brains of Alzheimer’s patients. The researchers also found that they could eliminate the signs of Alzheimer’s in brain cells with APOE4 by editing the gene to turn it into the APOE3 variant.

In another experiment, the researchers created three-dimensional “organoids,” or miniature brains, from cells with genes that are known to cause early-onset Alzheimer’s. These organoids had high levels of amyloid aggregates, but when they were exposed to APOE3 microglia, most of the aggregates were cleared away. In contrast, APOE4 microglia did not efficiently clear the aggregates.

Tsai said she believes that APOE4 may disrupt specific signaling pathways within brain cells, leading to the changes in behavior that the researchers saw in this study, revealing possible avenues for therapeutic intervention. The findings also suggest that if gene-editing technology could be made to work in humans, which many biotechnology companies are now trying to achieve, it could offer a way to treat Alzheimer’s patients who carry the APOE4 gene.

Anne Trafton | MIT News Office

Student Spotlight:
Exploring unknowns in cancer, the human brain, and the road ahead

MIT senior Kerrie Greene juggles many roles on campus and in her personal life — vice president of her dorm, neuroscientist, bioengineer, volleyball player, older sister — and she doesn’t plan to slow down any time soon. With her medical school applications complete, Greene is currently interviewing at prospective programs. She says she enjoys being involved and working hard, but it hasn’t exactly been easy.

One of her goals in coming to MIT was to study drug design, a topic that incorporates her interests in both medicine and engineering. For Greene, drug design offers a chance to increase the efficiency and accessibility of new drugs, and ultimately maximize their impact and reach. She found the ideal first major in bioengineering. Then, as a sophomore, Greene read a description of the social cognition research led by Rebecca Saxe, a professor of cognitive neuroscience, and began working in the Saxe lab through the Undergraduate Research Opportunities Program (UROP). Greene was instantly hooked.

“The more involved I was in the lab, the more I wanted to learn about the brain,” Greene explains. “I knew I had to take classes in brain and cognitive sciences.”

Inspired by Saxe’s research, she added brain and cognitive sciences as a second major her junior year. For Greene, the intense coursework is outweighed by her passion for both fields. “It’s been great,” she says. “I’ve really enjoyed getting to know students in both schools. Whichever class I’m in is the major I like more.”

Brittany Flaherty | School of Science