1. Study suggests adults with autism show diminished brain response to hearing their own name

    February 16, 2018 by Ashley

    From the Ghent University press release:

    Previously, research has shown that children at risk of an autism diagnosis respond less to hearing their own name. Now, a new study from the research group EXPLORA of Ghent University shows for the first time that the brain response to hearing one’s own name is also diminished in adults with an autism diagnosis. The study was conducted by Dr. Annabel Nijhof as part of her PhD project, supervised by Prof. Dr. Roeljan Wiersema and Prof. Dr. Marcel Brass.

    Whether you are at a party or in line at the supermarket, when you hear someone calling your name this usually elicits a strong orienting response. Hearing your own name typically signals that another person intends to attract your attention, and orienting to the own name is considered an important aspect of successful social interaction. Problems with social interaction and communication belong to the core symptoms of autism spectrum disorder (ASD). Studies with infants at risk for ASD have indicated that a diminished orienting response to the own name is one of the strongest predictors for developing ASD. Surprisingly however, this had not yet been studied in individuals with an ASD diagnosis.

    In a new study from Ghent University, Belgium, the brain response to hearing one’s own name versus other names was compared between a group of adults with ASD, and a control group of adults without an ASD diagnosis. Participants in the study were listening to their own name, and names of close and unfamiliar others, but did not need to respond to these names. Meanwhile, their brain activity was being recorded.

    Results showed that, as expected, the brain response to one’s own name was much stronger than for other names in neurotypical adults. Strikingly, this preferential effect for the own name was completely absent in adults with ASD. Furthermore, this group difference was related to diminished activity in the right temporoparietal junction (rTPJ). Previous research has related the rTPJ to the processes of self-other distinction and mentalizing (representing another person’s mental states). During these processes, abnormal patterns of activity have been found in individuals with ASD.

    This study is the first to show that brains of adults with ASD respond differently when hearing their own name, suggestive of a core deficit in self-other distinction associated with dysfunction of the rTPJ. This novel finding is important for our understanding of this complex condition and its development, and warrants further research on the possibility to use the atypical neural response to the own name as a potential biological marker of ASD.


  2. Using virtual reality to identify brain areas involved in memory

    February 15, 2018 by Ashley

    From the University of California – Davis press release:

    Virtual reality is helping neuroscientists at the University of California, Davis, get new insight into how different brain areas assemble memories in context.

    In a study published Jan. 18 in the journal Nature Communications, graduate student Halle Dimsdale-Zucker and colleagues used a virtual reality environment to train subjects, then showed that different areas of the hippocampus are activated for different types of memories.

    It’s well known that one memory can trigger related memories. We remember specific events with context — when and where it happened, who was there. Different memories can have specific context, as well as information that is the same between memories — for example, events that occurred in the same location.

    Dimsdale-Zucker and Professor Charan Ranganath at the UC Davis Center for Neuroscience and Department of Psychology are interested in how the brain assembles all the pieces of these memories. They use functional magnetic resonance imaging, or fMRI, to look for brain areas that are activated as memories are recalled, especially in the hippocampus, a small structure in the center of the brain.

    For this study, Dimsdale-Zucker used architectural sketching software to build houses in a 3-D virtual environment. The subjects watched a series of videos in which they went into one house then another. In each video, different objects were positioned within the houses. The subjects therefore memorized the objects in two contexts: which video (episodic memory) and which house (spatial memory).

    In the second phase of the study, the subjects were asked to try to remember the objects while they were scanned by fMRI.

    Being asked about the objects spontaneously reactivated contextual information, Dimsdale-Zucker said. Different regions of the hippocampus were activated for different kinds of information: One area, CA1, was associated with representing shared information about contexts (e.g., objects that were in the same video); another, distinct area was linked to representing differences in context.

    “What’s exciting is that it is intuitive that you can remember a unique experience, but the hippocampus is also involved in linking similar experiences,” Dimsdale-Zucker said. “You need both to be able to remember.”

    Another interesting finding was that in this study, the hippocampus was involved in episodic memories linking both time and space, she said. Conventional thinking has been that the hippocampus codes primarily for spatial memories, for example those involved in navigation.

    Virtual reality makes it possible to carry out controlled laboratory experiments with episodic memory, Dimsdale-Zucker said. A better understanding of how memories are formed, stored and recalled could eventually lead to better diagnosis and treatment for memory problems in aging or degenerative disorders such as Alzheimer’s disease.


  3. Study suggests body clock disruptions occur years before memory loss in Alzheimer’s

    by Ashley

    From the Washington University in St. Louis press release:

    People with Alzheimer’s disease are known to have disturbances in their internal body clocks that affect the sleep/wake cycle and may increase risk of developing the disorder. Now, new research at Washington University School of Medicine in St. Louis indicates that such circadian rhythm disruptions also occur much earlier in people whose memories are intact but whose brain scans show early, preclinical evidence of Alzheimer’s.

    The findings potentially could help doctors identify people at risk of Alzheimer’s earlier than currently is possible. That’s important because Alzheimer’s damage can take root in the brain 15 to 20 years before clinical symptoms appear.

    The research is published Jan. 29 in the journal JAMA Neurology.

    “It wasn’t that the people in the study were sleep-deprived,” said first author Erik S. Musiek, MD, PhD, an assistant professor of neurology. “But their sleep tended to be fragmented. Sleeping for eight hours at night is very different from getting eight hours of sleep in one-hour increments during daytime naps.”

    The researchers also conducted a separate study in mice, to be published Jan. 30 in The Journal of Experimental Medicine, showing that similar circadian disruptions accelerate the development of amyloid plaques in the brain, which are linked to Alzheimer’s.

    Previous studies at Washington University, conducted in people and in animals, have found that levels of amyloid fluctuate in predictable ways during the day and night. Amyloid levels decrease during sleep, and several studies have shown that levels increase when sleep is disrupted or when people don’t get enough deep sleep, according to research by senior author, Yo-El Ju, MD.

    “In this new study, we found that people with preclinical Alzheimer’s disease had more fragmentation in their circadian activity patterns, with more periods of inactivity or sleep during the day and more periods of activity at night,” said Ju, an assistant professor of neurology.

    The researchers tracked circadian rhythms in 189 cognitively normal, older adults with an average age of 66. Some had positron emission tomography (PET) scans to look for Alzheimer’s-related amyloid plaques in their brains. Others had their cerebrospinal fluid tested for Alzheimer’s-related proteins. And some had both scans and spinal fluid testing.

    Of the participants, 139 had no evidence of the amyloid protein that signifies preclinical Alzheimer’s. Most had normal sleep/wake cycles, although several had circadian disruptions that were linked to advanced age, sleep apnea or other causes.

    But among the other 50 subjects — who either had abnormal brain scans or abnormal cerebrospinal fluid — all experienced significant disruptions in their internal body clocks, determined by how much rest they got at night and how active they were during the day. Disruptions in the sleep/wake cycle remained even after the researchers statistically controlled for sleep apnea, age and other factors.

    The study subjects, from Washington University’s Knight Alzheimer’s Disease Research Center, all wore devices similar to exercise trackers for one to two weeks. Each also completed a detailed sleep diary every morning.

    By tracking activity during the day and night, the researchers could tell how scattered rest and activity were throughout 24-hour periods. Subjects who experienced short spurts of activity and rest during the day and night were more likely to have evidence of amyloid buildup in their brains.

    These findings in people reinforce the mouse research from Musiek’s lab. In that study, working with first author Geraldine J. Kress, PhD, an assistant professor of neurology, Musiek studied circadian rhythm disruptions in a mouse model of Alzheimer’s. To disrupt the animals’ circadian rhythms, his team disabled genes that control the circadian clock.

    “Over two months, mice with disrupted circadian rhythms developed considerably more amyloid plaques than mice with normal rhythms,” Musiek said. “The mice also had changes in the normal, daily rhythms of amyloid protein in the brain. It’s the first data demonstrating that the disruption of circadian rhythms could be accelerating the deposition of plaques.”

    Both Musiek and Ju said it’s too early to answer the chicken-and-egg question of whether disrupted circadian rhythms put people at risk for Alzheimer’s disease or whether Alzheimer’s-related changes in the brain disrupt circadian rhythms.

    “At the very least, these disruptions in circadian rhythms may serve as a biomarker for preclinical disease,” said Ju. “We want to bring back these subjects in the future to learn more about whether their sleep and circadian rhythm problems lead to increased Alzheimer’s risk or whether the Alzheimer’s disease brain changes cause sleep/wake cycle and circadian problems.”

    Reference: Kress, GJ, Liao F, Dimitry J, Cedeno MR, Fitzgerald GA, Holtzman DM, Musiek ES. Regulation of amyloid-beta dynamics and pathology by the circadian clock. The Journal of Experimental Medicine, Jan. 30, 2018.


  4. Study suggests brain response to music can reveal if you have musical training

    February 14, 2018 by Ashley

    From the University of Jyväskylä press release:

    How your brain responds to music listening can reveal whether you have received musical training, according to new Nordic research conducted in Finland (University of Jyväskylä and AMI Center) and Denmark (Aarhus University).

    By applying methods of computational music analysis and machine learning on brain imaging data collected during music listening, the researchers we able to predict with a significant accuracy whether the listeners were musicians or not. These results emphasize the striking impact of musical training on our neural responses to music to the extent of discriminating musicians’ brains from non-musicians’ brains despite other independent factors such as musical preference and familiarity.

    The research also revealed that the brain areas that best predict musicianship exist predominantly in the frontal and temporal areas of the brain’s right hemisphere. These findings conform to previous work on how the brain processes certain acoustic characteristics of music as well as intonation in speech. The paper was published on January 15 in the journal Scientific Reports.

    The study utilized functional magnetic resonance imaging (fMRI) brain data collected by Professor Elvira Brattico’s team at Aarhus University. The data was collected from 18 musicians and 18 non-musicians while they attentively listened to music of different genres. Computational algorithms were applied to extract musical features from the presented music.

    “A novel feature of our approach was that, instead of relying on static representations of brain activity, we modelled how music is processed in the brain over time. Taking the temporal dynamics into account was found to improve the results remarkably,” explains Pasi Saari, Postdoctoral Researcher at the University of Jyväskylä and the main author of the study.

    As the last step of modelling, the researchers used machine learning to form a model that predicts musicianship from a combination of brain regions.

    The machine learning model was able to predict the listeners’ musicianship with 77 % accuracy, a result that is on a par with similar studies on participant classification with, for example, clinical populations of brain-damaged patients. The areas where music processing best predicted musicianship resided mostly in the right hemisphere, and included areas previously found to be associated with engagement and attention, processing of musical conventions, and processing of music-related sound features (e.g. pitch and tonality).

    “These areas can be regarded as core structures in music processing which are most affected by intensive, lifelong musical training,” states Iballa Burunat, Postdoctoral Researcher at the University of Jyväskylä and a co-author of the study.

    In these areas, the processing of higher-level features such as tonality and pulse was the best predictor of musicianship, suggesting that musical training affects particularly the processing of these aspects of music.

    “The novelty of our approach is the integration of computational acoustic feature extraction with functional neuroimaging measures, obtained in a realistic music-listening environment, and taking into account the dynamics of neural processing. It represents a significant contribution that complements recent brain-reading methods which decode participant information from brain activity in realistic conditions,” concludes Petri Toiviainen, Academy Professor at the University of Jyväskylä and the senior author of the study.

    The research was funded by the Academy of Finland and Danish National Research Foundation.


  5. What are memories made of?

    February 12, 2018 by Ashley

    From the University of Colorado at Boulder press release:

    Ask a nonscientist what memories are made of and you’ll likely conjure images of childhood birthday parties or wedding days. Charles Hoeffer thinks about proteins.

    For five years, the assistant professor of integrative physiology at CU Boulder has been working to better understand a protein called AKT, which is ubiquitous in brain tissue and instrumental in enabling the brain to adapt to new experiences and lay down new memories.

    Until now, scientists have known very little about what it does in the brain.

    But in a new paper funded by the National Institutes of Health, Hoeffer and his co-authors spell it out for the first time, showing that AKT comes in three distinct varieties residing in different kinds of brain cells and affecting brain health in very distinct ways.

    The discovery could lead to new, more targeted treatments for everything from glioblastoma — the brain cancer Sen. John McCain has — to Alzheimer’s disease and schizophrenia.

    “AKT is a central protein that has been implicated in a bevy of neurological diseases yet we know amazingly little about it,” Hoeffer said. “Our paper is the first to comprehensively examine what its different forms are doing in the brain and where.”

    Discovered in the 1970s and known best as an “oncogene” (one that, when mutated, can promote cancer), AKT has more recently been identified as a key player in promoting “synaptic plasticity,” the brain’s ability to strengthen cellular connections in response to experience.

    “Let’s say you see a great white shark and you are scared and your brain wants to form a memory of what’s going on. You have to make new proteins to encode that memory,” he said. AKT is one of the first proteins to come online, a central switch that turns on the memory factory.

    But not all AKTs are created equal.

    For the study, Hoeffer’s team silenced the three different isoforms, or varieties, of AKT in mice and observed their brain activity.

    They made a number of key discoveries:

    AKT2 is found exclusively in astroglia, the supportive, star-shaped cells in the brain and spinal cord that are often impacted in brain cancer and brain injury.

    “That is a really important finding,” said co-author Josien Levenga, who worked on the project as a postdoctoral researcher at CU Boulder. “If you could develop a drug that targeted only AKT2 without impacting other forms, it might be more effective in treating certain issues with fewer side-effects.”

    The researchers also found that AKT1 is ubiquitous in neurons and appears to be the most important form in promoting the strengthening of synapses in response to experience, aka memory formation. (This finding is in line with previous research showing that mutations in AKT1 boost risk of schizophrenia and other brain disorders associated with a flaw in the way a patient perceives or remembers experiences.)

    AKT3 appears to play a key role in brain growth, with mice whose AKT3 gene is silenced showing smaller brain size.

    “Before this, there was an assumption that they all did basically the same thing in the same cells in the same way. Now we know better,” Hoeffer said.

    He notes that pan-AKT inhibitors have already been developed for cancer treatment, but he envisions a day when drugs could be developed to target more specific versions of the protein (AKT1 enhancers for Alzheimer’s and schizophrenia, AKT2 inhibitors for cancer), leaving the others forms untouched, preventing side-effects.

    More animal research is underway to determine what happens to behavior when different forms of the protein go awry.

    “Isoform specific treatments hold great promise for the design of targeted therapies to treat neurological diseases with much greater efficacy and accuracy than those utilizing a one-size-fits-all approach,” the authors conclude. “This study is an important step in that direction.”


  6. Study looks at what makes children with autism less social than their peers

    by Ashley

    From the University of California – Riverside press release:

    Pick a hand, any hand. That familiar refrain, repeated in schoolyards the world over, is the basis of a simple guessing game that was recently adapted to study how and why kids with autism spectrum disorder (ASD) interact with the people around them.

    The game is the brainchild of Katherine Stavropoulos, an assistant professor of special education in the Graduate School of Education at the University of California, Riverside. As a licensed clinical psychologist with a background in neuroscience, Stavropoulos looks closely at electrical activity in the brains of children with ASD and typical development, or TD, to discern differences in the respective groups’ reward systems.

    Historically, clinicians and scientists have proposed a variety of theories to explain why kids with ASD tend to be less socially communicative than their TD peers. One popular theory, the social motivation hypothesis, suggests that kids with ASD aren’t intrinsically motivated to interact with other people because they aren’t neurologically “rewarded” by social interactions the same way TD kids are.

    “Most of us get a hit of dopamine when we interact with other people, whether it’s through making eye contact or sharing something good that’s happened to us — it feels good to be social,” Stavropoulos said. “The social motivation hypothesis says kids with autism don’t get that same reward from social interaction, so they don’t go out of their way to engage with people because it’s not rewarding for them.”

    A second theory, sensory over-responsivity — also known as the overly intense world hypothesis — posits that because kids with ASD interpret sensory cues more intensely than their TD peers, those with ASD tend to shy away from interactions they perceive as overwhelming or aversive.

    “Kids with autism often find noises too loud or lights too bright, or they find them not intense enough,” Stavropoulos said. “Most of us wouldn’t want to talk to someone whom we perceive as screaming, especially in a room that was already too bright, with ambient noise that was already too loud.” Instead, sensory over-responsivity argues, such interactions compel many individuals with ASD to withdraw from socialization as a self-soothing behavior.

    But according to Stavropoulos, who also serves as assistant director of UCR’s SEARCH Family Autism Resource Center, it may be possible for these seemingly competing theories to exist in tandem.

    Stavropoulos and UC San Diego’s Leslie Carver, her research colleague and former graduate advisor, used electrophysiology to study the neural activity of 43 children between the ages of 7 and 10 — 23 of whom were TD and 20 of whom had ASD — during a guessing game-style simulation that provided participants with both social and nonsocial rewards. Their results, published this week in the journal Molecular Autism, provide a glimpse at the brain mechanisms behind autism.

    Wearing a cap outfitted with 33 electrodes, each child sat before a computer screen showing pairs of boxes containing question marks. Much like the format of the “pick a hand” guessing game, the child then chose the box he or she thought was the “right” one (in reality, the answers were randomized).

    Stavropoulos said it was crucial to design a simulation that would allow the researchers to study participants’ neural reactions to social and nonsocial rewards during two stages: reward anticipation, or the period before the child knew whether he or she had chosen the correct answer, and reward processing, or the period immediately after.

    “We structured the game so that the kids would pick an answer, and then there would be a brief pause,” Stavropoulos said. “It was during that pause that the kids would begin to wonder, ‘Did I get it?’ and we could observe them getting excited; the more rewarding something is to a person, the more that anticipation builds.”

    Each participant played the game in two blocks. During the social block, kids who chose the right box saw a smiling face and kids who chose the wrong box saw a sad, frowning face. During the nonsocial block, meanwhile, the faces were scrambled and reformed in the shapes of arrows pointing up to denote correct answers and down to denote incorrect ones.

    “After the kids saw whether they were right or wrong, we were then able to observe the post-stimulus reward-related activity,” Stavropoulos said of the process, which involved comparing participants’ neural oscillation patterns. The researchers gleaned several key findings from the simulation:

    • TD kids anticipated social awards — in this case, the pictures of faces — more strongly than kids with ASD.
    • Not only did children with ASD anticipate social rewards less than their TD peers, but within the ASD group, the researchers found that kids with more severe ASD were anticipating the nonsocial rewards, or the arrows, the most.
    • During reward processing, or the period after participants learned whether they had chosen the right or wrong box, the researchers observed more reward-related brain activity in TD children but more attention-related brain activity among children with ASD, which Stavropoulos said may be related to feelings of sensory overload in kids with ASD.
    • Among the autism group, meanwhile, kids with more severe ASD also showed heightened responsiveness to positive social feedback, which Stavropoulos said may indicate hyperactivity, or the state of being overwhelmed by “correct” social feedback that is commonly associated with sensory over-responsivity.

    Stavropoulos said the duo’s results provide support for both the social motivation hypothesis and the overly intense world hypothesis.

    Kids with autism might not be as rewarded by social interactions as typically developing kids are, but that doesn’t mean their reward systems are entirely broken,” she added. “This research makes the case for developing clinical interventions that help children with autism better understand the reward value of other people — to slowly teach these kids that interacting with others can be rewarding.

    “But, it is critical to do this while being sensitive to these kids’ sensory experiences,” she continued. “We don’t want to overwhelm them, or make them feel sensory overload. It’s a delicate balance between making social interactions rewarding while being aware of how loudly we speak, how excited our voices sound, and how bright the lights are.”


  7. Distinct brain rhythms, regions help us reason about categories

    February 10, 2018 by Ashley

    From the Picower Institute at MIT press release:

    We categorize pretty much everything we see, and remarkably, we often achieve that feat whether the items look patently similar — like Fuji and McIntosh apples — or they share a more abstract similarity — like a screwdriver and a drill. A new study at MIT’s Picower Institute for Learning and Memory explains how.

    Categorization is a fundamental cognitive mechanism,” says Earl Miller, Picower Professor in MIT’s Picower Institute for Learning and Memory and the Department of Brain and Cognitive Sciences. “It’s the way the brain learns to generalize. If your brain didn’t have this ability, you’d be overwhelmed by details of the sensory world. Every time you experienced something, if it was in different lighting or at a different angle, your brain would treat it as a brand new thing.”

    In the new paper in Neuron, Miller’s lab, led by postdoctoral associate Andreas Wutz and graduate student Roman Loonis, shows that the ability to categorize based on straightforward resemblance or on abstract similarity arises from the brain’s use of distinct rhythms, at distinct times, in distinct parts of the prefrontal cortex (PFC). Specifically when animals needed to match images that bore close resemblance, an increase in the power of high-frequency gamma rhythms in the ventral lateral PFC did the trick. When they had to match images based on a more abstract similarity, that depended on a later surge of lower frequency beta rhythms in the dorsal lateral PFC.

    Miller says those findings suggest a model of how the brain achieves category abstractions. It shows that meeting the challenge of abstraction is not merely a matter of thinking the same way but harder. Instead, a different mechanism in a different part of the brain takes over when simple, sensory comparison is not enough for us to judge whether two things belong to the same category.

    By precisely describing the frequencies, locations and the timing of rhythms that govern categorization, the findings, if replicated in humans, could prove helpful in research to understand an aspect of some autism spectrum disorders, Miller says. In ASD categorization can be challenging for patients, especially when objects or faces appear atypical. Potentially, clinicians could measure rhythms to determine whether patients who struggle to recognize abstract similarities are employing the mechanisms differently.

    Connecting the dots

    To conduct the study, Wutz, Loonis, Miller and co-authors measured brain rhythms in key areas of the PFC associated with categorization as animals played some on-screen games. In each round, animals would see a pattern of dots — a sample from one of two different categories of configurations. Then the sample would disappear and after a delay, two choices of dot designs would appear. The subject’s task was to fix its gaze on whichever one belonged to the same category as the sample. Sometimes the right answer was evident by sheer visual resemblance, but sometimes the similarity was based on a more abstract criterion the animal could infer over successive trials. The experimenters precisely quantified the degree of abstraction based on geometric calculations of the distortion of the dot pattern compared to a category archetype.

    “This study was very well defined” Wutz says. “It provided a mathematically correct way to distinguish something so vague as abstraction. It’s a judgement call very often, but not with the paradigm that we used.”

    Gamma in the ventral PFC always peaked in power when the sample appeared, as if the animals were making a “does this sample look like category A or not?” assessment as soon as they were shown it. Beta power in the dorsal PFC peaked during the subsequent delay period when abstraction was required, as if the animals realized that there wasn’t enough visual resemblance and deeper thought would be necessary to make the upcoming choice.

    Notably, the data was rich enough to reveal several nuances about what was going on. Category information and rhythm power were so closely associated, for example, that the researchers measured greater rhythm power in advance of correct category judgements than in advance of incorrect ones. They also found that the role of beta power was not based on the difficulty of choosing a category (i.e. how similar the choices were) but specifically on whether the correct answer had a more abstract or literal similarity to the sample.

    By analyzing the rhythm measurements, the researchers could even determine how the animals were approaching the categorization task. They weren’t judging whether a sample belonged to one category or the other, Wutz says. Instead they were judging whether they belonged to a preferred category or not.

    “That preference was reflected in the brain rhythms,” Wutz says. “We saw the strongest effects for each animal’s preferred category.”

    The National institute of Mental Health funded the study, which was co-authored by graduate student Jacob Donoghue and research scientist Jefferson Roy.


  8. Study suggests positive attitude toward math predicts math achievement in kids

    February 9, 2018 by Ashley

    From the Stanford University Medical Center press release:

    For the first time, scientists have identified the brain pathway that links a positive attitude toward math to achievement in the subject.

    In a study of elementary school students, researchers at the Stanford University School of Medicine found that having a positive attitude about math was connected to better function of the hippocampus, an important memory center in the brain, during performance of arithmetic problems.

    The findings will be published online Jan. 24 in Psychological Science.

    Educators have long observed higher math scores in children who show more interest in math and perceive themselves as being better at it. But it has not been clear if this attitude simply reflects other capacities, such as higher intelligence.

    The new study found that, even once IQ and other confounding factors were accounted for, a positive attitude toward math still predicted which students had stronger math performance.

    ‘Attitude is really important’

    “Attitude is really important,” said Lang Chen, PhD, the study’s lead author and a postdoctoral scholar in psychiatry and behavioral sciences. “Based on our data, the unique contribution of positive attitude to math achievement is as large as the contribution from IQ.”

    The scientists had not expected the contribution of attitude to be so large, Chen said. The mechanism underlying its link to cognitive performance was also unexpected.

    “It was really surprising to see that the link works through a very classical learning and memory system in the brain,” said the study’s senior author, Vinod Menon, PhD, professor of psychiatry and behavioral sciences. Researchers had previously hypothesized that the brain’s reward centers might drive the link between attitude and achievement — perhaps children with better attitudes were better at math because they found it more rewarding or motivating. “Instead, we saw that if you have a strong interest and self-perceived ability in math, it results in enhanced memory and more efficient engagement of the brain’s problem-solving capacities,” Menon said.

    The researchers administered standard questionnaires to 240 children ages 7 to 10, assessing demographics, IQ, reading ability and working-memory capacity. The children’s level of math achievement was measured with tests of their knowledge of arithmetic facts and ability to solve math word problems. Parents or guardians answered surveys about the children’s behavioral and emotional characteristics, as well as their anxiety about math and general anxiety. Children also answered a survey that assessed their attitude toward math, including questions about interest in math and self-perceived math ability, as well as their attitude toward academics in general.

    Forty-seven children from the group also participated in MRI brain scans while performing arithmetic problems. Tests were conducted outside the MRI scanner to discern which problem-solving strategies they used. An independent group of 28 children also was given MRI scans and other assessments in an attempt to replicate the findings from the cohort previously given brain scans.

    Opening the door

    Math performance correlated with a positive attitude toward math even after statistically controlling for IQ, working memory, math anxiety, general anxiety and general attitude toward academics, the study found. Children with poor attitudes toward math rarely performed well in the subject, while those with strongly positive attitudes had a range of math achievement.

    A positive attitude opens the door for children to do well but does not guarantee that they will; that depends on other factors as well,” Chen said.

    From the brain-imaging results, the scientists found that, when a child was solving a math problem, his or her positive-attitude scores correlated with activation in the hippocampus, an important memory and learning center in the brain. Activity in the brain’s reward centers, including the amygdala and the ventral striatum, was not linked to a positive attitude toward math. Statistical modeling of the brain imaging results suggested that the hippocampus mediates the link between positive attitude and efficient retrieval of facts from memory, which in turn is associated with better problem solving abilities.

    Having a positive attitude acts directly on your memory and learning system,” Chen said. “I think that’s really important and interesting.”

    The study could not disentangle the extent to which a positive attitude came from a child’s prior success in math. “We think the relationship between positive attitude and math achievement is mutual, bi-directional,” Chen said. “We think it’s like bootstrapping: A good attitude opens the door to high achievement, which means you then have a better attitude, getting you into a good circle of learning. And it can probably go the other way and be a vicious circle, too.”

    The findings may provide a new avenue for improving academic performance and learning in children who are struggling, Menon said, cautioning that this idea still needs to be tested through active interventions.

    “Typically, we focus on skill learning in individual academic domains, but our new work suggests that looking at children’s beliefs about a subject and their self-perceived abilities might provide another inroad to maximizing learning,” Menon said. The findings also offer a potential explanation for how a particularly passionate teacher can nurture students’ interest and learning capacities for a subject, he added. Inspiring teachers may be instinctively sharing their own interest, as well as instilling students in the belief that they can be good at the subject, building a positive attitude even if the student did not have it before.


  9. Study suggests cognitive training helps regain a younger-working brain

    February 8, 2018 by Ashley

    From the Center for BrainHealth press release:

    Relentless cognitive decline as we age is worrisome, and it is widely thought to be an unavoidable negative aspect of normal aging. Researchers at the Center for BrainHealth at The University of Texas at Dallas, however, say their research could provide new hope for extending our brain function as we age.

    In a randomized clinical study involving adults age 56 to 71 that recently published in Neurobiology of Aging, researchers found that after cognitive training, participants’ brains were more energy efficient, meaning their brain did not have to work as hard to perform a task.

    Dr. Michael Motes, senior research scientist at the Center for BrainHealth and one of the lead authors of the study, said, “Finding a nonpharmacological intervention that can help the aging brain to perform like a younger brain is a welcome finding that potentially advances understanding of ways to enhance brain health and longevity. It is thrilling for me as a cognitive neuroscientist, who has previously studied age-related cognitive decline, to find that cognitive training has the potential to strengthen the aging brain to function more like a younger brain.”

    To investigate changes in brain efficiency, the research team studied neural activity while the participant performed a task. For the study, 57 cognitively normal older adults were randomly assigned to a cognitive training group, a wait-listed control group, or physical exercise control group. The cognitive training utilized the Strategic Memory Advanced Reasoning Training (SMART) program developed at the Center for BrainHealth.

    Cognitive training strategies included how to focus on the most relevant information and filter out the less relevant; ways to continually synthesize information encountered in daily life to encourage deeper thinking; and how to inspire innovative thinking through generating diverse interpretations, solutions and perspectives. Because aerobic exercise has been shown to lead to improvements in processing speed and functional changes within the frontal and other brain regions, it was included as one of the study groups.

    The cognitive training was conducted over the course of 12 weeks. Participants in the active control physical exercise program exceeded physical activity guidelines of 150 minutes per week for the 12 weeks.

    Using functional magnetic resonance imaging (fMRI), an imaging technique that measures brain activity, researchers examined all three groups at the beginning (baseline), middle, and end of the study while participants performed computer-based speed tasks in the scanner.

    The fMRI results provided evidence that cognitive training improved speed-related neural activity. While all groups showed faster reaction times across sessions, the cognitive training group showed a significant increase in the association between reaction time and frontal lobe activity. After training, faster reaction times were associated with lower frontal lobe activity, which is consistent with the more energy-efficient neural activity found in younger adults.

    In contrast to the cognitive training group, the wait-listed and physical exercise groups showed significant decreases across sessions in the association between reaction time and frontal lobe activation.

    “This discovery of neural efficiency profiles found in the SMART-trained older adults is promising,” said Dr. Sandra Bond Chapman, one of the lead authors, Center for BrainHealth founder and chief director. “If replicated, this work paves the way for larger clinical trials to test the ability to harness the potential of the aging mind and its ability to excel — by working like a younger brain with all the rich knowledge and expertise accrued over time. To counteract the pattern of age-related losses and even enhance the brain’s inner workings by ‘thinking’ in smarter ways is an achievable and highly desirable goal.”


  10. Brain study reveals roots of desire, dislike

    February 7, 2018 by Ashley

    From the Picower Institute at MIT press release:

    The amygdala is a tiny hub of emotions where in 2016 a team led by MIT neuroscientist Kay Tye found specific populations of neurons that assign good or bad feelings, or “valence,” to experience. Learning to associate pleasure with a tasty food, or aversion to a foul-tasting one, is a primal function key to survival.

    In a new study in Cell Reports, Tye’s team at the Picower Institute for Learning and Memory returns to the amygdala for an unprecedentedly deep dive into its inner workings. Focusing on a particular section called the basolateral amygdala, the researchers show how valence-processing circuitry is organized and how key neurons in those circuits interact with others. What they reveal is a region with distinct but diverse and dynamic neighborhoods where valence is sorted out both by connecting with other brain regions, and also by sparking cross-talk within the basolateral amygdala itself.

    Perturbations of emotional valence processing is at the core of many mental health disorders,” says Tye, associate professor of neuroscience at the Picower Institute and the Department of Brain and Cognitive Sciences. “Anxiety and addiction, for example, may be an imbalance or a misassignment of positive or negative valence with different stimuli.”

    Despite its importance in both healthy behavior and psychiatric disorders, neuroscientists don’t know how valence assignment really works. The new study therefore sought to expose how the neurons and circuits are laid out and how they interact.

    Bitter, sweet

    To conduct the study, lead author Anna Beyeler, a former postdoctoral associate in Tye’s lab now a faculty member at the University of Bordeaux, France, led the group in training mice to associate yummy sucrose drops with one tone and nastily bitter quinine drops with another. They recorded the response of different neurons in the basolateral amygdala when the tones were played to see which ones were associated with the conditioned learned valence of the different tastes. They labeled those key neurons associated with valence encoding and engineered them to become responsive to pulses of light. When the researchers then activated them, they recorded the electrical activity not only of those neurons but also of many of their neighbors to see what influence their activity had in local circuits.

    They also found, labeled, and made similar measurements among neurons that became active on the occasion that a mouse actually licked the bitter quinine. With this additional step, they could measure not only the neural activity associated with the learned valence of the bitter taste but also that associated with the innate reaction to the actual experience.

    Later in the lab, they used tracing technologies to highlight three different kinds of neurons more fully, visualizing them in distinct colors depending on which other region they projected their tendrilous axons to connect with. Neurons that project to a region called the nucleus accumbens are predominantly associated with positive valence, those that connect to the central amygdala are mainly associated with negative valence, and they found that neurons uniquely activated by the unconditioned experience of actually tasting the quinine tended to project to the ventral hippocampus.

    In all, they mapped over 1,600 neurons.

    To observe the three-dimensional configuration of these distinct neuron populations, the researchers turned the surrounding brain tissues clear using a technique called CLARITY, invented by Kwanghun Chung, Assistant Professor of Chemical Engineering and Neuroscience and a colleague in the Picower Institute.

    Neighborhoods without fences

    Beyeler, Tye and their co-authors were able to make several novel observations about the inner workings of the basolateral amygdala’s valence circuitry.

    One finding was that the different functional populations of neurons tended to cluster together in neighborhoods, or “hotspots.” For example, picturing the almond-shaped amygdala as standing upright on its fat bottom, the neurons projecting to the central amygdala tended to cluster toward the point at the top and then on the right toward the bottom. Meanwhile the neurons that projected to the nucleus accumbens tended to run down the middle and the ones that projected to the hippocampus were clustered toward the bottom on the opposite side from the central amygdala projectors.

    Despite these trends, the researchers also noted that the neighborhoods were hardly monolithic. Instead, neurons of different types frequently intermingled creating a diversity where the predominant neuron type was never far from at least some representatives of the other types.

    Meanwhile, their electrical activity data revealed that the different types exerted different degrees of influence over their neighbors. For example, neurons projecting to the central amygdala, in keeping with their association with negative valence, had a very strong inhibitory effect on neighbors, while nucleus accumbens projectors had a smaller influence that was more balanced between excitation and inhibition.

    Tye speculates that the intermingling of neurons of different types, including their propensity to influence each other with their activity, may provide a way for competing circuits to engage in cross-talk.

    “Perhaps the intermingling that there is might facilitate the ability of these neurons to influence each other,” she says.

    Notably, Tye’s research has indicated the projections the different cell types make appear immutable, but the influence those cells have over each other is flexible. The basolateral amygdala may therefore be arranged to both assign valence, and also to negotiate it, for instance in those situations when a mouse spies some desirable cheese, but that mean cat is also nearby.

    “This helps us understand how form might give rise to function,” Tye says.