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Autistic kids who best peers at math show different brain organizationChildren with autism and ave

Autistic kids who best peers at math show different brain organization

Children with autism and average IQs consistently demonstrated superior math skills compared with nonautistic children in the same IQ range, according to a study by researchers at the Stanford University School of Medicine and Lucile Packard Children’s Hospital.

“There appears to be a unique pattern of brain organization that underlies superior problem-solving abilities in children with autism,” said Vinod Menon, PhD, professor of psychiatry and behavioral sciences and a member of the Child Health Research Institute at Packard Children’s.

The autistic children’s enhanced math abilities were tied to patterns of activation in a particular area of their brains — an area normally associated with recognizing faces and visual objects.

Menon is senior author of the study, published online Aug. 17 in Biological Psychiatry. Postdoctoral scholar Teresa luculano, PhD, is the lead author.

Children with autism have difficulty with social interactions, especially interpreting nonverbal cues in face-to-face conversations. They often engage in repetitive behaviors and have a restricted range of interests.

But in addition to such deficits, children with autism sometimes exhibit exceptional skills or talents, known as savant abilities. For example, some can instantly recall the day of the week of any calendar date within a particular range of years — for example, that May 21, 1982, was a Friday. And some display superior mathematical skills.

“Remembering calendar dates is probably not going to help you with academic and professional success,” Menon said. “But being able to solve numerical problems and developing good mathematical skills could make a big difference in the life of a child with autism.”

The idea that people with autism could employ such skills in jobs, and get satisfaction from doing so, has been gaining ground in recent years.

The participants in the study were 36 children, ages 7 to 12. Half had been diagnosed with autism. The other half was the control group. Each group had 14 boys and four girls. (Autism disproportionately affects boys.) All participants had IQs in the normal range and showed normal verbal and reading skills on standardized tests administered as part of the recruitment process for the study. But on the standardized math tests that were administered, the children with autism outperformed children in the control group.

After the math test, researchers interviewed the children to assess which types of problem-solving strategies each had used: Simply remembering an answer they already knew; counting on their fingers or in their heads; or breaking the problem down into components — a comparatively sophisticated method called decomposition. The children with autism displayed greater use of decomposition strategies, suggesting that more analytic strategies, rather than rote memory, were the source of their enhanced abilities.

Then, the children worked on solving math problems while their brain activity was measured in an MRI scanner, in which they had to lie down and remain still. The brain scans of the autistic children revealed an unusual pattern of activity in the ventral temporal occipital cortex, an area specialized for processing visual objects, including faces.

“Our findings suggest that altered patterns of brain organization in areas typically devoted to face processing may underlie the ability of children with autism to develop specialized skills in numerical problem solving,” Iuculano said.

“These findings not only empirically confirm that high-functioning children with autism have especially strong number-problem-solving abilities, but show that this cognitive strength in math is based on different patterns of functional brain organization,” said Carl Feinstein, MD, director of the Center for Autism and Related Disorders at Packard Children’s and professor of psychiatry and behavioral sciences at the School of Medicine. He was not involved in the study.

Menon added that previous research “has focused almost exclusively on weaknesses in children with autism. Our study supports the idea that the atypical brain development in autism can lead, not just to deficits, but also to some remarkable cognitive strengths. We think this can be reassuring to parents.”

The research team is now gathering data from a larger group of children with autism to learn more about individual differences in their mathematical abilities. Menon emphasized that not all children with autism have superior math abilities, and that understanding the neural basis of variations in problem-solving abilities is an important topic for future research.

(Image: Corbis)


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Imaging in mental health and improving the diagnostic process What are some of the most troubling nu

Imaging in mental health and improving the diagnostic process

What are some of the most troubling numbers in mental health? Six to 10 – the number of years it can take to properly diagnose a mental health condition. Dr. Elizabeth Osuch, a Researcher at Lawson Health Research Institute and a Psychiatrist at London Health Sciences Centre and the Department of Psychiatry at Western University, is helping to end misdiagnosis by looking for a ‘biomarker’ in the brain that will help diagnose and treat two commonly misdiagnosed disorders.

Major Depressive Disorder (MDD), otherwise known as Unipolar Disorder, and Bipolar Disorder (BD) are two common disorders. Currently, diagnosis is made by patient observation and verbal history. Mistakes are not uncommon, and patients can find themselves going from doctor to doctor receiving improper diagnoses and prescribed medications to little effect.

Dr. Osuch looked to identify a 'biomarker’ in the brain which could help optimize the diagnostic process. She examined youth who were diagnosed with either MDD or BD (15 patients in each group) and imaged their brains with an MRI to see if there was a region of the brain which corresponded with the bipolarity index (BI). The BI is a diagnostic tool which encompasses varying degrees of bipolar disorder, identifying symptoms and behavior in order to place a patient on the spectrum.

What she found was the activation of the putamen correlated positively with BD. This is the region of the brain that controls motor skills, and has a strong link to reinforcement and reward. This speaks directly to the symptoms of bipolar disorder. “The identification of the putamen in our positive correlation may indicate a potential trait marker for the symptoms of mania in bipolar disorder,” states Dr. Osuch.

In order to reach this conclusion, the study approached mental health research from a different angle. “The unique aspect of this research is that, instead of dividing the patients by psychiatric diagnoses of bipolar disorder and unipolar depression, we correlated their functional brain images with a measure of bipolarity which spans across a spectrum of diagnoses.” Dr. Osuch explains, “This approach can help to uncover a 'biomarker’ for bipolarity, independent of the current mood symptoms or mood state of the patient.”

Moving forward Dr. Osuch will repeat the study with more patients, seeking to prove that the activation of the putamen is the start of a trend in large numbers of patients. The hope is that one day there could be a definitive biological marker which could help differentiate the two disorders, leading to a faster diagnosis and optimal care.

In using a co-relative approach, a novel method in the field, Dr. Osuch uncovered results in patients that extend beyond verbal history and observation. These results may go on to change the way mental health is diagnosed, and subsequently treated, worldwide.


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There is no evidence that impaired blood flow or blockage in the veins of the neck or head is involved in multiple sclerosis, says a McMaster University study.

The research, published online by PLOS ONE Wednesday, found no evidence of abnormalities in the internal jugular or vertebral veins or in the deep cerebral veins of any of 100 patients with multiple sclerosis (MS) compared with 100 people who had no history of any neurological condition.

The study contradicts a controversial theory that says that MS, a chronic, neurodegenerative and inflammatory disease of the central nervous system, is associated with abnormalities in the drainage of venous blood from the brain. In 2008 Italian researcher Paolo Zamboni said that angioplasty, a blockage clearing procedure, would help MS patients with a condition he called chronic cerebrospinal venous insufficiency (CCSVI). This caused a flood of public response in Canada and elsewhere, with many concerned individuals lobbying for support of the ‘Liberation Treatment’ to clear the veins, as advocated by Zamboni.

“This is the first Canadian study to provide compelling evidence against the involvement of CCSVI in MS,” said principal investigator Ian Rodger, a professor emeritus of medicine in the Michael G. DeGroote School of Medicine. “Our findings bring a much needed perspective to the debate surrounding venous angioplasty for MS patients".

In the study all participants received an ultrasound of deep cerebral veins and neck veins as well as a magnetic resonance imaging (MRI) of the neck veins and brain. Each participant had both examinations performed on the same day. The McMaster research team included a radiologist and two ultrasound technicians who had trained in the Zamboni technique at the Department of Vascular Surgery of the University of Ferrara.

Researchers from King’s College London and the University of Nottingham have identified neuroimaging markers in the brain which could help predict whether people with psychosis respond to antipsychotic medications or not.

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In approximately half of young people experiencing their first episode of a psychosis (FEP), the symptoms do not improve considerably with the initial medication prescribed, increasing the risk of subsequent episodes and worse outcome. Identifying individuals at greatest risk of not responding to existing medications could help in the search for improved medications, and may eventually help clinicians personalize treatment plans.

In a study published today in JAMA Psychiatry, researchers used structural Magnetic Resonance Imaging (MRI) to scan the brains of 126 individuals – 80 presenting with FEP, and 46 healthy controls. Participants had an MRI scan shortly after their FEP, and another assessment 12 weeks later, to establish whether symptoms had improved following the first treatment with antipsychotic medications.

The researchers examined a particular feature of the brain called “cortical gyrification” - the extent of folding of the cerebral cortex and a marker of how it has developed. They found that the individuals who did not respond to treatment already had a significant reduction in gyrification across multiple brain regions, compared to patients who did respond and to individuals without psychosis. This reduced gyrification was particularly present in brain areas considered important in psychosis, such as the temporal and frontal lobes. Those who responded to treatment were virtually indistinguishable from the healthy controls.

The researchers also investigated whether the differences could be explained by the type of diagnosis of psychosis (eg. with or without affective symptoms, such as depression or elated mood). They found that reduced gyrification predicted non-response to treatment independently of the diagnosis. 

Dr Paola Dazzan from the Department of Psychosis Studies at King’s College London’s Institute of Psychiatry, and senior author of the paper, says: “Our study provides crucial evidence of a neuroimaging marker that, if validated, could be used early in psychosis to help identify those people less likely to respond to medications. It is possible that the alterations we observed are due to differences in the way the brain has developed early on in people who do not respond to medication compared to those who do.”

She continues:”There have been few advances in developing novel anti-psychotic drugs over the past 50 years and we still face the same problems with a sub-group of people who do not respond to the drugs we currently use. We could envisage using a marker like this one to identify people who are least likely to respond to existing medications and focus our efforts on developing new medication specifically adapted to this group. In the longer term, if we were able to identify poor responders at the outset, we may be able to formulate personalized treatment plans for that individual patient.” 

Dr Lena Palaniyappan from the University of Nottingham adds: “All of us have complex and varying patterns of folding in our brains. For the first time we are showing that the measurement of these variations could potentially guide us in treating psychosis. It is possible that people with specific patterns of brain structure respond better to treatments other than antipsychotics that are currently in use. Clearly, the time is ripe for us to focus on utilising neuroimaging to guide treatment decisions.”

Psychosis is a term used to indicate mental health disorders that present with symptoms like hallucinations (such as hearing voices) or delusions (unshakeable beliefs based on the person’s altered perception of reality, which may not correspond to the way others see the world). Psychotic episodes are present in conditions such as schizophrenia and bipolar disorder.

Approximately 1 in 100 people in England have at least one episode of psychosis throughout their lives. In most cases, psychosis develops during late adolescence (15 or above) or adulthood. Treatment involves a combination of antipsychotic medication, psychological therapies and social support. Many people with psychosis go on to lead ordinary lives and for about 60% of people, the symptoms disappear within 12 months from onset. However, for others, treatment is less straightforward and many do not respond to the initial antipsychotic treatment prescribed by their doctor. Early response to antipsychotic medication is known to be associated with better outcome and fewer subsequent episodes, and intervening early with effective treatments is therefore important.

Children’s brains are far more engaged by their mother’s voice than by voices of women they do not know, a new study from the Stanford University School of Medicine has found.

Brain regions that respond more strongly to the mother’s voice extend beyond auditory areas to include those involved in emotion and reward processing, social functions, detection of what is personally relevant and face recognition.

The study, which is the first to evaluate brain scans of children listening to their mothers’ voices, published online May 16 in the Proceedings of the National Academy of Sciences. The strength of connections between the brain regions activated by the voice of a child’s own mother predicted that child’s social communication abilities, the study also found.

“Many of our social, language and emotional processes are learned by listening to our mom’s voice,” said lead author Daniel Abrams, PhD, instructor in psychiatry and behavioral sciences. “But surprisingly little is known about how the brain organizes itself around this very important sound source. We didn’t realize that a mother’s voice would have such quick access to so many different brain systems.”

Preference for mom’s voice

Decades of research have shown that children prefer their mother’s voices: In one classic study, 1-day-old babies sucked harder on a pacifier when they heard the sound of their mom’s voice, as opposed to the voices of other women. However, the mechanism behind this preference had never been defined.

“Nobody had really looked at the brain circuits that might be engaged,” senior author Vinod Menon, PhD, professor of psychiatry and behavioral sciences, said. “We wanted to know: Is it just auditory and voice-selective areas that respond differently, or is it more broad in terms of engagement, emotional reactivity and detection of salient stimuli?”

The study examined 24 children ages 7 to 12. All had IQs of at least 80, none had any developmental disorders, and all were being raised by their biological mothers. Parents answered a standard questionnaire about their child’s ability to interact and relate with others. And before the brain scans, each child’s mother was recorded saying three nonsense words.

“In this age range, where most children have good language skills, we didn’t want to use words that had meaning because that would have engaged a whole different set of circuitry in the brain,” said Menon, who is the Rachael L. and Walter F. Nichols, MD, Professor.

Two mothers whose children were not being studied, and who had never met any of the children in the study, were also recorded saying the three nonsense words. These recordings were used as controls.

MRI scanning

The children’s brains were scanned via magnetic resonance imaging while they listened to short clips of the nonsense-word recordings, some produced by their own mother and some by the control mothers. Even from very short clips, less than a second long, the children could identify their own mothers’ voices with greater than 97 percent accuracy.

The brain regions that were more engaged by the voices of the children’s own mothers than by the control voices included auditory regions, such as the primary auditory cortex; regions of the brain that handle emotions, such as the amygdala; brain regions that detect and assign value to rewarding stimuli, such as the mesolimbic reward pathway and medial prefrontal cortex; regions that process information about the self, including the default mode network; and areas involved in perceiving and processing the sight of faces.

“The extent of the regions that were engaged was really quite surprising,” Menon said.

“We know that hearing mother’s voice can be an important source of emotional comfort to children,” Abrams added. “Here, we’re showing the biological circuitry underlying that.”

Children whose brains showed a stronger degree of connection between all these regions when hearing their mom’s voice also had the strongest social communication ability, suggesting that increased brain connectivity between the regions is a neural fingerprint for greater social communication abilities in children.

‘An important new template’

“This is an important new template for investigating social communication deficits in children with disorders such as autism,” Menon said. His team plans to conduct similar studies in children with autism, and is also in the process of investigating how adolescents respond to their mother’s voice to see whether the brain responses change as people mature into adulthood.

“Voice is one of the most important social communication cues,” Menon said. “It’s exciting to see that the echo of one’s mother’s voice lives on in so many brain systems.”

How Shared Neural Codes Help Us Recognize Familiar Faces

The ability to recognize familiar faces is fundamental to social interaction, as visual information activates social and personal knowledge about a person who is familiar. But how individuals in social groups process this information in their brains has long been a question. Distinct information about familiar faces is stored in a neural code that is shared across brains, according to a new study published in the Proceedings of the National Academy of Sciences.

“Within visual processing areas, we found that information about personally familiar and visually familiar faces is shared across the brains of people who have the same friends and acquaintances,” says first author Matteo Visconti di Oleggio Castello, Guarini ’18, a postdoctoral neuroscience scholar at the University of California, Berkeley, who conducted this research as a graduate student in psychological and brain sciences. “We were surprised to find that the shared information about personally familiar faces also extends to areas that are non-visual and important for social processing, suggesting that there is shared social information across brains.”

For the study, the research team applied a method called hyperalignment to create a common representational space for understanding how brain activity is similar among participants. The team obtained fMRI data from 14 graduate students in the same PhD program in three sessions. In one session, participants watched parts of the film The Grand Budapest Hotel. This data was used to align to participants’ brain responses to a common representational space. In the other two fMRI sessions, participants were asked to look at faces of fellow graduate students with whom they were personally familiar and at faces of strangers with whom they were visually familiar, but about whom they had no other information. The researchers used machine learning classifiers to predict what face a participant was looking at based on the brain activity of the other participants.

For visually familiar identities, participants only knew what the faces looked like. The results showed that the identity of visually familiar faces could be decoded with accuracy only in brain areas that are involved in visual processing of faces. On the other hand, the identity of personally familiar faces could be decoded with accuracy across participants in brain areas involved in visual processing and, surprisingly, also in areas involved in social cognition. These areas included the dorsal medial prefrontal cortex, which is involved in processing other people’s intentions and traits; the precuneus, an area active when processing personally familiar faces; the insula, which is involved in emotional processing; and the temporal parietal junction, which plays an important role in social cognition and in representing the mental states of others—what’s known as the “theory of the mind.”

This research builds on the team’s earlier work, which found that these theory-of-mind areas in the brain are activated when a person sees someone personally familiar.

“This is what allows us to interact in the most appropriate way with someone who is familiar,” says senior author Maria (Ida) Gobbini, a research associate professor in the Center for Cognitive Neuroscience and associate professor in the department of experimental, diagnostic, and specialty medicine at the University of Bologna. For example, how you interact with a friend or family member may be quite different from the way you interact with a colleague or boss.

“It would have been quite possible that everybody has their own private code for what people are like, but this is not the case,” says co-author James Haxby, professor of psychological and brain sciences. “Our research shows that processing familiar faces really has to do with general knowledge about people.”

New Study Helps in Finally Breaking the “Silence” on the Brain Network

Studying the complex network of operations in the brain not only helps us understand its working better, but also provides avenues for potential treatments for brain disorders. But linking the brain network to actual behavior is challenging. In a new study, researchers have discovered that pinpointed suppression or “silencing” of certain areas of monkey brains using genetically engineered drugs can be used to reveal changes to their operational network and the subsequent behavioral effects.​

Scientists have been studying the human brain for centuries, yet they have only scratched the surface of all there is to know about this complex organ. In 1990, the face of neuroscience changed with the invention of functional magnetic resonance imaging (fMRI). fMRI works on the idea that when a certain area of the brain is being used, it experiences an increase in blood flow. This technique has been used to study neurological activity in the brains of myriad animals and humans as well, providing valuable information on cognitive and movement-based functions.​

fMRI has also revealed that “activating” a certain part of the brain has effects on other anatomically or functionally connected regions. Trying to solve this “network” of operations in the brain is one of the key issues in neuroscience.

In a recent study, a research team—including Toshiyuki Hirabayashi and Takafumi Minamimoto from the National Institutes for Quantum Science and Technology (QST)—has shown that gene-targeting drugs in macaque monkeys can cause multifaceted behavioral effects via the altered operation of relevant brain networks, thus opening a critical path towards understanding the network of operations underlying higher functions in primates (monkeys, humans etc.). “Our technique will allow us to study how disturbances to the functional brain network lead to certain symptoms. This will help us to work backwards to clarify the network mechanisms behind brain disorders with similar symptoms, thus leading to new treatments,” reveals Dr. Toshiyuki Hirabayashi, principal researcher at QST, who led the study.

Conventional approaches to activating or suppressing areas of the brain include electrical stimulation or the injection of a psychoactive substance called muscimol, but recent research has focused on using genetic techniques of targeting due to how specific they are. Called chemogenetics, these techniques rely on artificial drugs that are designed to specifically bind to genetically induced artificial protein called “receptors.” The drugs bind to the receptors, and thus influence physiological and neurological processes in the brain, spinal cord, and other parts of the body where the receptors are genetically expressed. Combining chemogenetics with fMRI enables non-invasive visualization of network-level changes induced by local activity manipulation. But, unlike the recent study, chemogenetic fMRI studies so far have focused on a resting state, which might not provide the most useful results when trying to study task-related or sensory-related activities.

For their investigation into functional brain networks, the research team studied the effects of fMRI guided chemogenetics on hand-grasping in macaques. To do this, they first studied the part of the brain that is responsible for precise finger movement, and then silenced (suppressed) it for one hand using a “designer receptor exclusively activated by designer drugs” (DREADD). They then gave the monkeys with silenced hand-grasping skills a task that involved picking up food pellets from a board consisting of small slots. They found that the monkeys could pick up pellets well with the non-silenced hand, which was on the same side of the body as the silenced brain region. But they struggled with using the affected hand, which was on the opposite side. The scientists also saw that the designer drug caused a reduced fMRI signal from “downstream” areas of the monkey brains, providing insight into the rest of the network dysfunction underlying the altered hand-grasping behavior. Finally, they saw that silencing the hand sensory region caused unexpectedly elevated activity in the foot sensory region with an increased sensitivity in the foot on the opposite side of the body, which further suggested that portions of the network have inhibitory effects on other parts of the system.

These findings demonstrate that targeted chemogenetic silencing in macaques can cause stimulatory and inhibitory, i.e., bidirectional changes in brain activity, which can be identified using fMRI. Furthermore, chemogenetics offer a minimally invasive way to repeatedly manipulate the same location on the brain without causing damage to the brain tissue, making the approach beneficial for the study of the functional brain network. According to Dr. Hirabayashi, “Applying chemogenetic fMRI to higher brain functions in macaques like memory or affection will lead to translational understanding of causal network mechanisms for those functions in the human brain.”

With developments like these, it is easy to see humankind having a clearer picture of the workings of the human brain soon!

(Image caption: Schematic representation of the targeted silencing experiment. The scientists found that silencing the brain area (SI) for hand sensation surprisingly increased activity in the brain area for foot sensation. Credit: Toshiyuki Hirabayashi from National Institutes for Quantum Science and Technology)

Brain Activation in Sleeping Toddlers Shows Memory for Words

Very young children learn words at a tremendous rate. Now researchers at the Center for Mind and Brain at the University of California, Davis, have for the first time seen how specific brain regions activate as two-year-olds remember newly learned words — while the children were sleeping. The work was published in Current Biology.

“We can now leverage sleep to look at basic mechanisms of learning new words,” said Simona Ghetti, professor at the Center for Mind and Brain and UC Davis Department of Psychology.

At two to three years old, children enter a unique age in memory development, Ghetti said. But young children are challenging to study, and they especially dislike being in a functional MRI scanner.

“The scariest things to small children are darkness and loud noises, and that’s what it’s like during an MRI scan,” Ghetti said.

Ghetti’s team had previously found that if children fell asleep in a scanner while it wasn’t working, they could later start the scan and see brain activation in response to songs the children had heard earlier.

In the new study, they looked at how toddlers retained memories of words.

Graduate student Elliott Johnson and Ghetti created a series of made-up, but realistic sounding words as names for a series of objects and puppets. In the first session, two-year-olds were introduced to two objects and two puppets, then tested on their memory of the names after a few minutes. A week later, they returned and were tested on whether they remembered the names of the objects and puppets. Soon after the second test, they slept overnight in an MRI scanner. The researchers played back the words the children had learned, as well as other words, as they slept.

Activation of the hippocampus in learning

The researchers found activation of the hippocampus and the anterior medial temporal lobe when the sleeping children were played words they had previously learned. This activation correlated with how well they had performed when they initially learned the words a week earlier.

“This suggests that the hippocampus is particularly important for laying down the initial memory for words,” Ghetti said. “This compares quite well with findings from older children and adults, where the hippocampus is associated with learning and with recalling recent memories” Johnson added.

Although young children are rapidly forming memories of new words, they are also losing a lot of memories. When we form a memory, it includes the context: where, when, what else was going on. But if we just learned the name of an object, we don’t need to remember the context to use the word again. That extra detail can go.

It’s not clear how children remember some things, such as names, while losing the rest. Ghetti suspects that overlapping learning experiences interfere with each other and cancel out the unneeded details. Future research will focus on the memory processes that support these changes.

Our brains have a “fingerprint” too

An EPFL scientist has pinpointed the signs of brain activity that make up our brain fingerprint, which – like our regular fingerprint – is unique.

“I think about it every day and dream about it at night. It’s been my whole life for five years now,” says Enrico Amico, a scientist and SNSF Ambizione Fellow at EPFL’s Medical Image Processing Laboratory and the EPFL Center for Neuroprosthetics. He’s talking about his research on the human brain in general, and on brain fingerprints in particular. He learned that every one of us has a brain “fingerprint” and that this fingerprint constantly changes in time. His findings have just been published in Science Advances.

“My research examines networks and connections within the brain, and especially the links between the different areas, in order to gain greater insight into how things work,” says Amico. “We do this largely using MRI scans, which measure brain activity over a given time period.” His research group processes the scans to generate graphs, represented as colorful matrices, that summarize a subject’s brain activity. This type of modeling technique is known in scientific circles as network neuroscience or brain connectomics. “All the information we need is in these graphs, that are commonly known as “functional brain connectomes”. The connectome is a map of the neural network. They inform us about what subjects were doing during their MRI scan – if they were resting or performing some other tasks, for example. Our connectomes change based on what activity was being carried out and what parts of the brain were being used,” says Amico.

Two scans are all it takes

A few years ago, neuroscientists at Yale University studying these connectomes found that every one of us has a unique brain fingerprint. Comparing the graphs generated from MRI scans of the same subjects taken a few days apart, they were able to correctly match up the two scans of a given subject nearly 95% of the time. In other words, they could accurately identify an individual based on their brain fingerprint. “That’s really impressive because the identification was made using only functional connectomes, which are essentially sets of correlation scores,” says Amico.

(Image caption: Map of functional brain connectomes Credit: © 2021 EPFL)

He decided to take this finding one step further. In previous studies, brain fingerprints were identified using MRI scans that lasted several minutes. But he wondered whether these prints could be identified after just a few seconds, or if there was a specific point in time when they appear – and if so, how long would that moment last? “Until now, neuroscientists have identified brain fingerprints using two MRI scans taken over a fairly long period. But do the fingerprints actually appear after just five seconds, for example, or do they need longer? And what if fingerprints of different brain areas appeared at different moments in time? Nobody knew the answer. So, we tested different time scales to see what would happen,” says Amico.

A brain fingerprint in just 1 minute and 40 seconds

His research group found that seven seconds wasn’t long enough to detect useful data, but that around 1 minute and 40 seconds was. “We realized that the information needed for a brain fingerprint to unfold could be obtained over very short time periods,” says Amico. “There’s no need for an MRI that measures brain activity for five minutes, for example. Shorter time scales could work too.” His study also showed that the fastest brain fingerprints start to appear from the sensory areas of the brain, and particularly the areas related to eye movement, visual perception and visual attention. As time goes by, also frontal cortex regions, the ones associated to more complex cognitive functions, start to reveal unique information to each of us.

The next step will be to compare the brain fingerprints of healthy patients with those suffering from Alzheimer’s disease. “Based on my initial findings, it seems that the features that make a brain fingerprint unique steadily disappear as the disease progresses,” says Amico. “It gets harder to identify people based on their connectomes. It’s as if a person with Alzheimer’s loses his or her brain identity.”

Along this line, potential applications might include early detection of neurological conditions where brain fingerprints get disappear. Amico’s technique can be used in patients affected by autism, or stroke, or even in subjects with drug addictions. “This is just another little step towards understanding what makes our brains unique: the opportunities that this insight might create are limitless.”

Teaching Ancient Brains New Tricks

The science of physics has strived to find the best possible explanations for understanding matter and energy in the physical world across all scales of space and time. Modern physics is filled with complex concepts and ideas that have revolutionized the way we see (and don’t see) the universe. The mysteries of the physical world are increasingly being revealed by physicists who delve into non-intuitive, unseen worlds, involving the subatomic, quantum and cosmological realms. But how do the brains of advanced physicists manage this feat, of thinking about worlds that can’t be experienced?

In a recently published paper in npj: Science of Learning, researchers at Carnegie Mellon University have found a way to decode the brain activity associated with individual abstract scientific concepts pertaining to matter and energy, such as fermion or dark matter.

Robert Mason, senior research associate, Reinhard Schumacher, professor of physics and Marcel Just, the D.O. Hebb University Professor of Psychology, at CMU investigated the thought processes of their fellow CMU physics faculty concerning advanced physics concepts by recording their brain activity using functional Magnetic Resonance Imaging (fMRI).

Unlike many other neuroscience studies that use brain imaging, this one was not out to find “the place in the brain” where advanced scientific concepts reside. Instead, this study’s goal was to discover how the brain organizes highly abstract scientific concepts. An encyclopedia organizes knowledge alphabetically, a library organizes it according to something like the Dewey Decimal System, but how does the brain of a physicist do it?

The study examined whether the activation patterns evoked by the different physics concepts could be grouped in terms of concept properties. One of the most novel findings was that the physicists’ brains organized the concepts into those with measureable versus immeasurable size. Here on Earth for most of us mortals, everything physical is measureable, given the right ruler, scale or radar gun. But for a physicist, some concepts like dark matter, neutrinos or the multiverse, their magnitude is not measureable. And in the physicists’ brains, the measureable versus immeasurable concepts are organized separately.

Of course, some parts of the brain organization of the physics professors resembled the organization in physics students’ brains such as concepts that had a periodic nature. Light, radio waves and gamma rays have a periodic nature but concepts like buoyancy and the multiverse do not.

But how can this interpretation of the brain activation findings be assessed? The study team found a way to generate predictions of the activation patterns of each of the concepts. But how can the activation evoked by dark matter be predicted? The team recruited an independent group of physics faculty to rate each concept on each of the hypothesized organizing dimensions on a 1-7 scale. For example, a concept like “duality” would tend to be rated as immeasurable (i.e., low on the measureable magnitude scale). A computational model then determined the relation between the ratings and activation patterns for all of the concepts except one of them and then used that relation to predict the activation of the left-out concept. The accuracy of this model was 70% on average, well above chance at 50%. This result indicates that the underlying organization is well-understood. This procedure is demonstrated for the activation associated with the concept of dark matter in the accompanying figure.

(Image caption: Based on how other physics concepts are represented in terms of their underlying dimensions, a mathematical model can accurately predict the brain activation pattern of a new concept like dark matter)

Creativity of Thought

Near the beginning of the 20th century, post-Newtonian physicists radically advanced the understanding of space, time, matter, energy and subatomic particles. The new concepts arose not from their perceptual experience, but from the generative capabilities of the human brain. How was this possible?

The neurons in the human brain have a large number of computational capabilities with various characteristics, and experience determines which of those capabilities are put to use in various possible ways in combination with other brain regions to perform particular thinking tasks. For example, every healthy brain is prepared to learn the sounds of spoken language, but an infant’s experience in a particular language environment shapes which phonemes of which language are learned.

The genius of civilization has been to use these brain capabilities to develop new skills and knowledge. What makes all of this possible is the adaptability of the human brain. We can use our ancient brains to think of new concepts, which are organized along new, underlying dimensions. An example of a “new” physics dimension significant in 20th century, post-Newtonian physics is “immeasurability” (a property of dark matter, for example) that stands in contrast to the “measurability” of classical physics concepts, (such as torque or velocity). This new dimension is present in the brains of all university physics faculty tested. The scientific advances in physics were built with the new capabilities of human brains.

Another striking finding was the large degree of commonality across physicists in how their brains represented the concepts. Even though the physicists were trained in different universities, languages and cultures, there was a similarity in brain representations. This commonality in conceptual representations arises because the brain system that automatically comes into play for processing a given type of information is the one that is inherently best suited to that processing. As an analogy, consider that the parts of one’s body that come into play to perform a given task are the best suited ones: to catch a tennis ball, a closing hand automatically comes into play, rather than a pair or knees or a mouth or an armpit. Similarly, when physicists are processing information about oscillation, the brain system that comes into play is the one that would normally process rhythmic events, such as dance movements or ripples in a pond. And that is the source of the commonality across people. It is the same brain regions in everyone that are recruited to process a given concept.

So the secret of teaching ancient brains new tricks, as the advance of civilization has repeatedly done, is to empower creative thinkers to develop new understandings and inventions, by building on or repurposing the inherent information processing capabilities of the human brain. By communicating these newly developed concepts to others, they will root themselves in the same information processing capabilities of the recipients’ brains as the original developers used. Mass communication and education can propagate the advances to entire populations. Thus the march of science, technology and civilization continue to be driven by the most powerful entity on Earth, the human brain.

Hippocampus Is the Brain’s Storyteller

People love stories. We find it easier to remember events when they are part of an overarching narrative. But in real life, the chapters of a story don’t follow smoothly one from another. Other things happen in between. A new brain imaging study from the Center for Neuroscience at the University of California, Davis, shows that the hippocampus is the brain’s storyteller, connecting separate, distant events into a single narrative. The work was published in Current Biology.

“Things that happen in real life don’t always connect directly, but we can remember the details of each event better if they form a coherent narrative,” said Brendan Cohn-Sheehy, an M.D./Ph.D. student at UC Davis and first author on the paper.

Cohn-Sheehy and colleagues at Professor Charan Ranganath’s Dynamic Memory Laboratory at the Center for Neuroscience and Department of Psychology used functional MRI to image the hippocampus of volunteers as they learned and recalled a series of short stories.

The stories, created specifically for the study, featured main and side characters and an event. The stories were constructed so that some formed connected, two-part narratives and others did not.

The researchers played recordings of the stories to the volunteers in the fMRI scanner. The next day, they scanned them again as the volunteers recalled the stories into a microphone. The researchers compared the patterns of activity in the hippocampus between learning and recalling the different stories. 

As expected, they saw more similarity for learning pieces of a coherent story than for stories that did not connect. The results show the coherent memories being woven together, Cohn-Sheehy said.

“When you get to the second event, you’re reaching back to the first event and embedding part of it in the new memory,” he said.

Hippocampus weaves memories

Next, they compared hippocampal patterns during learning and retrieval. They found that when recalling stories that formed a coherent narrative, the hippocampus activates more information about the second event than when recalling nonconnected stories.

“The second event is where the hippocampus is forming a connected memory,” Cohn-Sheehy said.

When the researchers tested the volunteers’ memory of stories, they found that the ability to bring back hippocampal activity of the second event was linked to the amount of detail the volunteers could recall.

While other parts of the brain are involved in the process of memory, the hippocampus appears to bring pieces together across time and form them into connected, narrative memories, Cohn-Sheehy said.

The work is part of a new era in memory research. Traditionally, in neuroscience, researchers have studied the basic processes of memory involving disconnected pieces of information, whereas psychology has a tradition of studying how memory works to capture and connect events in the “real world.” These two camps are starting to merge, Cohn-Sheehy said.

“We’re using brain imaging to get at realistic memory processes,” he said.

Research on memory processes could ultimately lead to better clinical tests for early stages of memory decline in aging or dementia, or for assessing damage to memory from brain injuries.

(Image caption: A new brain imaging study shows that the hippocampus (green) is the brain’s master storyteller, weaving memories of past events into a coherent narrative. Credit: Brendan Cohn-Sheehy, Center for Neuroscience)

When It Comes to Communication Skills—Maybe We’re Born with It?

From inside the womb and as soon as they enter the world, babies absorb information from their environment and the adults around them, quickly learning after birth how to start communicating through cries, sounds, giggles, and other kinds of baby talk. But are a child’s long-term language skills shaped by how their brain develops during infancy, and how much of their language development is influenced by their environment and upbringing? 

Following dozens of children over the course of five years, a Boston University researcher has taken the closest look yet at the link between how babies’ brains are structured in infancy and their ability to learn a language at a young age, and to what degree their environment plays a role in brain and language development. 

The new research, described in a paper published in Developmental Cognitive Neuroscience, finds that the brain’s organizational pathways might set a foundation for a child’s language learning abilities within the first year of life. These pathways are known as white matter, and they act as the connectors between the billions of neurons—called gray matter—that comprise the brain tissue. This allows for the exchange of signals and for all of the different tasks and functions we need to perform, as well as all of the biological processes that sustain us. 

“A helpful metaphor often used is: white matter pathways are the ‘highways,’ and gray matter areas are the ‘destinations’,” says BU neuroscientist and licensed speech pathologist Jennifer Zuk, who led the study. Zuk, a College of Health & Rehabilitation Sciences: Sargent College assistant professor of speech, language, and hearing sciences, says the more someone does a certain task, like learning a new language, the stronger and more refined the pathways become in the areas of the brain responsible for that task, allowing information to flow more efficiently through the white matter highways. Recent evidence suggests that white matter most rapidly develops within the first two years of life, according to Zuk.

In addition to white matter development, scientists have long known that the environment also plays an important role in shaping a person’s language abilities, Zuk says. But many uncertainties remain about whether nature or nurture is more dominant in determining the makeup of white matter and how well a baby learns to communicate. 

In their study, Zuk says, she and her colleagues sought answers to several specific questions: from very early on, to what extent does predisposed brain structure play a role in development? Does the brain develop in tandem with language, and is the environment ultimately driving the progress of both? And to what extent does brain structure in early infancy set children up for success with language?

To investigate this, Zuk and Boston Children’s Hospital researcher and study senior author Nadine Gaab met with 40 families with babies to take images of the infants’ brains using magnetic resonance imaging (MRI) and gather first-of-its-kind data on white matter development. No small feat, considering the babies needed to be sound asleep to allow for crisp capture of their brain activity and structure using MRI.

“It was such a fun process, and also one that calls for a lot of patience and perseverance,” says Zuk, who had to master the challenge of getting 4-to-18-month-old babies comfortable enough to snooze through the MRI process—the loud sounds of an MRI could be very disruptive to a sleeping baby. “There are very few researchers in the world using this approach,” she says, “because the MRI itself involves a rather noisy background…and having infants in a naturally deep sleep is very helpful in accomplishing this pretty crazy feat.”

It’s also the first time that scientists have used MRI to look at the relationship between brain structure and language development in full-term, typically developing children from infancy to school age. 

One important white matter pathway the researchers looked at using MRI is called the arcuate fasciculus, which connects two regions of the brain responsible for language production and comprehension. Using MRI, the researchers measured the organization of white matter by looking at how easily water diffuses through the tissue, indicating the pathway’s density.

Five years after first rocking babies to sleep and gently tucking them inside an MRI machine, Zuk and her collaborators met up with the children and their families again to assess each child’s emerging language abilities. Their assessments tested each one’s vocabulary knowledge, their ability to identify sounds within individual words, and their ability to blend individual sounds together to understand the word it makes.   

According to their findings, children born with higher indications of white matter organization had better language skills five years later, suggesting that communication skills could be strongly linked to predisposed brain structure. But, Zuk says, this is only the first piece of a very complicated puzzle.

“Perhaps the individual differences in white matter we observed in infancy might be shaped by some combination of a child’s genetics and their environment,” she says. “But it is intriguing to think about what specific factors might set children up with more effective white matter organization early on.” 

Although their findings indicate a foundation for language is established in infancy, “ongoing experience and exposure [to language] then builds upon this foundation to support a child’s ultimate outcomes,” Zuk says.

She says this means that during the first year of a child’s life “there’s a real opportunity for more environmental exposure [to language] and to set children up for success in the long term.” 

Zuk and her research partners plan to continue investigating the relationship between environmental and genetic components of language learning. Their goal is to help parents and caretakers identify early risk factors in language development in young children and determine strategies for strengthening babies’ communicative skills early on in life. 

How scents take on meaning

A Bochum-based research team triggered artificial odour sensations in rats – and looked at what happens in the brain as a result.

Once a scent is detected, different areas of the brain are activated. A team from the Department of Neuroscience at Ruhr-Universität Bochum (RUB) has recently discovered that structures of the olfactory sense work closely together with the brain’s reward and aversion systems. This means that scents are processed not only by the olfactory centre but also by regions responsible for emotions and valence determination. The findings were published in the journal “Cerebral Cortex”.

Dr. Christina Strauch, PhD student Thu-Huong Hoang, and Professor Denise Manahan-Vaughan from the Department of Neurophysiology collaborated on the study with Professor Frank Angenstein from the German Center for Neurodegenerative Diseases (DZNE) in Magdeburg.

Olfactory perception outside the olfactory bulb and the olfactory cortex

The researchers studied how the processing of scents affects structures in the brain. They used electrical impulses to stimulate the olfactory bulbs of test animals. Then, they analysed the activity in the olfactory cortex, where olfactory stimuli are processed. “We already knew that there is a connection between the olfactory bulb and the piriform cortex, a part of the olfactory cortex, in the perception of scents,” explains Dr. Christina Strauch, lead author of the study. “But our goal was to go deeper into the brain structures and find out which regions we had underestimated or overlooked until now.” “So far, only a few studies on olfactory perception have analysed regions outside the olfactory bulb and olfactory cortex regions in rodents,” says Professor Denise Manahan-Vaughan, spokesperson of Collaborative Research Centre 874 Integration and Representation of Sensory Processes. “It is still not completely understood how olfactory memories are formed. Our goal was to clarify to what extent brain structures that aren’t part of the olfactory system are involved in olfactory memory formation.”

Evidence of olfactory processing in the rodent brain

In their study, the researchers combined electrophysiological stimulation with functional magnetic resonance imaging (fMRI). Following this approach, the team obtained a detailed picture of the neuronal structures that responded to the stimulation of the olfactory bulb. Highly responsive structures were then analysed in more depth using fluorescence in situ hybridisation analysis of neuronal gene expression. This technique helps researchers determine whether neurons do indeed store the olfactory stimulus: This event serves as evidence of memory formation.

Sure enough, stimulation of the olfactory bulb had led to altered gene activity. This happened even in the nerve cells of the limbic cortex – that is, in a functional unit attributed with the processing of emotions. “The involvement of these non-olfactory structures probably plays a key role in the storage of olfactory experiences,” as Christina Strauch interprets the findings. “We deduce from this that rodents quickly categorise perceived scents as pleasant or unpleasant while smelling them.”

Overall, the results prove that the olfactory system works closely with the brain’s reward and aversion systems in both learning and memory formation.

“The study provides us an additional theoretical basis for understanding why the sense of smell plays such a unique role in the formation and retrieval of memories,” says Denise Manahan-Vaughan, who together with Christina Strauch has been exploring how memories are formed from scents since 2010.

Scientists Pinpoint the Uncertainty of Our Working Memory

The human brain regions responsible for working memory content are also used to gauge the quality, or uncertainty, of memories, a team of scientists has found. Its study uncovers how these neural responses allow us to act and make decisions based on how sure we are about our memories.

“Access to the uncertainty in our working memory enables us to determine how much to ‘trust’ our memory in making decisions,” explains Hsin-Hung Li, a postdoctoral fellow in New York University’s Department of Psychology and Center for Neural Science and the lead author of the paper, which appears in the journal Neuron. “Our research is the first to reveal that the neural populations that encode the content of working memory also represent the uncertainty of memory.”

Working memory, which enables us to maintain information in our minds, is an essential cognitive system that is involved in almost every aspect of human behavior—notably decision-making and learning. 

For example, when reading, working memory allows us to store the content we just read a few seconds ago while our eyes keep scanning through the new sentences. Similarly, when shopping online, we may compare, “in our mind,” the item in front of us on the screen with previous items already viewed and still remembered. 

“It is not only crucial for the brain to remember things, but also to weigh how good the memory is: How certain are we that a specific memory is accurate?” explains Li. “If we feel that our memory for the previously viewed online item is poor, or uncertain, we would scroll back and check that item again in order to ensure an accurate comparison.”

While studies on human behaviors have shown that people are able to evaluate the quality of their memory, less clear is how the brain achieves this. 

More specifically, it had previously been unknown whether the brain regions that hold the memorized item also register the quality of that memory.

In uncovering this, the researchers conducted a pair of experiments to better understand how the brain stores working memory information and how, simultaneously, the brain represents the uncertainty—or, how good the memory is—of remembered items. 

In the first experiment, human participants performed a spatial visual working memory task while a functional magnetic resonance imaging (fMRI) scanner recorded their brain activity. For each task, or trial, the participant had to remember the location of a target—a white dot shown briefly on a computer screen—presented at a random location on the screen and later report the remembered location through eye movement by looking in the direction of the remembered target location.

Here, fMRI signals allowed the researchers to decode the location of the memory target—what the subjects were asked to remember—in each trial. By analyzing brain signals corresponding to the time during which participants held their memory, they could determine the location of the target the subjects were asked to memorize. In addition, through this method, the scientists could accurately predict memory errors made by the participants; by decoding their brain signals, the team could determine what the subjects were remembering and therefore spot errors in their recollections.  

In the second experiment, the participants reported not only the remembered location, but also how uncertain they felt about their memory in each trial. The resulting fMRI signals recorded from the same brain regions allowed the scientists to decode the uncertainty reported by the participants about their memory. 

Taken together, the results yielded the first evidence that the human brain registers both the content and the uncertainty of working memory in the same cortical regions.

“The knowledge of uncertainty of memory also guides people to seek more information when we are unsure of our own memory,” Li says in noting the utility of the findings.

Neuroimaging study reveals potential brain mechanism underlying chronic neuropathic pain in individuals with HIV

As medical advances help individuals with HIV survive longer, there is an increasing need to treat their chronic symptoms. One of the most common is neuropathic pain, or pain caused by damage to the nervous system.

Distal sensory polyneuropathy (DSP) is the most prevalent neurological problem in HIV infection, affecting 50 percent of all HIV patients. Most persons with DSP describe sensations of numbness, tingling, burning and stinging in their hands or feet, which impair daily functioning and can lead to unemployment and depression.

Previous research on DSP has mostly focused on the peripheral nervous system, but nerve injury cannot fully explain the wide variability in DSP symptoms. Researchers at University of California San Diego School of Medicine and University of California San Francisco instead looked at the brain to see how it may be contributing to patients’ pain.

In a new study, published online October 29, 2021 in Brain Communications, the team observed unique patterns of brain activity in HIV-DSP patients when they experienced a painful stimulus. Compared to other patients with HIV, those with DSP showed increased activity in the anterior insula, a brain area involved in predicting and emotionally processing pain.

“The anterior insula is trying to predict the future for you,” said senior author Alan Simmons, PhD, professor of psychiatry at UC San Diego School of Medicine and research scientist at the Veterans Affairs San Diego Healthcare System. “It’s forming expectations about what is about to happen to you and how you’re going to feel. These expectations of pain play an important role in determining how much pain you then actually experience.”

Pictured: HIV patients with and without chronic neuropathic pain received short or long heat stimuli on their hands (control site) or feet (neuropathic site).

Not So Great Expectations: Pain in HIV Related to Brain’s Expectations of Relief

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