Alison Abbott In October 2013, I attended the launch of the Human Brain Project in Lausanne, Switzerland, as correspondent for Nature. I hoped to leave with a better understanding of the exact mission of the baffling billion-euro enterprise, but I was frustrated. Things became clear the following year, when the project fell spectacularly, and very publicly, apart. Noah Hutton’s documentary In Silico captures a sense of what it was like behind the scenes of the project, which was supported with great fanfare by the European Commission. It had been hyped as a quantum leap in understanding how the human brain works. Instead, it left a trail of angry neuroscientists across Europe. Yet aspects of what went so expensively wrong still remain elusive. In Silico is more about the back story of the Human Brain Project (HBP). Hutton was 22 years old when he watched a 2009 talk by Henry Markram, the controversial figure who later became the first director of the HBP. Markham was speaking about the Blue Brain Project, a major initiative he had launched a few years before at one of Europe’s top universities, the Swiss Federal Institute of Technology in Lausanne, with generous funding from the Swiss government. He claimed that he would — with the help of a supercomputer related to the one that beat world chess champion Garry Kasparov in 1997 — simulate an entire rodent brain within a decade. He planned to build it from information about the brain’s tens of millions of individual neurons. © 2020 Springer Nature Limited

Keyword: Brain imaging
Link ID: 27614 - Posted: 12.09.2020

by Laura Dattaro Autistic boys with large brains in early childhood still have large brains in adolescence, according to a new study. Autistic girls, too, have brains that grow differently from those of their non-autistic peers. The findings challenge the long-standing idea that brain enlargement in autism is temporary. Previous studies indicated that young children on the spectrum have larger brains than their non-autistic peers but older people with autism do not. To explain the difference, researchers speculated that a pruning process follows early brain overgrowth. But the changes are a mirage, the researchers behind the new study say: Because having a large brain is associated with a low intelligence quotient (IQ) and severe autism traits, and because older children with such characteristics are often excluded from imaging studies, the prior results reflect only a lack of older participants with large brains. “This whole idea of this early overgrowth followed by normalization is just an artifact of sampling bias,” says lead investigator Christine Wu Nordahl, associate professor of psychiatry and behavioral sciences at the University of California, Davis MIND Institute. “It was sort of like, ‘Wow, why didn’t we ever think about this before?’ But it’s pretty clear that that’s what’s happening.” Autistic and non-autistic children also show different development patterns in their white matter — fibers that connect regions of the brain — in early childhood, a second study from Nordahl’s group shows. Some of the differences correlate with changes in the children’s autism traits over time. © 2020 Simons Foundation

Keyword: Autism; Brain imaging
Link ID: 27598 - Posted: 11.30.2020

By Lindsay Gray When Herbert Weinstein stood trial for the murder of his wife in 1992, his attorneys were struck by the measured calm with which he recounted her death and the events leading up to it. He made no attempt to deny that he was culpable, and yet his stoicism in the face of his wildly uncharacteristic actions led his defense to suspect that he might not be. Weinstein underwent neuroimaging tests, which confirmed what his attorneys had suspected: a cyst had impinged upon large parts of Weinstein’s frontal lobe, the seat of impulse control in the brain. On these grounds, they reasoned he should be found not guilty by reason of insanity, despite Weinstein’s free admission of guilt. Guilt is difficult to define, but it pervades every aspect of our lives, whether we’re chastising ourselves for skipping a workout, or serving on the jury of a criminal trial. Humans seem to be hardwired for justice, but we’re also saddled with a curious compulsion to diagram our own emotional wiring. This drive to assign a neurochemical method to our madness has led to the generation of vast catalogs of neuroimaging studies that detail the neural underpinnings of everything from anxiety to nostalgia. In a recent study, researchers now claim to have moved us one step closer to knowing what a guilty brain looks like. Since guilt carries different weight depending on context or culture, the authors of the study chose to define it operationally as the awareness of having harmed someone else. A series of functional magnetic resonance imaging (fMRI) experiments across two separate cohorts, one Swiss and one Chinese, revealed what they refer to as a “guilt-related brain signature” that persists across groups. Since pervasive guilt is a common feature in severe depression and PTSD, the authors suggest that a neural biomarker for guilt could offer more precise insight into these conditions and, potentially, their treatment. But brain-based biomarkers for complex human behaviors also lend themselves to the more ethically fraught discipline of neuroprediction, an emergent branch of behavioral science that combines neuroimaging data and machine learning to forecast how an individual is likely to act based on how their brain scans compare to those of other groups. © 2020 Scientific American,

Keyword: Stress; Brain imaging
Link ID: 27591 - Posted: 11.21.2020

Researchers at the National Eye Institute (NEI) have decoded brain maps of human color perception. The findings, published today in Current Biology, open a window into how color processing is organized in the brain, and how the brain recognizes and groups colors in the environment. The study may have implications for the development of machine-brain interfaces for visual prosthetics. NEI is part of the National Institutes of Health. “This is one of the first studies to determine what color a person is seeing based on direct measurements of brain activity,” said Bevil Conway, Ph.D., chief of NEI’s Unit on Sensation, Cognition and Action, who led the study. “The approach lets us get at fundamental questions of how we perceive, categorize, and understand color.” The brain uses light signals detected by the retina’s cone photoreceptors as the building blocks for color perception. Three types of cone photoreceptors detect light over a range of wavelengths. The brain mixes and categorizes these signals to perceive color in a process that is not well understood. To examine this process, Isabelle Rosenthal, Katherine Hermann, and Shridhar Singh, post-baccalaureate fellows in Conway’s lab and co-first authors on the study, used magnetoencephalography or “MEG,” a 50-year-old technology that noninvasively records the tiny magnetic fields that accompany brain activity. The technique provides a direct measurement of brain cell activity using an array of sensors around the head. It reveals the millisecond-by-millisecond changes that happen in the brain to enable vision. The researchers recorded patterns of activity as volunteers viewed specially designed color images and reported the colors they saw.

Keyword: Vision; Brain imaging
Link ID: 27588 - Posted: 11.21.2020

In a 2009 TED Talk, Israeli neuroscientist Henry Markram made a shocking claim: he was going to create a machine version of human brain within 10 years. The project was catnip to filmmaker Noah Hutton, who began documenting Markram's quest. Ultimately, Hutton followed Markram for a decade — but the scientist's lofty goal remains conspicuously incomplete. The resulting film, In Silico, finally makes its world premiere as part of the online version of the DOC NYC film festival on November 11. The film traces Markram’s journey with the Human Brain Project, from the project’s inception to its $1.4 billion in funding from the European Commission — and how it failed to meet its 10-year goal by 2019. Following a neuroscientist for a decade reveals a lot of highs and lows. Hutton presents the controversies by interviewing both the Human Brain Project team and its critics, including Princeton neuroscientist Sebastian Seung, researcher Zach Mainen at the Champalimaud Centre for the Unknown based in Portugal, and experimental cognitive psychologist Stanislas Dehane, who is professor at Collège de France in Paris. The film also features candid interviews with neuroscientists Christof Koch, who head's up the Allen Institute's MindScope Program, Harvard University's Jeremy R. Knowles Professor of Molecular and Cellular Biology Jeff W. Lichtman, and Stanford University neuroscience adjunct professor David Eagleman. Neuroscientists Idan Segev of Hebrew University in Israel, Cori Bargmann, Torsten N. Weisel Professor of Genetics and Genomics and Neuroscience and Behavior at Rockefeller University, and Cold Spring Harbor Lab professor Anne Churchland.

Keyword: Brain imaging
Link ID: 27577 - Posted: 11.14.2020

By Sundas Hashmi It was the afternoon of Jan. 31. I was preparing for a dinner party and adding final touches to my cheese platter when everything suddenly went dark. I woke up feeling baffled in a hospital bed. My husband filled me in: Apparently, I had suffered a massive seizure a few hours before our guests were to arrive at our Manhattan apartment. Our children’s nanny found me and I was rushed to the hospital. That had been three days earlier. My husband and I were both mystified: I was 37 years old and had always been in excellent health. In due course, a surgeon dropped by and told me I had a glioma, a type of brain tumor. It was relatively huge but operable. I felt sick to my stomach. Two weeks later, I was getting wheeled to the operating theater. I wouldn’t know the pathology until much later. I said my goodbyes to everyone — most importantly to my children, Sofia, 6, and Nyle, 2 — and prepared to die. But right before the surgery, in a very drugged state, I asked the surgeon to please get photos of me and my brother from my husband. I wanted the surgeon to see them. My brother had died two decades earlier from a different kind of brain tumor — a glioblastoma. I was 15 at the time, and he was 18. He died within two years of being diagnosed. Those two years were the worst period of my life. Doctors in my home country of Pakistan refused to take him, saying his case was fatal. So, my parents gathered their savings and flew him to Britain, where he was able to get a biopsy (his tumor was in an inoperable location) and radiation. Afterward, we had to ask people for donations so he could get the gamma knife treatment in Singapore that my parents felt confident would save him. In the end, nothing worked, and he died, taking 18 years of memories with him. © 2020 The New York Times Company

Keyword: Glia
Link ID: 27536 - Posted: 10.21.2020

Adrian Owen DR. ADRIAN OWEN: Imagine this scenario. You've unfortunately had a terrible accident. You're lying in a hospital bed and you're aware—you're aware but you're unable to respond, but the doctors and your relatives don't know that. You have to lie there, listening to them deciding whether to let you live or die. I can think of nothing more terrifying. Communication is at the very heart of what makes us human. It's the basis of everything. What we're doing is we're returning the ability to communicate to some patients who seem to have lost that forever. The vegetative state is often referred to as a state of wakefulness without awareness. Patients open their eyes, they'll just gaze around the room. They'll have sleeping and waking cycles, but they never show any evidence of having any awareness. So, typically, the way that we assess consciousness is through command following. We ask somebody to do something, say, squeeze our hand, and if they do it, you know that they're conscious. The problem in the vegetative state is that these patients by definition can produce no movements. And the question I asked is, well, could somebody command follow with their brain? It was that idea that pushed us into a new realm of understanding this patient population. When a part of your brain is involved in generating a thought or performing an action, it burns energy in the form of glucose, and it's replenished through blood flow. As blood flows to that part of the brain, we're able to see that with the FMRI scanner. I think one of the key insights was the realization that we could simply get somebody to lie in the scanner and imagine something and, based on the pattern of brain activity, we will be able to work out what it is they were thinking. We had to find something that produces really a quite distinct pattern of activity that was more or less the same for everybody. So, we came up with two tasks. One task, imagine playing tennis, produces activity in the premotor cortex in almost every healthy person we tried this in. A different task, thinking about moving from room to room in your house, produces an entirely different pattern of brain activity; particularly, it involves a part of the brain known as the parahippocampal gyrus. And again, it's very consistent across different people.

Keyword: Consciousness; Brain imaging
Link ID: 27513 - Posted: 10.07.2020

by Angie Voyles Askham Autistic people share some brain structure differences with people who have other neuropsychiatric conditions, including schizophrenia and attention deficit hyperactivity disorder (ADHD), according to a massive new brain-imaging study1. These shared differences stem from the atypical development of one particular type of neuron, the findings suggest. The results provide “further evidence that our understanding of autism can really be advanced by explicitly studying autism in the context of other disorders,” says Armin Raznahan, chief of the Section on Developmental Neurogenomics at the U.S. National Institute of Mental Health in Bethesda, Maryland, who was not involved in the study. The researchers looked at brain scans from 28,321 people to identify structural changes associated with any of six conditions: autism, ADHD, bipolar disorder, major depressive disorder, obsessive-compulsive disorder and schizophrenia. The team found that the brains of people with these conditions differ from controls in a specific way: They have similar patterns of thickness across the cortex, the brain’s outer layer. The cortical regions with the biggest differences in thickness are typically rich in a particular type of excitatory neuron. “We were able to put our fingers on what might be behind that commonality,” says lead researcher Tomas Paus, professor of psychology and psychiatry at the University of Toronto in Canada. “That was very exciting.” The work combined data from 145 cohorts within the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, an international group of researchers who collect and analyze brain-scan data in a standardized way so that they can pool their results. © 2020 Simons Foundation

Keyword: Autism; Brain imaging
Link ID: 27503 - Posted: 10.03.2020

By Rebekah Tuchscherer Call it neuroscience on the go. Scientists have developed a backpack that tracks and stimulates brain activity as people go about their daily lives. The advance could allow researchers to get a sense of how the brain works outside of a laboratory—and how to monitor diseases such as Parkinson’s and post-traumatic stress disorder in real-world settings. The technology is “an inspiring demonstration of what’s possible” with portable neuroscience equipment, says Timothy Spellman, a neurobiologist at Weill Cornell Medicine who was not involved with the work. The backpack and its vast suite of tools, he says, could broaden the landscape for neuroscience research to study the brain while the body is in motion. Typically, when scientists want to scan the brain, they need a lot of room—and a lot of money. Functional magnetic resonance imaging (fMRI) scanners, which detect activity in various regions of the brain, are about the size of a pickup truck and can cost more than $1 million. And patients must stay still in the machine for about 1 hour to ensure a clear, readable scan. © 2020 American Association for the Advancement of Science.

Keyword: Brain imaging
Link ID: 27479 - Posted: 09.19.2020

For Armin Raznahan, publishing research on sex differences is a fraught proposition. Now chief of the section on developmental neurogenomics at the National Institutes of Health, Raznahan learned early that searching for dissimilarities between men’s and women’s brains can have unintended effects. “I got my fingers burned when I first started,” Raznahan says. As a PhD student, he published a study that examined structural differences between men’s and women’s brains and how they changed with age. “We observed a particular pattern, and we were very cautious about just describing it, as one should be, not jumping to functional interpretations,” he says. Despite his efforts, The Wall Street Journal soon published an article that cited his study in a defense of single-sex schooling, under the assumption that boys and girls must learn in distinct ways because their brain anatomy is slightly different. “That really threw me,” he says. “The experience has stayed with me.” Nevertheless, Raznahan has continued to study sex differences, in the hope that they could help us better understand neurodevelopmental disorders. He focuses on people with sex chromosome aneuploidy, or any variation other than XX (typically female) and XY (typically male). People with genetic variations (such as XXY) have an inflated risk of autism spectrum disorder, ADHD, and anxiety, among other ailments. Raznahan’s hope is that uncovering if and how men’s and women’s brains differ—for example, in the sizes of regions or the strengths of the connections among them—could help us figure out why people with aneuploidy are more likely to experience neurodevelopmental and psychiatric concerns. Solving this puzzle could be a step toward unlocking the perplexing mystery of psychiatric illness. © 2020 Condé Nast

Keyword: Sexual Behavior; Brain imaging
Link ID: 27451 - Posted: 09.05.2020

By Moises Velasquez-Manoff Jack Gallant never set out to create a mind-reading machine. His focus was more prosaic. A computational neuroscientist at the University of California, Berkeley, Dr. Gallant worked for years to improve our understanding of how brains encode information — what regions become active, for example, when a person sees a plane or an apple or a dog — and how that activity represents the object being viewed. By the late 2000s, scientists could determine what kind of thing a person might be looking at from the way the brain lit up — a human face, say, or a cat. But Dr. Gallant and his colleagues went further. They figured out how to use machine learning to decipher not just the class of thing, but which exact image a subject was viewing. (Which photo of a cat, out of three options, for instance.) One day, Dr. Gallant and his postdocs got to talking. In the same way that you can turn a speaker into a microphone by hooking it up backward, they wondered if they could reverse engineer the algorithm they’d developed so they could visualize, solely from brain activity, what a person was seeing. The first phase of the project was to train the AI. For hours, Dr. Gallant and his colleagues showed volunteers in fMRI machines movie clips. By matching patterns of brain activation prompted by the moving images, the AI built a model of how the volunteers’ visual cortex, which parses information from the eyes, worked. Then came the next phase: translation. As they showed the volunteers movie clips, they asked the model what, given everything it now knew about their brains, it thought they might be looking at. The experiment focused just on a subsection of the visual cortex. It didn’t capture what was happening elsewhere in the brain — how a person might feel about what she was seeing, for example, or what she might be fantasizing about as she watched. The endeavor was, in Dr. Gallant’s words, a primitive proof of concept. And yet the results, published in 2011, are remarkable. The reconstructed images move with a dreamlike fluidity. In their imperfection, they evoke expressionist art. (And a few reconstructed images seem downright wrong.) But where they succeed, they represent an astonishing achievement: a machine translating patterns of brain activity into a moving image understandable by other people — a machine that can read the brain. © 2020 The New York Times Company

Keyword: Vision; Brain imaging
Link ID: 27448 - Posted: 09.02.2020

When it comes to brain cells, one size does not fit all. Neurons come in a wide variety of shapes, sizes, and contain different types of brain chemicals. But how did they get that way? A new study in Nature suggests that the identities of all the neurons in a worm are linked to unique members of a single gene family that control the process of converting DNA instructions into proteins, known as gene expression. The results of this study could provide a foundation for understanding how nervous systems have evolved in many other animals, including humans. The study was funded by the National Institute of Neurological Disorders and Stroke (NINDS), part of the National Institutes of Health. “The central nervous systems of all animals, from worms to humans, are incredibly intricate and highly ordered. The generation and diversity of a plethora of neuronal cell types is driven by gene expression,” said Robert Riddle, Ph.D., program director at NINDS. “So, it is surprising and exciting to consider that the cell diversity we see in the entire nervous system could come from a just a single group of genes.” Researchers led by Oliver Hobert, Ph.D., professor of biochemistry and molecular biophysics at Columbia University in New York City and graduate student Molly B. Reilly, wanted to know how brain cells in the C. elegans worm got their various shapes and functions. For these experiments, the researchers used a genetically engineered worm in which individual neurons were color coded. In addition, coding sequences for green fluorescence protein were inserted into homeobox genes, a highly conserved set of genes known to play fundamental roles in development. Homeobox gene expression patterns were determined by examining the patterns of the glowing fluorescent marker.

Keyword: Development of the Brain; Brain imaging
Link ID: 27428 - Posted: 08.20.2020

By Abdul-Kareem Ahmed “He doesn’t look like himself,” his wife said. It was midnight, and I was consulting on a patient in the emergency room. He was 48 years old and complaining of a headache. Ten years ago my attending had partially removed a benign tumor growing in his cerebellum, part of the hindbrain that controls movement, coordination and speech. Our team had also placed a shunt in his brain. The brain is buoyed and bathed by cerebrospinal fluid. This clear fluid is made in large cavities, called ventricles, and is eventually absorbed by veins. The tumor’s inoperable remnant had blocked the fluid’s natural escape, causing it to build up, a condition known as hydrocephalus. A shunt is a thin rubber tube that is placed in the ventricles of the brain and tunneled under the skin, into the abdomen. It can have a programmable pressure valve, a gauge that sits under the scalp. His shunt had been siphoning excess fluid to his abdomen for years where it was absorbed, preventing life-threatening high pressure in the brain. Today, however, something was wrong, and I thought it was revealed on his new head CT. His ventricles were very large, suggesting high pressure. “I get a bad headache when I sit up,” he mumbled. “Sometimes I vomit. I feel better when I lie flat.” His wife, a strong and kindhearted woman, corroborated his complaint. “He’s also having memory problems, and he’s losing his balance when he walks,” she added. His symptoms were the opposite of what I expected. He was describing a low-pressure headache. He was relieved by lying down but worsened when sitting up.

Keyword: Pain & Touch
Link ID: 27397 - Posted: 08.03.2020

"Julich-Brain" is the name of the first 3D-atlas of the human brain that reflects the variability of the brain’s structure with microscopic resolution. The atlas features close to 250 structurally distinct areas, each one based on the analysis of 10 brains. More than 24000 extremely thin brain sections were digitized, assembled in 3D and mapped by experts. As part of the new EBRAINS infrastructure of the European Human Brain Project, the atlas serves as an interface to link different information about the brain in a spatially precise way. German researchers led by Prof. Katrin Amunts have now presented the new brain atlas in the renowned journal Science. Under the microscope, it can be seen that the human brain is not uniformly structured, but divided into clearly distinguishable areas. They differ in the distribution and density of nerve cells and in function. With the Julich-Brain, researchers led by Katrin Amunts now present the most comprehensive digital map of the cellular architecture and make it available worldwide via the EBRAINS research infrastructure. "On the one hand, the digital brain atlas will help to interpret the results of neuroimaging studies, for example of patients, more accurately", says Katrin Amunts, Director at the German Research Center Juelich and Professor at the University of Düsseldorf. "On the other hand, it is becoming the basis for a kind of 'Google Earth' of the brain - because the cellular level is the best interface for linking data about very different facets of the brain. ©2017 Human Brain Project.

Keyword: Brain imaging
Link ID: 27396 - Posted: 08.03.2020

By Karen Kwon, Liz Tormes In 1968 an exhibit entitled Cybernetic Serendipity: The Computer and the Arts was held at the Institute of Contemporary Arts in London. The first major event of its kind, Cybernetic Serendipity’s aim was to “present an area of activity which manifests artists’ involvement with science, and the scientists’ involvement with the arts,” wrote British art critic Jasia Reichardt, who curated the exhibit. Even though it was an art show, “most of the participants in the exhibition were scientists,” Reichardt said in a 2014 video. “Artists didn’t have computers in the 1960s.” A lot has changed since then, however. Computers, no longer the commodity of a select few, help artists to deviate from more traditional mediums. The changes since the 1960s are well-reflected in the entries for the 2020 Art of Neuroscience competition, held by the Netherlands Institute for Neuroscience. Now marking its 10th year, the contest features some highly technological pieces and others grounded in classical methods, such as drawing with pen on paper. The winning entries were created by independent artists, as well as working scientists, demonstrating that art and neuroscience can inspire both professions. A winner and four honorable mentions were selected from dozens of submitted works. And seven pieces were chosen by Scientific American as Editors’ Picks. (Photography editor Liz Tormes served on the panel of judges for the competition.) © 2020 Scientific American

Keyword: Brain imaging
Link ID: 27381 - Posted: 07.25.2020

Salvatore Domenic Morgera How the brain works remains a puzzle with only a few pieces in place. Of these, one big piece is actually a conjecture: that there’s a relationship between the physical structure of the brain and its functionality. The brain’s jobs include interpreting touch, visual and sound inputs, as well as speech, reasoning, emotions, learning, fine control of movement and many others. Neuroscientists presume that it’s the brain’s anatomy – with its hundreds of billions of nerve fibers – that make all of these functions possible. The brain’s “living wires” are connected in elaborate neurological networks that give rise to human beings’ amazing abilities. It would seem that if scientists can map the nerve fibers and their connections and record the timing of the impulses that flow through them for a higher function such as vision, they should be able to solve the question of how one sees, for instance. Researchers are getting better at mapping the brain using tractography – a technique that visually represents nerve fiber routes using 3D modeling. And they’re getting better at recording how information moves through the brain by using enhanced functional magnetic resonance imaging to measure blood flow. But in spite of these tools, no one seems much closer to figuring out how we really see. Neuroscience has only a rudimentary understanding of how it all fits together. To address this shortcoming, my team’s bioengineering research focuses on relationships between brain structure and function. The overall goal is to scientifically explain all the connections – both anatomical and wireless – that activate different brain regions during cognitive tasks. We’re working on complex models that better capture what scientists know of brain function. t © 2010–2020, The Conversation US, Inc.

Keyword: Brain imaging
Link ID: 27373 - Posted: 07.18.2020

By Arianne Cohen1 minute Read You know all those studies about brain activity? The ones that reveal thought patterns and feelings as a person performs a task? There’s a problem: The measurement they’re based on is inaccurate, according to a study out of Duke University that is rocking the field. Functional MRI machines (fMRIs) are excellent at determining the brain structures involved in a task. For example, a study asking 50 people to count or remember names while undergoing an fMRI scan would accurately identify which parts of the brain are active during the task. Brain scans showing functional MRI mapping for three tasks across two different days. Warm colors show the high consistency of activation levels across a group of people. Cool colors represent how poorly unique patterns of activity can be reliably measured in individuals. View image larger here. [Image: Annchen Knodt/Duke University] The trouble is that when the same person is asked to do the same tasks weeks or months apart, the results vary wildly. This is likely because fMRIs don’t actually measure brain activity directly: They measure blood flow to regions of the brain, which is used as a proxy for brain activity because neurons in those regions are presumably more active. Blood flow levels, apparently, change. “The correlation between one scan and a second is not even fair, it’s poor,” says lead author Ahmad Hariri, a professor of neuroscience and psychology at Duke University. The researchers reexamined 56 peer-reviewed, published papers that conducted 90 fMRI experiments, some by leaders in the field, and also looked at the results of so-called “test/retest” fMRIs, where 65 subjects were asked to do the same tasks months apart. They found that of seven measures of brain function, none had consistent readings.

Keyword: Brain imaging
Link ID: 27339 - Posted: 07.01.2020

The Human Brain Project (HBP) has announced the start of its final phase as an EU-funded FET Flagship. The European Commission has signed a grant agreement to fund the HBP with 150 million Euros from now until 2023. Over the next three years, the project will narrow its focus to advance three core scientific areas – brain networks, their role in consciousness, and artificial neural nets – while expanding its innovative EBRAINS infrastructure. EBRAINS offers the most comprehensive atlas and database on the human brain, directly coupled with powerful computing and simulation tools, to research communities around neuroscience, medicine and technology. Currently transitioning into a sustainable infrastructure, EBRAINS will remain available to the scientific community, as a lasting contribution of the HBP to global scientific progress. Supercomputers, Big Data Analytics, Simulation, Robots and AI have all become new additions to the “toolbox” of modern neuroscience – a development strongly pushed forward by the HBP and its EBRAINS infrastructure. Started in 2013 as a FET Flagship project, the HBP is the largest brain science project in Europe. Now entering the final phase of its ten-year lifespan, the project is proud to present its scientific workplan and transformative technological offerings for brain research and brain-inspired research and development. HBP’s scientific activities in the new phase focus on three topics: networks that are studied across different spatial and temporal scales, their significance for consciousness and disorders of consciousness, and the development of artificial neural networks and neurorobotics.

Keyword: Brain imaging
Link ID: 27337 - Posted: 07.01.2020

Ruth Williams Turning off just one factor in the brain’s astrocyte cells is sufficient to convert them into neurons in live mice, according to a paper published in Nature today (June 24) and one this spring by another research team in Cell. By flipping this cellular identity switch, researchers have, to some extent, been able to reverse the neuron loss and motor deficits caused by a Parkinson’s-like illness. Not everyone is entirely convinced by the claims. “I think this is very exciting work,” says Pennsylvania State University’s Gong Chen of the Nature paper. It reaffirms that “using the brain’s internal glial cells to regenerate new neurons is a really new avenue for the treatment of brain disorders,” he continues. Chen, who is also based at Jinan University and is the chief scientific officer for NeuExcell—a company developing astrocyte-to-neuron conversion therapies—has performed such conversions in the living mouse brain by a different method but was not involved in the new study. In Parkinson’s disease, dopaminergic neurons within the brain’s substantia nigra—a region in the midbrain involved in movement and reward—gradually die. This results in a deterioration of motor control, characterized by tremors and other types of dyskinesia, with other faculties such as cognition and mood sometimes affected too, especially at later stages of the disease. While treatments to boost diminishing dopamine levels, such as the drug levodopa, can ameliorate symptoms, none can stop the underlying disease process that relentlessly eats away at the patient’s neurological functions and quality of life. © 1986–2020 The Scientist.

Keyword: Parkinsons; Glia
Link ID: 27324 - Posted: 06.26.2020

Published by Steven Novella under Neuroscience This is an important and sobering study, that I fear will not get a lot of press attention – especially in the context of current events. It is a bit wonky, but this is exactly the level of knowledge one needs in order to be able to have any chance of consuming and putting into context scientific research. I have discussed fMRI previously – it stands for functional magnetic resonance imaging. It uses MRI technology to image blood flow to different parts of the brain, and from that infer brain activity. It is used more in research than clinically, but it does have some clinical application – if, for example, we want to see how active a lesion in the brain is. In research it is used to help map the brain, to image how different parts of the brain network and function together. It is also used to see which part of the brain lights up when subjects engage in specific tasks. It is this last application of fMRI that was studied. Professor Ahmad Hariri from Duke University just published a reanalysis of the last 15 years of his own research, calling into question its validity. Any time someone points out that an entire field of research might have some fatal problems, it is reason for concern. But I do have to point out the obvious silver lining here – this is the power of science, self-correction. This is a dramatic example, with a researcher questioning his own research, and not afraid to publish a study which might wipe out the last 15 years of his own research. Copyright © 2020 All Rights Reserved .

Keyword: Brain imaging
Link ID: 27288 - Posted: 06.08.2020