搜索结果：Brain sciences

Engineers at Northwestern University have taken a striking leap toward merging machines with the human brain by printing artificial neurons that can actually communicate with real ones。 These flexible, low-cost devices generate lifelike electrical signals capable of activating living brain cells, a breakthrough demonstrated in mouse brain tissue

Scientists have uncovered a surprising link between simple body movement and brain health: every time you tighten your abdominal muscles—even slightly—your brain may gently sway inside your skull。 This subtle motion, triggered by pressure changes in connected blood vessels, appears to help circulate cerebrospinal fluid around the brain, potentially

Fish oil has long been praised as brain-boosting, but new research suggests the story may be more complicated。 Scientists found that in people with repeated mild head injuries, a key omega-3 fatty acid in fish oil—EPA—may actually interfere with the brain’s ability to repair itself。 Instead of helping recovery, it appears to weaken blood vessel sta

Scientists at MIT discovered that chaotic laser light can spontaneously form a highly focused beam instead of scattering—if the conditions are just right。 This “pencil beam” enabled them to image the blood-brain barrier in 3D at speeds 25 times faster than existing techniques。 The method also lets researchers watch how drugs move into brain cells i

Scientists have discovered a way to help the brain clean itself of harmful Alzheimer’s plaques by activating its own support cells。 By increasing a protein called Sox9, researchers were able to boost the activity of astrocytes, star shaped cells that help maintain brain health。 In mice that already showed memory problems, this approach reduced plaq

Deep within the brain, scientists have uncovered a hidden “switch” that may decide whether pain fades away—or lingers for months or even years。 Researchers found that a small, little-known region called the caudal granular insular cortex (CGIC) acts like a command center, telling the body to keep pain signals alive long after an injury has healed。

A breakthrough in brain-inspired computing could make today’s energy-hungry AI systems far more efficient。 Researchers have engineered a new nanoelectronic device using a modified form of hafnium oxide that mimics how neurons process and store information at the same time。 Unlike conventional chips that waste energy moving data back and forth, this

Reviewing the history of the development of artificial intelligence (AI) clearly reveals that brain science has resulted in breakthroughs in AI, such as deep learning. At present, although the developmental trend in AI and its applications has surpassed expectations, an insurmountable gap remains between AI and human intelligence. It is urgent to establish a bridge between brain science and AI research, including a link from brain science to AI, and a connection from knowing the brain to simulating the brain. The first steps toward this goal are to explore the secrets of brain science by studying new brain-imaging technology; to establish a dynamic connection diagram of the brain; and to integrate neuroscience experiments with theory, models, and statistics. Based on these steps, a new generation of AI theory and methods can be studied, and a subversive model and working mode from machine perception and learning to machine thinking and decision-making can be established. This article discusses the opportunities and challenges of adapting brain science to AI.

A renowned neuroscientist explains how our brains and bodies give rise to knowledge, creativity, and mental experience Burgeoning advancements in brain science are opening up new perspectives on how we acquire knowledge. Indeed, it is now possible to explore consciousness-the very center of human concern-by scientific means. In this illuminating book, Dr. Gerald M. Edelman offers a new theory of knowledge based on striking scientific findings about how the brain works. And he addresses the related compelling question: Does the latest research imply that all knowledge can be reduced to scientific description? Edelman's brain-based approach to knowledge has rich implications for our understanding of creativity, of the normal and abnormal functioning of the brain, and of the connections among the different ways we have of knowing. While the gulf between science and the humanities and their respective views of the world has seemed enormous in the past, the author shows that their differences can be dissolved by considering their origins in brain functions. He foresees a day when brain-based devices will be conscious, and he reflects on this and other fascinating ideas about how we come to know the world and ourselves.

Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/.

Neuroeconomics, neuromarketing, neuroaesthetics, and neurotheology are just a few of the novel disciplines that have been inspired by a combination of ancient knowledge together with recent discoveries about how the human brain works. The mass media are full of news items featuring colour photos of the brain, that show us the precise location in which a certain thought or emotion, or even love occurs, hence leading us to believe that we can directly observe, with no mediation, the brain at work. But is this really so? Even throughout the developed world, the general public has been seduced into believing that any study, research article, or news report, accompanied by a brain image or two is more reliable and more scientific, than one featuring more mundane illustrations. This fascinating, accessible, and thought provoking new book questions our obsession with brain imaging. Written by two highly experienced psychologists, it discusses some of the familiar ideas usually associated wtih mind-body, brain-psyche, and nature-culture relationships, showing how the biased and unquestioning use of brain imaging technology could have significant cultural effects for all of us.

Brain science accelerates the study of intelligence and behavior, contributes fundamental insights into human cognition, and offers prospective treatments for brain disease. Faced with the challenges posed by imaging technologies and deep learning computational models, big data and high-performance computing (HPC) play essential roles in studying brain function, brain diseases, and large-scale brain models or connectomes. We review the driving forces behind big data and HPC methods applied to brain science, including deep learning, powerful data analysis capabilities, and computational performance solutions, each of which can be used to improve diagnostic accuracy and research output. This work reinforces predictions that big data and HPC will continue to improve brain science by making ultrahigh-performance analysis possible, by improving data standardization and sharing, and by providing new neuromorphic insights.