{"id":3935,"date":"2019-07-27T16:18:21","date_gmt":"2019-07-27T07:18:21","guid":{"rendered":"http:\/\/163.180.4.222\/lab\/?p=3935"},"modified":"2019-07-27T16:18:21","modified_gmt":"2019-07-27T07:18:21","slug":"how-to-map-the-brain","status":"publish","type":"post","link":"https:\/\/biochemistry.khu.ac.kr\/lab\/?p=3935","title":{"rendered":"How to map the brain"},"content":{"rendered":"<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<h5>As efforts to chart the brain\u2019s neurons gather pace, researchers must find a way to make the accumulating masses of data useful.<\/h5>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<div class=\"article__body serif cleared\">\n<figure class=\"figure\">\n<div class=\"embed intensity--high\">\n<div class=\"embed intensity--high\"><img decoding=\"async\" class=\"figure__image\" src=\"https:\/\/media.nature.com\/w800\/magazine-assets\/d41586-019-02208-0\/d41586-019-02208-0_16961106.jpg\" alt=\"\" data-src=\"\/\/media.nature.com\/w800\/magazine-assets\/d41586-019-02208-0\/d41586-019-02208-0_16961106.jpg\" \/><\/div>\n<\/div><figcaption>\n<p class=\"figure__caption sans-serif\"><span class=\"mr10\">The synapse between two neurons (retinal ganglion cell, blue; amacrine cell, yellow) in a mouse retina reconstructed for neuron-mapping game Eyewire.<\/span>Credit: Alex Norton\/Eyewire<\/p>\n<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>It\u2019s April 2019 at the Allen Institute for Brain Science in Seattle, Washington. In a room containing five transmission electron microscopes, three shiny party balloons are bobbing around. The balloons are to celebrate the institute\u2019s researchers reaching the latest milestone in an effort to map each of the 100,000 neurons and the one billion connections, or synapses, between them in a cubic millimetre of mouse brain \u2014 a sample that\u2019s roughly the size of a grain of sand.<\/p>\n<p>&nbsp;<\/p>\n<aside class=\"recommended pull pull--left sans-serif\" data-label=\"Related\"><a href=\"https:\/\/www.nature.com\/collections\/jigfghaeje\" data-track=\"click\" data-track-label=\"recommended article\"><img decoding=\"async\" class=\"recommended__image\" src=\"https:\/\/media.nature.com\/w400\/magazine-assets\/d41586-019-02208-0\/d41586-019-02208-0_16963858.jpg\" \/><\/a><\/p>\n<p class=\"recommended__title serif\">Part of Nature Outlook: The brain<\/p>\n<\/aside>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>The microscopes ran continuously for five months, collecting more than 100 million images of 25,000 slices of mouse visual cortex, each just 40 nanometres thick. Then, software developed by the institute\u2019s computer scientists took about three months to assemble the images into a single 3D volume. The balloons proclaim the size of the completed data set, spelling out \u201c2PB\u201d (2 petabytes, which is equivalent to 2 million gigabytes) in blue and silver letters. More than 30 years of satellite images of Earth, collected by the Landsat missions, take up only about 1.3 petabytes, which makes the mouse-brain images almost \u201ca world in a grain of sand\u201d, says Clay Reid, a neurobiologist at the Allen Institute, quoting English poet William Blake.<\/p>\n<p>The mouse-brain cubic-millimetre project is just one of several attempts in various species to map a nanoscale connectome \u2014 a wiring diagram of the nervous system with synapse-level detail. Neuroscientists think that these efforts will give them unparalleled insights into how neural circuits encode information and direct behaviour \u2014 in short, how brains work.<\/p>\n<p>The ultimate achievement in this area \u2014 a nanoscale connectome of a whole human brain \u2014 is still a long way off. The human brain has 10<sup>15<\/sup>connections and contains roughly the same number of neurons as there are stars in the Milky Way, around 100 billion. Using current imaging technology, it would take dozens of microscopes, working around the clock, thousands of years just to collect the data required for such an endeavour.<\/p>\n<p>But advances in microscopy, as well as the development of more powerful computers and algorithms for image analysis, have propelled the field of connectomics forwards at a pace that has surprised even those involved. \u201cFive years ago, it felt overly ambitious to be thinking about a cubic millimetre,\u201d Reid says. Many researchers now think that mapping the entire mouse brain \u2014 about 500 cubic millimetres in volume \u2014 might be possible in the next decade. And doing so for the much larger human brain is becoming a legitimate long-term goal. \u201cToday, mapping the human brain at the synaptic level might seem inconceivable. But if steady progress continues, in both computational capabilities and scientific techniques, another factor of 1,000 is not out of the question.\u201d<\/p>\n<p>&nbsp;<\/p>\n<p><strong>All the small things<\/strong><\/p>\n<p>Nanoscale connectomes have been completed in two species: the nematode\u00a0<i>Caenorhabditis elegans<\/i><sup><a href=\"https:\/\/www.nature.com\/articles\/d41586-019-02208-0?utm_source=feedburner&amp;utm_medium=feed&amp;utm_campaign=Feed%3A+nature%2Frss%2Fcurrent+%28Nature+-+Issue%29#ref-CR1\" data-track=\"click\" data-action=\"anchor-link\" data-track-label=\"go to reference\" data-track-category=\"references\">1<\/a><\/sup>, in 1986, and the larva of a marine organism known as\u00a0<i>Ciona intestinalis<\/i><sup><a href=\"https:\/\/www.nature.com\/articles\/d41586-019-02208-0?utm_source=feedburner&amp;utm_medium=feed&amp;utm_campaign=Feed%3A+nature%2Frss%2Fcurrent+%28Nature+-+Issue%29#ref-CR2\" data-track=\"click\" data-action=\"anchor-link\" data-track-label=\"go to reference\" data-track-category=\"references\">2<\/a><\/sup>, in 2016.<\/p>\n<p>These neural maps are a powerful winnowing tool. \u201cThere are a lot of hypotheses that have been refuted by the\u00a0<i>C. elegans<\/i>\u00a0wiring diagram,\u201d says Bobby Kasthuri, a neuroscientist at Argonne National Laboratory in Lemont, Illinois. If an observation about the worm\u2019s nervous system or behaviour can be easily explained by the wiring diagram, there\u2019s no need for further experiments; researchers can move on to more fruitful lines of inquiry. But when the connectome doesn\u2019t offer a ready explanation for results, it can indicate productive directions of research for scientists to explore.<\/p>\n<p>Some researchers do question the focus on nanoscale connectomes. The enormous amount of time, effort and money that goes into such projects might be overkill, says Anthony Movshon, a neuroscientist at New York University in New York City who studies the visual system. When it comes to complex brains such as those of mice or humans, \u201cI don\u2019t need to know the precise details of the wiring of each cell and each synapse in each of those brains,\u201d Movshon says. \u201cWhat I need to know, instead, is the organizational principles that wire them together.\u201d This, he suggests, can be gleaned with a coarser level of resolution.<\/p>\n<p>Yet the nanoscale connectome is a goal that captures the imaginations of many scientists. They say that this work could help to unravel the origins of mental-health conditions and lead to more informed treatments, as well as have applications in a host of fields, including\u00a0<a href=\"https:\/\/www.nature.com\/articles\/d41586-019-02212-4\" data-track=\"click\" data-label=\"https:\/\/www.nature.com\/articles\/d41586-019-02212-4\" data-track-category=\"body text link\">artificial intelligence<\/a>\u00a0and energy-efficient computation.<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Project proliferation<\/strong><\/p>\n<p>To map the nanoscale connectome of\u00a0<i>C. elegans<\/i>, in the 1980s, researchers led by biologist Sydney Brenner at the University of Cambridge, UK, thinly sliced the millimetre-long worms and photographed each slice using a film camera mounted to an electron microscope. In the resulting images, they then painstakingly traced by hand the pathways of neurons and the connections between them.<\/p>\n<p>But\u00a0<i>C. elegans<\/i>\u00a0has a mere 302 neurons and around 7,600 synapses. The methods used to produce its connectome simply weren\u2019t practical to use in larger nervous systems. Researchers did not think seriously about embarking on considerably larger projects until 2004, when physicist Winfried Denk and neuroanatomist Heinz Horstmann, then both at the Max Planck Institute for Medical Research in Heidelberg, Germany, proposed using an automated microscope to slice and image the brain and software to stack and align the resulting images<sup><a href=\"https:\/\/www.nature.com\/articles\/d41586-019-02208-0?utm_source=feedburner&amp;utm_medium=feed&amp;utm_campaign=Feed%3A+nature%2Frss%2Fcurrent+%28Nature+-+Issue%29#ref-CR3\" data-track=\"click\" data-action=\"anchor-link\" data-track-label=\"go to reference\" data-track-category=\"references\">3<\/a><\/sup>.<\/p>\n<p>One of the largest complete nanoscale connectomes to be released represents a roughly 100-micrometre cube of mouse retina containing around 1,000 neurons and 250,000 synapses. Denk, now director of the Max Planck Institute of Neurobiology in Martinsried, Germany, and his collaborator Moritz Helmstaedter, co-director of the Max Planck Institute for Brain Research in Frankfurt, Germany, published the analysis<sup><a href=\"https:\/\/www.nature.com\/articles\/d41586-019-02208-0?utm_source=feedburner&amp;utm_medium=feed&amp;utm_campaign=Feed%3A+nature%2Frss%2Fcurrent+%28Nature+-+Issue%29#ref-CR4\" data-track=\"click\" data-action=\"anchor-link\" data-track-label=\"go to reference\" data-track-category=\"references\">4<\/a><\/sup>\u00a0in 2013. But the mouse-brain cubic-millimetre project will be looking at 100,000 neurons, and other, similar programmes are also under way.<\/p>\n<p>\u201cA cubic millimetre is a size that seems to be sufficient, at least for the neurons in the centre of that grain of sand, to get most of their local connections,\u201d says Nuno da Costa, a neuroscientist at the Allen Institute. The mouse-brain project will therefore enable scientists to explore complete local circuits, rather than single neurons with a sparse network of connections. The work being conducted at the Allen Institute is part of a collaboration with researchers at Baylor College of Medicine in Houston, Texas, Princeton University in New Jersey and Harvard University in Cambridge, Massachusetts, known as Machine Intelligence from Cortical Networks, which is funded by the US government.<\/p>\n<p>&nbsp;<\/p>\n<div class=\"embed intensity--high\">\n<div class=\"ratio--16-9\"><iframe src=\"https:\/\/www.youtube.com\/embed\/irdqVhzG4SQ\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\" data-mce-fragment=\"1\"><\/iframe><\/div>\n<\/div>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>Its progress has led some to predict that the nanoscale connectome of a complete mouse brain \u2014 likely to produce around one exabyte (one billion gigabytes) of data \u2014 could be mapped in the next decade. \u201cIt would require many laboratories,\u201d says Jeff Lichtman, a neuroscientist at Harvard University. \u201cBut it\u2019s doable,\u201d he says, \u201cand that\u2019s exciting.\u201d<\/p>\n<p>Others remain cautious. \u201cThere are so many logistic challenges\u201d to a project of that size, says Stephen Plaza, a computer scientist at the Howard Hughes Medical Institute Janelia Research Campus in Ashburn, Virginia. He thinks that the field should target intermediary-scale projects before tackling something as complex as the mouse brain. \u201cWe\u2019re still in the training-wheels stage of connectomics,\u201d he says.<\/p>\n<p>Plaza manages one such project. Called FlyEM, it aims to produce a connectome of the central nervous system of the fruit fly\u00a0<i>Drosophila melanogaster<\/i>. His team expects to release data on roughly one-third of the\u00a0<i>D. melanogaster<\/i>\u00a0brain in early 2020. Plaza expects that the connectome of the entire central nervous system \u2014 composed of about 100,000 neurons and 100 million connections in the fly\u2019s brain alone, plus a similar number of neurons and synapses in the ventral nerve cord (roughly equivalent to the spinal cord of vertebrates) \u2014 will follow a few years later.<\/p>\n<p>Meanwhile, Lichtman is working on the zebrafish (<i>Danio rerio<\/i>) connectome, as well as analysing a small piece of the human brain \u2014 a sample of the medial temporal gyrus obtained from a person who was undergoing brain surgery for epilepsy. That piece is also roughly one cubic millimetre in volume, but to capture the full thickness of the human cortex, the sample is shaped like a slab, rather than a cube.<\/p>\n<p>Denk and his colleagues are mapping portions of the connectome in the zebra finch (<i>Taeniopygia guttata<\/i>), a small bird whose process of song learning can yield insights into human speech. And Kasthuri has a number of projects in progress. \u201cNow that there is a lot of data available on the circuitry of the mouse brain, I think the best way to do it is to either look across species or look across development,\u201d he says. \u201cThe best information will come from comparing that diagram to other things.\u201d<\/p>\n<p>To that end, Kasthuri aims to map the visual part of the brain in non-human primates, as well as in an octopus (<i>Octopus bimaculoides<\/i>). \u201cIt\u2019s probably the creature that is the most alien to us that\u2019s still smart,\u201d he says, of the octopus. \u201cSo, I\u2019m interested in comparing the wiring of that brain to the wiring of the mouse brain.\u201d<\/p>\n<p>Kasthuri is also working on the full connectomes of young mice and octopuses; comparing these immature connectomes to those of adult animals could offer insights into how the brain learns from experience. Owing to its small size, he hopes to map the young-octopus connectome in about one year.<\/p>\n<p>&nbsp;<\/p>\n<p><strong>AI spy<\/strong><\/p>\n<p>Now that the researchers at the Allen Institute have finished imaging their cubic millimetre of mouse brain, they have passed on the data to Sebastian Seung, a neuroscientist and computer scientist at Princeton University. Seung\u2019s lab will align the resulting images, and then annotate the synapses and trace, or segment, the estimated four kilometres of nerve fibre that are contained within the volume.<\/p>\n<p>Segmentation has long been the rate-limiting step in connectomics. It can take weeks to trace by hand the path of a single neuron through a stack of electron micrographs. But now, artificial intelligence is getting involved. Seung\u2019s team has developed a machine-learning algorithm that can evaluate images pixel by pixel to determine the location of neurons.<\/p>\n<p>Computers can perform segmentation faster than the human eye, which cuts down the time it takes to trace neurons to a matter of minutes or hours. But they aren\u2019t as accurate: algorithms can miss out bits of neuron or incorrectly merge two neurons into one. People are therefore still needed to check the reconstruction. Seung is tackling this requirement through crowdsourcing and, specifically, an online game called Eyewire, in which players are challenged to correct mistakes in the rough draft of a connectome. Launched in 2012, Eyewire has 290,000 registered users who have collectively put in an effort that is equivalent to 32 people working full time for 7 years, says Amy Robinson Sterling, executive director of Eyewire.<\/p>\n<p>&nbsp;<\/p>\n<figure class=\"figure\">\n<div class=\"embed intensity--high\">\n<div class=\"embed intensity--high\"><img decoding=\"async\" class=\"figure__image\" src=\"https:\/\/media.nature.com\/w800\/magazine-assets\/d41586-019-02208-0\/d41586-019-02208-0_16961108.jpg\" alt=\"\" data-src=\"\/\/media.nature.com\/w800\/magazine-assets\/d41586-019-02208-0\/d41586-019-02208-0_16961108.jpg\" \/><\/div>\n<\/div><figcaption>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p class=\"figure__caption sans-serif\"><span class=\"mr10\">The Developing Human Connectome Project is imaging nerve fibres in the brains of newborns.<\/span>Credit: Max Pietsch\/DHCP<\/p>\n<\/figcaption><\/figure>\n<p>So far, players have been tracing cells in the mouse retina. They\u2019ve contributed to the discovery of six types of neuron, which players chose to name after ancient Greek deities. Sterling and her team are preparing a new version of the game, called Neo, that will be used with the mouse visual-cortex data set.<\/p>\n<p>Neo\u2019s interface is based on Neuroglancer, a program developed by Google that visualizes flat, black-and-white electron micrographs as a colourful 3D forest of neurons. Many nanoscale connectome-mapping efforts use the program to visualize data.<\/p>\n<p>Google has also developed an algorithm for neuron segmentation. A team led by Viren Jain at Google AI, in Mountain View, California, has designed a machine-learning algorithm called a flood-filling network, which builds structures from a point in an image, rather than trying to define the boundaries of all neurons at once. \u201cIt\u2019s a little bit like the way a human would colour in a colouring book,\u201d Jain says. His team is applying the technique to FlyEM data and has constructed a rough-draft connectome of a whole fly brain that was imaged by another team at Janelia Research Campus. They are also working with data from the labs of Denk and Lichtman.<\/p>\n<p>\u201cIt\u2019s truly beautiful to look at,\u201d Lichtman says of the result, noting that the algorithm is able to trace neurons faster than his team can collect imaging data. \u201cWe\u2019re not able to keep up with them,\u201d he adds. \u201cThat\u2019s a great place to be.\u201d<\/p>\n<p>Jain strikes a more cautious note, and points out that as scientists take on ever larger projects, segmentation algorithms have to become more accurate to keep feasible the amount of human checking that is required.<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Close look<\/strong><\/p>\n<p>Meanwhile, scientists are honing microscopy techniques to produce sharper, more-detailed images at a much quicker pace, in anticipation of taking on the nanoscale connectomes of large, mammalian brains.<\/p>\n<p>The conventional approach to microscopy in connectomics is a type of electron microscopy known as serial-section electron microscopy. Researchers embed neural tissue in plastic, and cut it into slices that are a fraction of the thickness of a human hair. They then mount the slices on a specialized tape and feed the result \u2014 which looks remarkably similar to film on a reel \u2014 through the microscope.<\/p>\n<p>The advantage of this method is that the sample is preserved and can be re-imaged, if needed. But no matter how precisely it is done, cutting the sample inevitably results in distortions that make it difficult to align the images.<\/p>\n<p>A newer approach, known as focused ion beam scanning electron microscopy (FIB-SEM), uses a beam of charged ions to shave away a thin layer of a tissue sample. The microscope captures an image of the freshly exposed surface, and then the process is repeated. The FlyEM sample represents the first substantial volume to be imaged by this method.<\/p>\n<p>Although it lacks speed, one advantage of FIB-SEM is that the resolution of the images produced is the same in all three dimensions, rather than being coarser along the vertical axis. However, samples can be imaged only once, because they are vaporized in the process. In addition, the field of view is very small, which makes it difficult to apply to larger samples. (Even the fruit-fly brain, which is roughly the size of a poppy seed, has to be chopped into smaller chunks.) A method called gas cluster ion beam scanning electron microscopy (GCIB-SEM), developed by Kenneth Hayworth, a neuroscientist at Janelia Research Campus, works similarly but has a larger field of view, which makes it more feasible for use in imaging larger brains.<\/p>\n<p>GCIB-SEM might also be more compatible with multibeam electron microscopes, which researchers hope will speed up image acquisition. Numerous electron beams scan a sample at the same time, which enables the microscope to capture hundreds of millions of pixels per second. Lichtman is using a machine produced by Carl Zeiss that has 61 beams, and Denk has one with 91 beams. And electron microscopes with hundreds of beams are on the way, which might eventually capture a gigapixel of imaging data every second.<\/p>\n<h2><\/h2>\n<p><strong>Make it meaningful<\/strong><\/p>\n<p>But speed creates its own problems. Now that nanoscale connectome projects are rapidly producing data, another challenge is looming: how to make sense of it all. \u201cWe have so much processed data at our fingertips,\u201d Reid says. \u201cA large number of scientists could routinely discover new things on this data set. Many more than we could possibly hire.\u201d<\/p>\n<p>There is also the issue of linking nanoscale-connectome data with that produced by other large-scale neuroscience projects such as the Human Connectome Project. That effort used magnetic resonance imaging to scan the brains of about 1,200 people to define millimetre-wide tracts of nerve fibres that connect regions of the brain. The result was a map known as the macroconnectome.<\/p>\n<p>\u201cThe biggest problem in neuroscience is the problem of scale,\u201d says David Edwards, a neonatologist at Kings College London. He is part of the Developing Human Connectome Project, which is wrapping up its effort to scan the brains of hundreds of fetuses in the womb, as well as those of both full-term and premature babies. \u201cThere are great things being done at the macroscale, great things being done at the microscale, great things being done at population level,\u201d Edwards says. \u201cBut there are very few ways of linking those together.\u201d<\/p>\n<p>&nbsp;<\/p>\n<aside class=\"recommended pull pull--left sans-serif\" data-label=\"Related\"><a href=\"https:\/\/www.nature.com\/nature\/collections?type=outlook\" data-track=\"click\" data-track-label=\"recommended article\"><img decoding=\"async\" class=\"recommended__image\" src=\"https:\/\/media.nature.com\/w400\/magazine-assets\/d41586-019-02208-0\/d41586-019-02208-0_16963878.jpg\" \/><\/a><\/p>\n<p class=\"recommended__title serif\">More from Nature Outlooks<\/p>\n<\/aside>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>Fresh sources of data that are, in some ways, even more detailed than the nanoscale connectome, are also emerging. For example, the connectome only provides information about the location of synapses, not their molecular composition. \u201cI see that as a gap that needs to be bridged,\u201d says Seth Grant, a molecular neuroscientist at the University of Edinburgh, UK. \u201cIf you can\u2019t bridge it, you don\u2019t find your way to the genome.\u201d And those genomic insights, Grant suggests, will be essential for working out how evolution and genetics govern brain function.<\/p>\n<p>Enter the synaptome. In a 2018 paper, Grant and his team catalogued one billion synapses across the whole mouse brain<sup><a href=\"https:\/\/www.nature.com\/articles\/d41586-019-02208-0?utm_source=feedburner&amp;utm_medium=feed&amp;utm_campaign=Feed%3A+nature%2Frss%2Fcurrent+%28Nature+-+Issue%29#ref-CR5\" data-track=\"click\" data-action=\"anchor-link\" data-track-label=\"go to reference\" data-track-category=\"references\">5<\/a><\/sup>, which enabled them to define 37 subtypes on the basis of protein content, size and shape, and to identify patterns of subtypes that characterize various brain regions. The team has also begun to match the subtypes with the connections that they make. \u201cMarrying up the synaptome with the connectome,\u201d Grant says, \u201cis going to be one of the next frontiers.\u201d<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<\/div>\n<p><span class=\"emphasis\">Nature<\/span>\u00a0<strong>571<\/strong>, S6-S8 (2019)<\/p>\n<p>&nbsp;<\/p>\n<div class=\"emphasis\">doi: 10.1038\/d41586-019-02208-0<\/div>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<p>(\uc6d0\ubb38: <a href=\"https:\/\/www.nature.com\/articles\/d41586-019-02208-0?utm_source=feedburner&amp;utm_medium=feed&amp;utm_campaign=Feed%3A+nature%2Frss%2Fcurrent+%28Nature+-+Issue%29\">\uc5ec\uae30<\/a>\ub97c \ud074\ub9ad\ud558\uc138\uc694~)<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>&nbsp; &nbsp; As efforts to chart the brain\u2019s neurons gather pace, researchers must find a way to make the accumulating masses of data useful. &nbsp;<a href=\"https:\/\/biochemistry.khu.ac.kr\/lab\/?p=3935\" class=\"more-link\">(more&#8230;)<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[33,29,30],"tags":[],"class_list":["post-3935","post","type-post","status-publish","format-standard","hentry","category-do-biology","category-lets-do-science","category-recent-science-news"],"aioseo_notices":[],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack-related-posts":[{"id":1827,"url":"https:\/\/biochemistry.khu.ac.kr\/lab\/?p=1827","url_meta":{"origin":3935,"position":0},"title":"A new way to capture the brain\u2019s electrical symphony","author":"biochemistry","date":"September 23, 2018","format":false,"excerpt":"\u00a0 \u00a0 (\uc6d0\ubb38) \u00a0 \u00a0 How voltage readings from individual neurons could power the next revolution in neuroscience. \u00a0 Illustration by Joanna Gebal \u00a0 \u00a0 Biophysicist Adam Cohen was strolling around San Francisco, California, in 2010, when a telephone call caught him by surprise. \u201cWe have a signal,\u201d said the\u2026","rel":"","context":"In &quot;Let's Do Biology!&quot;","block_context":{"text":"Let's Do Biology!","link":"https:\/\/biochemistry.khu.ac.kr\/lab\/?cat=33"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":2584,"url":"https:\/\/biochemistry.khu.ac.kr\/lab\/?p=2584","url_meta":{"origin":3935,"position":1},"title":"Pioneering brain study reveals \u2018software\u2019 differences between humans and monkeys","author":"biochemistry","date":"January 29, 2019","format":false,"excerpt":"\u00a0 \u00a0 Neuroscientists tracked the activity of single neurons deep in the brain and suggest the findings could explain humans\u2019 intelligence \u2014 and susceptibility to psychiatric disorders. \u00a0 People with epilepsy undergoing certain treatments often also participate in neuroscience studies.Credit: BSIP\/UIG via Getty \u00a0 \u00a0 Neuroscientists have for the first\u2026","rel":"","context":"In &quot;Let's Do Biology!&quot;","block_context":{"text":"Let's Do Biology!","link":"https:\/\/biochemistry.khu.ac.kr\/lab\/?cat=33"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":4788,"url":"https:\/\/biochemistry.khu.ac.kr\/lab\/?p=4788","url_meta":{"origin":3935,"position":2},"title":"Next-generation artificial vision comes into view","author":"biochemistry","date":"November 8, 2019","format":false,"excerpt":"\u00a0 \u00a0 A grid of photodiodes as wide as a sesame seed rests in the eye of a person with macular degeneration. PHOTO: PIXIUM VISION SA\/PARIS \u00a0 \u00a0 In 2014, U.S. regulators approved a futuristic treatment for blindness. The device, called Argus II, sends signals from a glasses-mounted camera to\u2026","rel":"","context":"In &quot;'06. \uc5d0\ub108\uc9c0\uc640 \uc5d4\ud2b8\ub85c\ud53c'\uc640 '07. \uacfc\ud559\uacfc \ubb38\uba85' \uad00\ub828&quot;","block_context":{"text":"'06. \uc5d0\ub108\uc9c0\uc640 \uc5d4\ud2b8\ub85c\ud53c'\uc640 '07. \uacfc\ud559\uacfc \ubb38\uba85' \uad00\ub828","link":"https:\/\/biochemistry.khu.ac.kr\/lab\/?cat=42"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":4122,"url":"https:\/\/biochemistry.khu.ac.kr\/lab\/?p=4122","url_meta":{"origin":3935,"position":3},"title":"Countering opioid side effects","author":"biochemistry","date":"September 23, 2019","format":false,"excerpt":"\u00a0 \u00a0 The toll from opioid overdose in the United States now exceeds 45,000 deaths per year. Shockingly, more Americans die from opioid overdose than from motor vehicle collisions (1), and opioid overdose has become the number one cause of accidental death. Worldwide, two-thirds of drug-related deaths were a result\u2026","rel":"","context":"In &quot;Let's Do Biology!&quot;","block_context":{"text":"Let's Do Biology!","link":"https:\/\/biochemistry.khu.ac.kr\/lab\/?cat=33"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":3001,"url":"https:\/\/biochemistry.khu.ac.kr\/lab\/?p=3001","url_meta":{"origin":3935,"position":4},"title":"Neural representations across species","author":"biochemistry","date":"March 29, 2019","format":false,"excerpt":"\u00a0 \u00a0 A plethora of studies in rodents have described spatially tuned neurons, including place cells in the hippocampus and grid cells in the medial entorhinal cortex (MEC), suggesting a crucial role of the hippocampal formation in spatial navigation (1). Human studies have, in turn, shown that the hippocampal formation\u2026","rel":"","context":"In &quot;Let's Do Biology!&quot;","block_context":{"text":"Let's Do Biology!","link":"https:\/\/biochemistry.khu.ac.kr\/lab\/?cat=33"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":3939,"url":"https:\/\/biochemistry.khu.ac.kr\/lab\/?p=3939","url_meta":{"origin":3935,"position":5},"title":"The forgotten part of memory","author":"biochemistry","date":"July 27, 2019","format":false,"excerpt":"\u00a0 \u00a0 Long thought to be a glitch of memory, researchers are coming to realize that the ability to forget is crucial to how the brain works. \u00a0 \u00a0 Credit: Sam Falconer \u00a0 \u00a0 Memories make us who we are. They shape our understanding of the world and help us\u2026","rel":"","context":"In &quot;Let's Do Biology!&quot;","block_context":{"text":"Let's Do Biology!","link":"https:\/\/biochemistry.khu.ac.kr\/lab\/?cat=33"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"jetpack_sharing_enabled":false,"jetpack_shortlink":"https:\/\/wp.me\/p9Xo1j-11t","_links":{"self":[{"href":"https:\/\/biochemistry.khu.ac.kr\/lab\/index.php?rest_route=\/wp\/v2\/posts\/3935","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/biochemistry.khu.ac.kr\/lab\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/biochemistry.khu.ac.kr\/lab\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/biochemistry.khu.ac.kr\/lab\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/biochemistry.khu.ac.kr\/lab\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3935"}],"version-history":[{"count":1,"href":"https:\/\/biochemistry.khu.ac.kr\/lab\/index.php?rest_route=\/wp\/v2\/posts\/3935\/revisions"}],"predecessor-version":[{"id":3936,"href":"https:\/\/biochemistry.khu.ac.kr\/lab\/index.php?rest_route=\/wp\/v2\/posts\/3935\/revisions\/3936"}],"wp:attachment":[{"href":"https:\/\/biochemistry.khu.ac.kr\/lab\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3935"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/biochemistry.khu.ac.kr\/lab\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3935"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/biochemistry.khu.ac.kr\/lab\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3935"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}