{"id":112043,"date":"2020-08-28T16:33:52","date_gmt":"2020-08-28T23:33:52","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2020\/08\/people-power-increase-processing-speed"},"modified":"2020-08-28T16:33:52","modified_gmt":"2020-08-28T23:33:52","slug":"people-power-increase-processing-speed","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2020\/08\/people-power-increase-processing-speed","title":{"rendered":"People Power Increase Processing Speed"},"content":{"rendered":"<p><\/p>\n<p><iframe style=\"display: block; margin: 0 auto; width: 100%; aspect-ratio: 4\/3; object-fit: contain;\" src=\"https:\/\/www.youtube.com\/embed\/6zXVjGxyd_E?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; encrypted-media; gyroscope;\n   picture-in-picture\" allowfullscreen><\/iframe><\/p>\n<p><b>Big initiatives to understand the workings of the brain<\/b><\/p>\n<p>Neuroscience has a data problem. In our efforts to understand the brain researchers are generating ever greater amounts of data. The problem is, how can they gain meaning from it?<\/p>\n<p>A <a href=\"https:\/\/www.nature.com\/nature\/journal\/v536\/n7615\/full\/nature18933.html#ref-link-61\">recent study<\/a>, that used functional magnetic resonance imaging (fMRI) data to produce the <a href=\"http:\/\/humanconnectome.org\/study\/hcp-young-adult\/article\/nature-article-cortical-brain-maps-at-the-highest-resolution-to-date\">most detailed map to date of the human cortex<\/a>, looked at data from 210 peoples\u2019 brains. The researchers estimated that equated to 30 gigabytes of data per participant. Meaning over 6 terabytes of data were analyzed to form the map, and this was a study of a large section of cortex, not the whole brain.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Big initiatives to understand the workings of the brain Neuroscience has a data problem. In our efforts to understand the brain researchers are generating ever greater amounts of data. The problem is, how can they gain meaning from it? A recent study, that used functional magnetic resonance imaging (fMRI) data to produce the most detailed [\u2026]<\/p>\n","protected":false},"author":367,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1523,47],"tags":[],"class_list":["post-112043","post","type-post","status-publish","format-standard","hentry","category-computing","category-neuroscience"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/112043","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/367"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=112043"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/112043\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=112043"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=112043"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=112043"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}