{"id":180740,"date":"2017-01-17T20:50:00","date_gmt":"2017-01-18T01:50:00","guid":{"rendered":"https:\/\/www.panix.com\/~msaroff\/40years\/2017\/01\/17\/still-a-few-bugs-in-the-system\/"},"modified":"2017-01-17T20:50:00","modified_gmt":"2017-01-18T01:50:00","slug":"still-a-few-bugs-in-the-system","status":"publish","type":"post","link":"https:\/\/www.panix.com\/~msaroff\/40years\/2017\/01\/17\/still-a-few-bugs-in-the-system\/","title":{"rendered":"Still a Few Bugs in the System"},"content":{"rendered":"<p>Some neuroscientists decided to see if the latest neuroscience tools could handle a simpler case than the human brain.<\/p>\n<p>They chose a 40+ year old CPU, and <a href=\"http:\/\/arstechnica.com\/science\/2017\/01\/can-modern-neuroscience-understand-donkey-kong\/\">they failed abysmally<\/a>:<\/p>\n<blockquote><p><span style=\"color: blue;\">In 2014, the US announced a new <a href=\"https:\/\/directorsblog.nih.gov\/2014\/09\/30\/brain-launching-americas-next-moonshot\/\">effort to understand the brain<\/a>.  Soon, we would map every single connection within the brain, track the  activity of individual neurons, and start to piece together some of the  fundamental units of biological cognition. The program was named BRAIN  (for Brain Research through Advancing Innovative Neurotechnologies), and  it posited that we were on the verge of these breakthroughs because  both imaging and analysis hardware were finally powerful enough to  produce the necessary data, and we had the software and processing power  to make sense of it.<\/span><br \/><span style=\"color: blue;\"><br \/><\/span><span style=\"color: blue;\">But this week, <i>PLoS Computational Biology<\/i> published a  cautionary note that suggests we may be getting ahead of ourselves. Part  experiment, part polemic, a computer scientist got together with a  biologist to apply the latest neurobiology approaches to a system we  understand far more completely than the brain: a processor booting up  the games <i>Donkey Kong<\/i> and <i>Space Invaders<\/i>. The results  were about as awkward as you might expect, and they helped the  researchers make their larger point: we may not understand the brain  well enough to understand the brain.<\/span><br \/><span style=\"color: blue;\"><br \/><\/span><span style=\"color: blue;\">On the surface, this may sound a bit ludicrous. But it gets at  something fundamental to the nature of science. Science works on the  basis of having models that can be used to make predictions. You can  test those models and use the results to refine them. And you have to  understand a system on at least some level to build those models in the  first place.<\/span><\/p>\n<p><span style=\"color: blue;\">&nbsp;\u2026\u2026\u2026<\/span><\/p>\n<p><span style=\"color: blue;\">That&#8217;s where <em>Donkey Kong<\/em> comes in.<\/span><\/p>\n<p><span style=\"color: blue;\"><\/span><span style=\"color: blue;\">Games on early Atari systems were powered by the 6502 processor, also  found in the Apple I and Commodore 64. The two authors of the new paper  (Eric Jonas and Konrad Paul Kording) decided to take this relatively  simple processor and apply current neuroscience techniques to it,  tracking its activity while loading these games. The 6502 is a good  example because we can understand everything about the processor and use  that to see how well the results match up. And, as they put it, &#8220;most  scientists have at least behavioral-level experience with these  classical video game systems.&#8221;<\/span><\/p>\n<p><span style=\"color: blue;\"><\/span><span style=\"color: blue;\">So they built upon the work of the <a href=\"http:\/\/www.visual6502.org\/\">Visual 6502 project<\/a>,  which got ahold of a batch of 6502s, decapped them, and imaged the  circuitry within. This allowed the project to build an exact software  simulator with which they could use to test neuroscience techniques. But  it also enabled the researchers to perform&nbsp;a test of the field of  &#8220;connectomics,&#8221; which tries to understand the brain by mapping all the  connections of the cells within it.<\/span><\/p>\n<p><span style=\"color: blue;\">To an extent, the fact that their simulator worked is a validation of  the approach. But, at the same time, the chip is incredibly simple:  there is only one type of transistor, as opposed to the countless number  of specialized cells in the brain. And the algorithms used to analyze  the connections only got the team so far; lots of human intervention was  required as well. &#8220;Even with the whole-brain connectome,&#8221; Jonas and  Kording conclude, &#8220;extracting hierarchical organization and  understanding the nature of the underlying computation is incredibly  difficult.&#8221;<\/span> <\/p><\/blockquote>\n<p>Remember, in a microprocessor, a transistor is a transistor is a transistor, in the brain, neurons and ganglia vary from cell to cell.<\/p>\n<p>This is a valid test of the software, the 6502 is arguably the most thoroughly understood CPU in existence, and <i>Donkey Kong<\/i> is arguably one of the best understood pieces of software in existence.<\/p>\n<p>And they still could not do it on a&nbsp; processor that can access only 64K of RAM.<\/p>\n<p>We are much further from mapping the brain in any detail than is implied in the mainstream media reports.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Some neuroscientists decided to see if the latest neuroscience tools could handle a simpler case than the human brain. They chose a 40+ year old CPU, and they failed abysmally: In 2014, the US announced a new effort to understand the brain. Soon, we would map every single connection within the brain, track the activity &hellip;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[769,767,768,481,533],"class_list":["post-180740","post","type-post","status-publish","format-standard","hentry","tag-biology","tag-computer","tag-fail","tag-intelligence","tag-software"],"_links":{"self":[{"href":"https:\/\/www.panix.com\/~msaroff\/40years\/wp-json\/wp\/v2\/posts\/180740"}],"collection":[{"href":"https:\/\/www.panix.com\/~msaroff\/40years\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.panix.com\/~msaroff\/40years\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.panix.com\/~msaroff\/40years\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.panix.com\/~msaroff\/40years\/wp-json\/wp\/v2\/comments?post=180740"}],"version-history":[{"count":0,"href":"https:\/\/www.panix.com\/~msaroff\/40years\/wp-json\/wp\/v2\/posts\/180740\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.panix.com\/~msaroff\/40years\/wp-json\/wp\/v2\/media?parent=180740"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.panix.com\/~msaroff\/40years\/wp-json\/wp\/v2\/categories?post=180740"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.panix.com\/~msaroff\/40years\/wp-json\/wp\/v2\/tags?post=180740"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}