Here is my problem with the article: It has the title of a magna opus. The article has a title that suggests content that is expansive and authoritative, containing both rigorous theory and seminal empirical research. This article is not at all deserving of such a title, and I cannot think of a single neuroscientist I know that would put such a title on even their most ambitious work, much less this loosely thought out treatment.<p>It is, frankly, embarrassing. Even in 2011.
Dave Touretzky's course <i>Computational Models of Neural Systems</i> should be checked out by anyone with the interest in the topic.<p>Lectures, assignments and matlab code are all available online: <a href="http://www.cs.cmu.edu/afs/cs/academic/class/15883-f15/" rel="nofollow">http://www.cs.cmu.edu/afs/cs/academic/class/15883-f15/</a><p>The readings page alone is a treasure trove of background text in computational neuroscience theory starting from 1970s.
In the 1900s, people used to think the mind (and body, in a way) worked like a steam engine. In part, the steam engine was used as the analogy because that was the nearest and most technologically advanced input/output closed system that was available. (And, importantly, that most people could grasp and talk about.)<p>Hence colloquialisms like I need to "let off steam" or "I am under so much pressure".<p>It turned out to be an analogy that was so far removed from reality, it was useless.<p>I wonder if we are making the same mistake with computers as we know them today?<p>"I really just need to reset and reboot, y'know."
The article says nothing about how brains are built, nor does it mention any principles of computational neuroscience.<p>The paper largely consists of smug statements such as:<p>> Despite huge efforts and large budgets,
we have no artificial systems that rival humans at recognizing faces, nor understanding natural languages, nor learning from experience<p>Progress in these areas is very rapid, I hope the author won't be too disappointed in the outcome.
I know it was published in 2011, but to extend the logic in this article:<p>To build a machine that can fly, we need to build a machine that can flap its wings.<p>To build a car that moves, we must build a machine that can lift its two feet in alternating motion.<p>To build a camera that sees, we need to build a lens that can flex itself to change focus.
We also have the mind, Computational Theory of the Mind (CTM) <a href="https://plato.stanford.edu/entries/computational-mind/" rel="nofollow">https://plato.stanford.edu/entries/computational-mind/</a>
The paper is not about computational neuroscience, but about the brain in general. For those interested, there is a great book actually titled "Principles of computational neuroscience"[1]. Also, the free "Book of Genesis"[2] has an excellent short introduction to computational neuroscience.<p>1. <a href="https://www.amazon.com/Principles-Computational-Modelling-Neuroscience-Sterratt/dp/0521877954" rel="nofollow">https://www.amazon.com/Principles-Computational-Modelling-Ne...</a><p>2. <a href="http://www.genesis-sim.org/iBoG/iBoGpdf/index.html" rel="nofollow">http://www.genesis-sim.org/iBoG/iBoGpdf/index.html</a>
It would be nice if the article's title mentioned its publishing date. I wrote a comment criticizing the article for ignoring a number of important papers published since 2010, the latest published article that was cited, and then had to delete it.
Hey guys, I found the non-crappy papers:<p><a href="https://arxiv.org/abs/1604.00289" rel="nofollow">https://arxiv.org/abs/1604.00289</a> -- <i>Building Machines that Learn and Think like People</i><p><a href="http://rsif.royalsocietypublishing.org/content/13/122/20160616" rel="nofollow">http://rsif.royalsocietypublishing.org/content/13/122/201606...</a> -- <i>Active Inference and Robot Control: a case-study</i>