Jeff Hawkins. An On-Line Biology Book. Guide to Getting Started in Machine Learning. Someone at work recently asked how he should go about studying machine learning on his own. So I’m putting together a little guide. This post will be a living document…I’ll keep adding to it, so please suggest additions and make comments. Fortunately, there’s a ton of great resources that are free and on the web. The very best way to get started that I can think of is to read chapter one of The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2009 edition). Once you’ve read the first chapter, download R. Once you’ve installed R, maybe played around a little, then check out this page which describes the major machine learning packages in R.
Oh, by the way, if you want to start playing around with machine learning in R, you’ll need data. I’d suggest next reading more of The Elements of Statistical Learning. If you’re looking for perhaps a more passive experience, or want the feel of a classrom, Andrew Ng of Stanford has posted all of his lectures online. To make memories, new neurons must erase older ones. Short-term memory may depend in a surprising way on the ability of newly formed neurons to erase older connections.
That's the conclusion of a report in the November 13th issue of the journal Cell, a Cell Press publication, that provides some of the first evidence in mice and rats that new neurons sprouted in the hippocampus cause the decay of short-term fear memories in that brain region, without an overall memory loss. The researchers led by Kaoru Inokuchi of The University of Toyama in Japan say the discovery shows a more important role than many would have anticipated for the erasure of memories.
They propose that the birth of new neurons promotes the gradual loss of memory traces from the hippocampus as those memories are transferred elsewhere in the brain for permanent storage. Although they examined this process only in the context of fear memory, Inokuchi says he "thinks all memories that are initially stored in the hippocampus are influenced by this process. " Blogs been dark lately, but I've been busy, busy. I've read a couple of "Intro" to neuroscience and psychology books, and what I've learned has fascinated and inspired my way more than anything I've learned about computers and electronics over the years.
The Brain is truly the more complex "computer" the work has ever seen! Here's a couple books I've read that I highly recommend: A User's Guide to the Brain: Attention, Preception, and the Four Theaters of the Brain by John Ratey Thinking in Pictures: My Life with Autism by Temple Grandin A couple other books I highly recommend that are related to this area; even if they are more Sociological: Cesar's Way: The Natural, Everyday Guide to Understanding and Correcting Common Dog Problems by Cesar Millan Be The Pack Leader: Use Cesar's Way to Transform Your Dog ... I've decided to start in the pursuit of a degree in Neuroscience; instead of Computer Science even though CS may be "easier" since I've been doing software programming/development/architecture for ~8+ years now. The Cloud and Collaboration. Paper written as a contribution to the Ars Electronica symposium on Cloud Intelligence. Let's take as a starting point the discussion of 'cloud intelligence' on the conference website: In the cloud of connections, we each become social neurons, mimicking the biological human brain but on a giant scale.
This collective knowledge is far beyond anything a single search engine could index and archive. Intelligence is spreading everywhere, every minute, and cloud computing can draw new links across new ideas. (80+1, 2008) This idea of the connected world as a global brain is not new, nor surprising. It seems clear that we can identify something like social intelligence in the community, and the analogy between humans and neurons is compelling. Peter Russell's The Global Brain explicitly makes the connection. We have already noted that there are, very approximately, the same number of nerve cells in a human brain as there are human minds on the planet. Tom Stonier writes, reciprocity is strong. Brain innately separates living and non-living objects for proce. For unknown reasons, the human brain distinctly separates the handling of images of living things from images of non-living things, processing each image type in a different area of the brain.
For years, many scientists have assumed the brain segregated visual information in this manner to optimize processing the images themselves, but new research shows that even in people who have been blind since birth the brain still separates the concepts of living and non-living objects. The research, published in today's issue of Neuron, implies that the brain categorizes objects based on the different types of subsequent consideration they demand—such as whether an object is edible, or is a landmark on the way home, or is a predator to run from. They are not categorized entirely by their appearance. "When we looked at the MRI scans, it was pretty clear that blind people and sighted people were dividing up living and non-living processing in the same way," says Mahon.
Story source. Neuroscience. Neuroscience is the scientific study of the nervous system.[1] Traditionally, neuroscience has been seen as a branch of biology. However, it is currently an interdisciplinary science that collaborates with other fields such as chemistry, computer science, engineering, linguistics, mathematics, medicine and allied disciplines, philosophy, physics, and psychology. It also exerts influence on other fields, such as neuroeducation[2] and neurolaw. The term neurobiology is usually used interchangeably with the term neuroscience, although the former refers specifically to the biology of the nervous system, whereas the latter refers to the entire science of the nervous system.
Because of the increasing number of scientists who study the nervous system, several prominent neuroscience organizations have been formed to provide a forum to all neuroscientists and educators. History[edit] The study of the nervous system dates back to ancient Egypt. Modern neuroscience[edit] Human nervous system.