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Adult Brains More Flexible Than Previously Thought
stemceller passed us a link to the official site for Johns Hopkins, which is reporting on some research into cognition. Generally, doctors have understood our best learning to be done at a young age, when the brain has a 'robust flexibility'. As we get older, our brain cells become 'hard-wired' along certain paths and don't move much - if at all. Or, at least, that was the understanding. Research headed by the hospital's Dr. Linden has taken advantage of 'two-photon microscopy', a new technique, to get a new picture inside a mouse's head. "They examined neurons that extend fibers (called axons) to send signals to a brain region called the cerebellum, which helps coordinate movements and sensory information. Like a growing tree, these axons have a primary trunk that runs upward and several smaller branches that sprout out to the sides. But while the main trunk was firmly connected to other target neurons in the cerebellum, stationary as adult axons are generally thought to be, 'the side branches swayed like kite tails in the wind,' says Linden. Over the course of a few hours, individual side branches would elongate, retract and morph in a highly dynamic fashion. These side branches also failed to make conventional connections, or synapses, with adjacent neurons. Furthermore, when a drug was given that produced strong electrical currents in the axons, the motion of the side branches stalled.'"
There's a branch of neural net studies that focuses on a technique called entropic topography. Essentially, it involves random evolution of just the fringes of a digital neural net. That is, much as this John-Hopkins study has found, a rigid core is kept. It is only the neural subnets branching off that undergo synthesis and morphing.
While there are various deterministic algorithms that are used to evolve neural nets, it's only recently that we've begun seeing randomness used. This has an added benefit of bringing in unexpected mutations, which really don't happen with the deterministic algorithms.
Some advances from the study of Lei topographies have also lead to breakthroughs recently, where some of the more complex, yet deterministic, algorithms have had entropic terms introduced in order to bring in an element of randomness. These neural nets are probably the closest to the human brain, as they introduce the random mutation that is so prevalent within the human species, while also following the constraints of this new-found core neural path.
Here's another article on the same topic.
I's true. After reading the article I had my old dog learn new tricks.
I hate this view that some how results of tests on animals don't apply to humans at all. It's simply not true, almost every major medical advance has been tested or researched on animals like mice first. the simple fact is mammals bodies all work in very similar ways.
Having worked in a lab (disclaimer: not as a scientist) I learned that there are loads and loads of promising treatments for cancer and such that work great in mice, and never translate beyond. Even a casual glance at immunology from a layman's perspective reveals your statement to be utter bullshit; there are many, many diseases and afflictions that are species specific, sometimes highly so.
Anyway...it is entirely plausible that this ability to re-purpose brain cells is a plus for mice in survival/adaptation, where they have very little brain capacity at their disposal. We have loads at our disposal, and tend to build a lot of generally useful knowledge..ie, we build tools, literally or figuratively, and apply those 'real' tools or knowledge/skill 'tools'. Mice do not do either. We're more "general purpose", so maybe we don't *need* the ability to re-learn, since our learned skills are so broadly applicable in a survival sense.
Please help metamoderate.
Why is this article tagged with 'ronpaul' and 'ronpaulisanazi'? I thought this was slashdot, not digg. Why don't we just tag the article with 'omgiphonejailbreak' and '10waystoimproveyourwebsite' while we're at it?
Even a casual glance at immunology from a layman's perspective reveals your statement to be utter bullshit; there are many, many diseases and afflictions that are species specific, sometimes highly so.
He stated that it's "not true" that animal tests don't apply to humans at all (true), that almost every major medical advance has been tested or researched on animals like mice first (true, at least since the mid-twentieth century), and that mammal bodies work in very similar ways (true).
What you said is also true--that despite the huge similarities there are also significant differences--but that doesn't make his statement "bullshit"... perhaps merely "incomplete."
I support your point in general, especially because brains is obviously one of the organs in which humans differ the most, but I don't think that gives you the right to call a bunch of essentially truthful statements "bullshit."
Granted, most of this comes back to lack of effort, but in most cases, the decision to not put forth the effort is very understandable. It doesn't mean that adults can't learn. It just means they're too busy, have too many distractions and demands on their time, are happy with their current methods, or are simply too damn tired.
And this is also one reason why it may be good for a person to change job now and then to not grow stale in one environment. It may be good to not change too often but if the job stops to develop a person it will result in that the person having the job will get bound to the job and unable to accept changes or the person will change job.
It's important for people to take on challenges now and then - even if failing it's a learning experience. If failing all the time - it's just meaning that this person is attempting things that always are too hard or that that particular person hasn't the ability to know his/her own limits.
If builders built buildings the way programmers wrote programs, then the first woodpecker would destroy civilization.
Let me add: "reward systems."
If an adult speaks a second language poorly, people go, "Oh, what an idiot... Will you please just speak in your native tongue?!"
But if a child learning a language speak it poorly, people go, "Wow! You're learning so quickly! You're really doing a great job!" They'll smother the child with attention.
Kids also find other kids who are basically forced to learn to speak a language, and are learning at the same skill level, and so on.
I've always thought this - of course, I didn't have any scientific evidence, but my personal experience is I find learning easier now as an adult than I did as a child - the easier learning now because I have a more disciplined approach to learning and I'm much better able to stay the course. But the actual mechanism of learning something new, at least for me, doesn't appear to have faded at all. (In fact I enjoy it - my best days at work are when I'm doing something completely new and having to discover new things, and my hobbies all include learning new things).
That and the anecdotes of retired people learning new things with all the time they now have - such as a friend's father, who's a retired air force officer - doing a computer science degree in his 60s, and doing it as well as any college kid.
Oolite: Elite-like game. For Mac, Linux and Windows