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.'"

Comments

Similar to neural net entropic topography.

[Anonymous Coward]

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.

Re:Not true

[nospam007]

I's true. After reading the article I had my old dog learn new tricks.

Re:Scary combination

[Belial6]

I agree. The other thing that people forget is that children often have access to vastly superior resources. Take for example the classic example of children learning languages easier than adults. When people point that out, they generally fail to notice that children tend to learn their language via total immersion and virtually everyone around them is happy to be a 24/7 personal tutor on the language. While most children can get by in their first language by 2 or 3 years only, they tend not to be what we would call fluent until 5 or 6. Give me a couple of full time language tutors and 5 years of total immersion with no need to remember my native tongue, and I will learn the new language too.

Re:Adults can learn...

[CrazedWalrus]

I think you're right. I think adults tend to be reluctant to learn new things for a few reasons:

• Fatigue. Most adults are overworked, and many tend to avoid taking on any extra effort beyond what's required to get to the next day. Gratuitous learning of a foreign subject matter tends to be difficult, so is about the last thing they want to do when they get home from a hard day at work.
• Divided attention, or excessive multitasking. Again, a matter of not enough cycles to go around. I find that it's a sheer joy to me if I can spend an hour or two and really concentrate on something. Usually I can't do so without interruption or another obligation getting in the way.
• Information layering. By the time people are adults, they've built a stack of information that suits them well. The last thing they want to do is start over from the bottom. To use an analogy: Each successive level of math builds on the principles established in previous levels. By the time you're a Physicist using Calculus, why in the hell would you want to go back and learn a new way to add numbers when the one you know works just fine?
• 
  
  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.

Re:Not true

[Z00L00K]

Actual truth is that as an adult you become more habit-bound than as a kid, but that doesn't stop you from learning new things. As a kid you are all over testing boundaries but as an adult you skip that part and strive forward in the direction you found were the most ideal when you were a kid. What's ideal for one person may not be for another and depending on the environment and the stimulus received as a kid you get preferences.

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.