One Step Closer To The Matrix: Automated Learning Technology
Everyone remembers the famous scene from The Matrix where Neo is plugged into a machine that downloads information into his brain. When it finishes downloading, Neo’s eyes open, and he mutters, “I know kung fu.” While students everywhere wish it was that easy to learn, the technology to do so may be closer to reality than you think.
A team made up of American scientists from Boston University and Japanese scientists from ATR Commutational Neuroscience Laboratories in Kyoto says they may have created a way to easily imprint learning onto the brain using functional magnetic resonance imaging, or fMRI; feedback to make a person’s visual cortex match a specific set of brain patterns. These brain patterns allow a person to do high-performance tasks, such as hitting a curve ball or playing the piano, with very little conscious effort. The researchers themselves have even alluded to the fact that this method resembles the learning methods from the Matrix movie series!
How Does Automated Learning Work?
Here’s how it works. The system uses a feedback mechanism to compare two sets of fMRI images against each other. One set is the subject’s current visual cortex; the other set consists of images of the target brain state, such as the visual cortex of an accomplished pianist. As the software works, the subjects sits in front of a computer screen. They are shown visual feedback of these two brain states, showing the similarities between the two states and how closely they match.
Research Kazuhisa Shibata says the team examines specific visual feature-based patterns in the target brain and uses what they call “decoded fMRI neuro-feedback” to induce those brain patterns in the subject. The team then tests for pattern repetitions to see if they caused improvement. Over and over again, they found improvement in the subject being “learned.” The subject’s brain began to pick up on the new patterns and incorporate them. The result is a brand-new learning approach that offers quick, long-lasting improvement for visual performance tasks.
Study lead author Takeo Watanabe says that early visual areas in the adult brain still retain plasticity, making visual perceptual learning like this possible. The study builds on previous research that confirmed the correlation between early visual area changes and improved visual performance, but it wasn’t until now that any studies directly addressed the question: Are early visual areas plastic enough that they could cause visual perceptual learning? It turns out the answer is yes.
Perhaps the most intriguing fact, Watanabe notes, is that this method worked even when subjects did not know what they were “learning.” When they tested this, the subject was not presented with any expectations of the feature to be learned, but the behavioral data still showed visual performance improvement after the neurofeedback training. The brain did its work without requiring a conscious effort on the subject’s behalf. The subject didn’t even have to pay attention to the visual feedback being shown for the brain to start making the necessary pattern adjustments.
Still a Long Way to Go
While it’s easy to theorize about ways this technology could be used in the future, the researchers are wary of over-hyping its potential. There are many tests still left to run to determine whether it works on other types of learning besides visual learning, and they want to make sure the method is never used in any way that might be considered unethical.
The team does acknowledge that there is no reason the neurofeedback method could not be used for memory, motor, and rehabilitation. The rehabilitative possibilities in particular are enormous. Should this method prove successful in that area, patients with impairments due to certain types of brain damage could potentially be able to regain some of their lost brain functions. That type of technology is still not something we have access to yet, but with studies like this happening, it could happen a lot sooner than we think.
Brandon Serna writes on topics related to education, technology, and entertainment. This article was written on behalf of Westwood College, which encourages (non-automated) learning by offering a wide variety of online degrees and career training programs.