The Evolution of Neural Learning & Future Prediction

The brain is the apex of all thought in the human body. Courtesy of neuroscience and brain imaging, we could soon stumble upon the ability to predict future behavior

The mind is arguably the most fascinating human organ. It is common knowledge that the human brain holds immense potential to perform herculean functions at dizzying speed. Mankind is constantly attempting to harness this potential by digging deeper into the vestiges of the brain.

Neural image mapping has helped harness this potential substantially. Noninvasive brain scans like the FMRI have paved the way for functions such as measuring brain activity and changes in blood flow. While it does solve a critical purpose, it has a limited impact in our day-to-day lives.  In short, neural image mapping is insignificant in the long run. Recent evidence suggests that the true potential of brain imaging lies in predictive behaviour. A scan of your brain could someday allow experts to predict future behavior, response patterns and subsequent response to stimuli. It could also help map abilities, traits, competencies, tendencies, attitudes and more, possibly years before the individual showcases them. If neuroscience is to be believed, we may not be far from the next big deal-breaker.

Predicting the implications of predictive behaviour is extraordinarily simple

The positive implications of predictive behaviour are astonishing. The diverse range of abilities we would possess through predictive future behaviour can be chalked down quite easily. On a macro-level, this ability would transform personalized education, improved learning, clinical practices, career competencies, psychotherapy and possibly even abate criminal tendencies. While all these are alluring possibilities, the most lucrative of them is the potential to transform the learning process in individuals.

The modern human learns new things through two key sources, outside information and personal experience. The mind’s tendency to absorb external information may not always be tuned to perfection. Consider this example; a student with a competency in math may not be adequately competent in science. It would take multiple setbacks attempting to learn science to come to this realization of a lack of competency. The personal experience of struggling with science would eventually prod the student to venture deeper into math instead. In the grand scheme of things, this method of learning is longer, and unfortunately is the conventionally followed method today. Moreover, existing behaviour testing falls short on accuracy far too often to be considered beneficial.

Neural learning could replace the hit-or-miss tendency of available behaviour testing methods. It will enable mankind to chip away at the unnecessary aspects of the potential life-long learning curve of an individual. We could unearth a human’s competencies, be able to map future behaviour, predicting future performance with this tool at our disposal. By identifying risk of failure and unlocking core competencies, neural learning simply creates a short cut in the learning curve. This it does by discovering an individual’s abilities and creating a straight road to a more logical and substantially more foolproof end result as opposed to a meandering obstacle course riddled with uncertainty. 

The new age of neural learning beckons

The possibility of being able to cater to each individual based on their learning patterns and potential future behaviour is astonishing. Neural learning and subsequently being able to predict human behaviour is something that would be too good to pass up on. It could help a student pick a career better suited to his or her ability. Teachers could reliably reach out to students with learning difficulties. The odds being in the wrong program of education and a mismatched career could be reduced to an insignificant number. If we put our minds to work, we could well and truly be en-route to harnessing the true power of the mind in the near future. It doesn’t take a neuroscientist to predict neural learning might just be the answer we’re looking for.

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