Before human intelligence (AI) can really become a reality, we have to understand a lot more about how the brain works than we currently do. Intellect is defined by how various parts of the brain interact with each other at different times. The frequency with which the different brain areas interact with each other determines how high a person’s IQ and creativity are.
In recent studies in China and at the University of Warwick human intelligence is being measured and defined for the first time ever. The brains of thousands of people around the world have been analyzed using resting-state MRI analysis. Professor Jianfeng Feng of the Department of Computer Science and lead author notes that the areas of the brain associated with learning and development show high levels of variability. This means they change their neural connections with other parts of the brain frequently over a matter of minutes or seconds. In contrast, small variability and adaptability is shown is shown in the visual, auditory, and sensory-motor areas – the areas not associated with intelligence.
The results of the study could be applied to the construction of advanced artificial neural networks in computers, which should give them the ability to learn, grow and adapt. Feng feels that this adaptability and variability is vital in AI development. Designs of current systems does not include these characteristics.
Mental health, currently a misunderstood field, could also benefit from the results of Feng’s study. When observing brain patterns in schizophrenia, autism and Attention Deficit Hyperactivity Disorder (ADHD) patients, the brain’s default network shown altered patterns of variability. Once scientists know the root cause of mental health defects, they would be that much closer to treating and preventing them in the future.
Feng ascribes his success to the newly developed advanced brain imaging techniques that were used during the study. Although human intelligence has been debated hotly for a long time, Feng feels his study has provided sufficient insights to resolve these questions and shape developments in artificial intelligence, while at the same time establish the basis for understanding and diagnosis of mental disorders such as depression and schizophrenia.
The full study was published in the Brain journal.