Neuroimaging provides evidence that human intelligence is tied to several structural and functional brain properties. The concept of “neural efficiency” plays a central role in understanding intellectual performance and capability.
So, what exactly is ‘neural efficiency’? Think of it this way: Consider a very complex computer with thousands of components and perhaps 1 million or more interconnections between them. We all have experienced the failure of our computers to carry out a command sometimes leading to an unexpected output or a complete freeze. Very complex systems such as those used by the military and NASA often have built-in systems so that if one part fails others come into play so that commands can be completed accurately. Our brain consists of between 80 and 100 billion neurons and perhaps anywhere from many trillion to almost a quadrillion connections. In addition to structural connectivity there is the functional connectivity and the direction of flow within circuits.
When one is trying to comprehend a very complex concept it requires screening out extraneous stimuli and the ability to focus on those aspects of the problem which can lead to a successful solution. This may require the interaction of specific networks such as the salience network and the dorsal, ventral, attention networks and other brain systems such as those associated with output – both skeletal motor, and autonomic. In a system as complex as the human brain perhaps there are failures in those portions of the circuits that are necessary to fully comprehend and make decisions based on many types of information that must be integrated. Perhaps for an individual with more limited intellectual capacity more of these “circuit failures” occur than for individuals with superior intellect.
We are only beginning to develop measures that might help us understand how these circuits operate. A recently posted paper “multimodal description of whole brain connectivity” by Pilar Graces et al. examines the interrelationship for structural connectivity and functional connectivity using diffusion weighted imaging, FMRI, MEG\EEG. This information, particularly when cast in a graph format where we can look at the relationship between nodes and their hubs and the vertices or links between them, may begin to give us some idea of how to measure “neural efficiency” in individuals with different intellectual capacities under different task conditions. This may be particularly useful in being able to understand special abilities such as superior mathematical ability, artistic ability, musical, or advanced writing skills.
It is predicted that within the next decade, especially considering that articles are appearing at the rate of more than one per day dealing with the complexity of brain organization, we may be able to really understand at a very detailed level the basis for different intellectual capabilities and perhaps with neurofeedback and/or stimulation techniques develop ways to enhance people with deficient intellectual capacity as well as those who are normal or even have superior capacities that they would like to enhance further.