Insights into CPU allocation in humans via compensatory plasticity

In young children, the loss of half the cerebral hemisphere results in significant activation of compensatory plasticity to enable to retention of as much brain function as possible while working with only half the number of neurons available.

Interestingly, these children are still able to grow up being fully able to walk despite losing half their brain. While most functions were able to be restored by neuronal plasticity, this is not true for the motor functions of the upper limb. We understand that the motor area for the hand takes up a significant region of the primary motor cortex. We believe large area is required to enable the fine motor movements and manual dexterity conferred by the hands and not any other part of the human body. It therefore seems that when humans lose half of the brain, the brain has chosen to sacrifice fine motor movements in favour of enable more other motor functions to be regained.

This sparks questions about the optimization algorithm used in compensatory plasticity. How does the human brain decide on what functions to keep and what functions to let go? In computers, when we run out of CPU, there are mechanisms to optimize the machine, to shut down certain functions and retain the more important ones as a measure to keep the computer running in a resource constrained environment. However, these decisions on shutting down processes and retaining process were determined using deliberate human decisions. But how does the brain make these decisions? Are there mechanistic pathways in which the brain knows the sacrifices to make to optimize for survival?

Intuitively, we may think that the brain removes functions that are space inefficient. In this case, the hands are small muscular structures when compared to the rest of the body, however, they take up disproportionately large amounts of space in the motor cortex. One way to look at this is the space ratio between area of musculature being innervated and area of brain allocated to that area of musculature. Perhaps our brain first removes functions that has a very low space ratios hence indicating functional space inefficiency.

Moving forward, it would be interesting to investigate in more detail of optimization algorithms used in computers and draw comparisons to observations seen in the human brain. How the human brain determines what functions are crucial for ‘survival’ is interesting to explore. This is especially because the functions of ‘survival’ is different depending on the environmental context the individual is in and therefore the brain might have a way to adapt to it. Perhaps it increases retention from strong synpatic connections and removes the weaker synpatic connections and uses those neurons to form strong synpatic connections for new functions? In other words, in severe compensatory plasticity, there average strength of synpatic connections might increase?