A transistor can’t grow into a computer but a cell can grow a brain, as all of us did, so building a processor isn’t the same as evolving one. Evolution found a path from a cell to a brain and embryo brains grow by following that path.
Even so, brains and computers have similarities, as both use electricity to power on/off units that process data, so brain neurons are logic gates that process data just as computer transistors do (McCulloch & Pitts, 1943). Sensorimotor channels also mirror computer input-output channels so brain-computer theories propose that nerves process the senses to give muscle output as computers process input and output (Churchland & Sejnowski, 1992). Yet the comparison ends there, because growing and building a processor are different challenges (Whitworth, 2008).
We build a computer at leisure then switch it on but an evolving brain must always run because life never stops. Our computers use the Von Neumann design of a central processing unit (CPU) with memory that processes input to give output (Figure 6.3) so it always knows what to do next but if the CPU fails, everything does. Biological parts fail regularly, so a system that fails if a part does won’t survive. Evolution had to find another way so brains don’t have a central processing unit.
To understand the brain, one must understand evolution. Darwin’s natural selection is that traits gradually change over time to select what survives (Figure 6.4). For a brain, this requires variability, change and survival:
1. Variability. Nerve autonomy, the ability to act by internal direction, lets brains vary. If nerves didn’t act by their own choice, the brain couldn’t evolve, so neural freedom allows evolution while absolute central control denies it, so the brain had to decentralize control.
2. Change. Evolution occurs in a step-wise manner so brains had to change in the same way. A brain can’t string neurons together in a series of steps that eventually give value as programmers do, because each step has to give value. The result is a nested hierarchy of processing, where each step adds value alone and leads to the next. It is layer upon layer, where each layer evolved while the previous one was still operating.
3. Survival. To survive, a brain must add body value, say by moving towards the light, but a sense like light detection is useless if it isn’t acted upon. To survive, a brain must control the feedback loop between sensory input and muscle output.
Decentralized control, nested hierarchies and feedback control, as the principles of brain evolution, explain it better than any computer analogy.