Evolution

The human brain has evolved from earlier versions. At a macro level, many brain structures are identical and the materials comprising a brain are virtually identical. While it comes as no surprise that our brains share a common ancestry, more attention to our ancestral brain will continue to support our research.

Patomic theory is built on the knowledge that much earlier forms of life benefitted from pattern-matching and usage abilities. Simply detecting predators and initiating stored patterns to move away could protect very early creatures. Equally detecting prey and moving towards them offered similar survival benefits.

Survival long enough to reproduce using these simple capabilities requires no intelligence. It merely requires the correctly linked patterns to trigger the appropriate stored motion patterns.

To design a human brain from scratch is an enormously complex task. To modify a chimpanzee’s brain is considerably less complex, as genetically their DNA is 98% similar. This introduces the model of evolution, our best scientific model to explain biologically diversity and progress. It is worthwhile verifying that the proposed model is conceivable from the perspective of evolution.

Darwin’s theory of evolution indicates that sequences of successful mutations explain incremental biological progress. Evolutionary theory indicates that some kind of controlling mechanism must ensure that harmful actions are not undertaken in preference to beneficial actions for survival and reproduction. Our brain’s structure supports this view as numerous ancestral structures are visible (Carter, 1998), operating using ancient principles and intertwined with recent adaptations. Here, I analyse whether the principles used in primitive brains can be scaled up to explain more complex brains. If so, evolution is consistent with Patomic Theory and provides an explanation for the development towards our brain’s capabilities.

In vertebrates, a brain enables complex movement (Greenfield, 1996) by simultaneously controlling the actions of multiple muscles. Coordination between flexing and extending muscles leads to more efficient motion as bones are not pushed and pulled simultaneously. The evolution of vertebrates may have started with a simple collection of neurons connected to muscles. These neurons are assumed to have collectively performed two functions: (1) they stored instantaneous sets of muscle contractions (snapshot patterns) and (2) they stored sequences of these (sequential patterns or linksets). This assumption means that the neurons comprise a Patom.

This simple brain delivers a continuous sequential stream of snapshot patterns to create a motion such as swimming. Motion is flexible as the neurons store both pattern sequences and snapshots. Changes to either result in a motion change. The evolutionary success of this fictional animal is driven by a number of factors including, in particular, the sensory capability of its predators and prey.

Following the creation of this simple brain (Patom), a mutation could easily exploit it. While the addition of olfactory sensors to detect water-bourn chemicals (and the Patom’s storage as snapshot and sequential patterns) is not beneficial in isolation, connecting it to the original motion Patom provides useful new capabilities. Patterns found in one sense can be linked to the other. An example is turning left, a collection of tail and fin motions, in response to a left nostril detected odour. If an animal swims towards the smell of blood, it may increase its survival chances or the reverse. Put another way, if “smell A triggering motion B” enhances survival, this animal may increase its population. By linking olfaction with motion, avoidance actions from predators and attraction to prey results because natural selection removes ineffective choices from the gene pool.

The example above allows for the control of simple animals. But even the comparatively simple, modern brain found in fish has input elements like hearing, vision, touch, taste and smell; and output elements like muscle movement and digestion. These brains follow the evolutionary model in which sensors connect to brain sensory cells which then combine further. Whether a brain can scale further from the basic concept probably depends on its ability to handle the more complex human elements. In this case, brain anatomy, evolutionary similarity and human uniqueness are important considerations.

Brain anatomy

The human brain is similar to our ancestor’s brain. Carter (1998) and Greenfield (1997) compare the structures of our brains and those of our ancestors. From fish, to reptiles, to mammals, to humans – the brain strongly resembles our predecessor’s brains with extensions. For this reason, by focussing on the unique capabilities humans possess, we may be able to progress in robotic development through the emulation of some of our earlier ancestors as a first step, rather than first focussing on our brain’s unique capabilities that rely on these earlier elements.

Evolutionary similarity

Moving up the evolutionary tree from fish, despite a mammal’s emotions being complex, they appear to follow defined patterns. Dog behaviour includes numerous predictable patterns, for example (Coren, 1994) shows a number of canine motion behaviours or recognisable patterns. Similarly, from a motor and chemical perspective human emotions appear to be predefined, repeatable patterns. Greenfield (2000) describes the intricate, but repeatable, patterns taking place in our brain resulting from drug use and emotional reaction. The standard nature of these patterns is further exemplified by the commonality of human body language (Pease and Garner, 1985) and psychologist’s exploitation using tools like NLP as widely communicated by high-profile speakers like Robbins (1988). This commonality in pattern use between humans and other animals supports the pattern-matching paradigm, since pattern use accounts for complex chemical release, body motion and neural activation seen in animal’s emotions.