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Transcript

The 5 Transitions of Cognitive Evolution

Transition 1

Transition 3

a recurrent nervous system. The output/the action command flows back into the system and becomes an input. This system is very developmental as it introduces the point where you can model your behavioural output before executing it. This enables things like reafferent motor control and enables you to maintain reverberating representations across time. This meaning you now have a temporal domain rather than simply a spatial domain. This is the system we find in insects.

Transition 5

Reflective: A system that learns how to tackle a particular problem, how to come up with solutions - for example humans, but not necessarily only humans - and has the ability to change its own control flow

Transition 2

Centralised nervous system-This is from a nervous system with no single point of control to one WITH centralised control… this would be where the brain later resides.-Much like the first transition, this is multicellular.-With the potential for specialised sensory systems, specialised limbs and specialised multimodal learning to direct behavioural output.- Examples of this are Nematodes and Tardigrade, leeches and flatworms.

Transition 4

“laminated” systems. This is similar to transition 3, however in this stage, there are multiple recurrent systems that all work in tangent with one another. The control flow is able to move in parallel to these recurrent systems within the process of motor learning. An example of a species with a laminated system is a simple, bony fish.

The first transition here outlines the shift from an organism having no nervous system at all, to one that is decentralised. This shift is usually observed when an organism evolves from one that is unicellular, to one that is multicellular Once an organism is multicellular, it becomes more difficult to co-ordinate its body. A decentralised nervous system is an effective way to mitigate this problem By transitioning to a decentralised nervous system, an organism acquires Environmental adaptation Local learning Local interactions between sensory systems and local muscle effectors

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