The Evolution of Animal Intelligence: The Five Major Transitions

Monday - July 10 2023, 18:28 UTC - 1 year ago

This article outlines the five major transitions that have shaped the evolution of animal intelligence, from the simple neurological networks of jellyfish to the complex learning abilities of primates.

The animal world is full of different types of intelligence, from the simple bodily coordination of jellyfish to the navigation abilities of bees, the complex songs of birds, and the imaginative symbolic thought of humans.

In an article published this week in Proceedings of the Royal Society B, we argue the evolution of all these kinds of animal intelligence has been shaped by just five major changes in the computational capacity of brains.

Each change was a major transitional point in the history of life that changed what types of intelligence could evolve.

The Coordination Problem .

The first intelligence transition was the development of animals with a nervous system. Some have argued single-celled organisms show adaptive and complex behavior and forms of learning, but these are limited to life at tiny sizes. Multi-cellular bodies allowed animals to get big and exploit entirely new physical domains. However, a multi-cellular body needs to be coordinated to actively move as a single entity. A nervous system solves that coordination problem. The simplest nervous systems look something like the kind of diffuse neural networks we see in jellyfish. This is great for coordinating a body, but it is not so good at putting information together.

Growing a Brain .

The second transition was to a centralized nervous system. With this came a brain, and the capacity to combine information from different senses. A brain can be the master coordinator of the whole body, and this let new types of bodies evolve: bodies with specialized limbs and special sensory structures. We see these very simple brains in modern worms, leeches, and tardigrades. With these brains animals can integrate senses, learn from sensory input, and coordinate and orient their movements. Simple brains transform sensory input to motor output. We can think of the information flow as a "feed forward" from information to action.

A Feedback Loop .

The third transition was to more complex brains, specifically ones with feedback. When the output of a process is fed back into the process, we call it "recurrence." Insects have recurrent brains. The brilliance of bees—their ability to quickly learn different types of art, to recognize abstract concepts, and to navigate to goal locations—is all enabled by their recurrent brains.

Parallel Processing .

The fourth transition is to brains constructed from multiple recurrent systems, each in recurrent connection to each other. Here information flow iterates through recurrent systems. We see brains like this in birds, dogs, reptiles, and fish. This allows massive parallel processing of information. The same information can be used in multiple different ways at the same time, and relationships between different types of information can be recognized. These networks of recurrent systems are why birds are so good at learning complex sequences in songs; why birds, rats, and dogs are great at learning what, where, and when things happen; and why monkeys can learn new ways to manipulate objects to solve problems and make rudimentary tools.

The Brain That Modifies Itself .

The fifth transition was to brains that can modify their ow̅n structure both during development and over the course of a lifetime in response to experience. We see these brains in primates, but especially in humans. The ability to modify the structure of our brains in response to experience is what enables us to learn quickly and to build our knowledge, skills, and behavior out from the simple rules we initially learn.