Let’s Build a Brain
The story introduces the concept of building a tiny creature, called a spark, with a very simple brain. This spark is designed to reach light, its primary goal in life. To sense its environment, a single neuron is given to the spark to detect brightness and convert it into electrical pulses. To move, another neuron is assigned to control a flipper's movement.
By connecting these two neurons, a basic neural circuit is formed, causing the spark to wiggle its flipper in proportion to the amount of light it perceives. If the spark faces the light, it is drawn towards it; otherwise, it moves away. The story highlights the limitations of this simple circuit, as the spark can only move in one direction, making it unable to steer towards the light.
The solution is to add two eyes to the spark, allowing it to sense whether the light is to its left or right, and then adjust its movements accordingly. However, this still leaves the spark charging towards the light without slowing down, leading to a false perception of it attacking the light. The root of this issue is the excitatory connection between the eye and flipper neurons, where more input leads to more output.
To resolve this, an inhibitory connection is introduced, where more input results in less output, causing the spark to slow down and gently come to a stop near the light. The article continues to demonstrate how changing the type of connections between neurons can lead to different behaviors, including steering towards and stopping at the light.
By varying the strength of these connections, each spark can have unique preferences for light, similar to how brains create individual preferences in humans. Despite being simplified models, these sparks exhibit behaviors that resemble intelligence, emphasizing how complex behaviors emerge from simple neural circuits. The story concludes by hinting at future articles that will explore the learning process in these brain models, showcasing how neural circuits can change and adapt over time.
Written by urgent.news from Lobsters's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.