The McCulloch-Pitts neuron is a simplified model of a biological neuron, created by Warren McCulloch and Walter Pitts in 1943. It operates as a binary unit, receiving multiple inputs and producing a single output. Each input is assigned a weight, and if the sum of these weighted inputs exceeds a certain threshold, the neuron activates and outputs a signal, typically represented as a "1." If the threshold is not met, the output is "0." This model laid the groundwork for artificial neural networks and is fundamental in understanding how neurons process information. Although it is a basic representation, the McCulloch-Pitts neuron captures essential features of neural computation, influencing both neuroscience and computer science.