Models of neural computation

Models of neural computation refer to theoretical frameworks and mathematical representations used to understand how neural systems, particularly in the brain, process information. These models encompass various approaches and techniques that aim to explain the mechanisms of information representation, transmission, processing, and learning in biological and artificial neural networks. Here are some key aspects of models of neural computation: 1. **Neuroscientific Models**: These models draw from experimental data to simulate and describe the functioning of biological neurons and neural circuits.