Definition
Neural Information Processing is the brain’s distributed activity by which perception, language, memory, and action are coordinated. It is the biological foundation for Artificial Neural Networks (ANNs), which seek to mimic the way neurons and synapses process information.
Why It Matters
Understanding how the brain processes information is the key to both biological medicine and artificial intelligence. If we ignore the ‘code’ of the brain, we remain limited to treating symptoms rather than causes in mental health and building ‘black box’ AIs we don’t understand.
Core Concepts
- Hebb’s Law: “Cells that fire together, wire together.” Learning occurs when the connection between two neurons (or computational nodes) is strengthened by simultaneous activation.
- The Perceptron (1957): The first artificial neural network, created by Frank Rosenblatt. It used a “neuronal network” to see and learn simple visual patterns, proving that intelligence could arise from a “bottom-up” simulation of the brain.
- Active Predictive Systems: Brains are not passive recording devices; they are active prediction engines that use dynamic patterns across neural networks to model reality.
- Distributed Representation: A thought or memory is not in a single neuron; it is a temporally extended pattern of coordinated activity across millions of nodes.