Neural coding

Neural coding is the study of how neurons represent and transmit information through patterns of electrical and chemical activity. It asks: what does a spike mean? How do populations of cells encode sensory input, memory, decisions, or motor commands?

The field bridges neuroscience and information theory. A single neuron's firing rate, the precise timing of spikes, or the synchronized bursting of many cells can all carry meaning. Sensory systems convert light, sound, and touch into neural signals; Motor systems decode those signals into action. Understanding these mappings is foundational to neuroscience and inspires AI architectures.

Classic questions remain open: Is information encoded in the rate of firing, the timing between spikes, or population geometry? Do neurons use linear or nonlinear codes? How do recurrent circuits maintain and update information over time?

Neural coding connects to Connectomics, Electrophysiology, Brain-computer interfaces, and computational models. It's also inspired by and informs transformers and other deep learning systems that mimic neural information processing.

Related

Neuroscience, Spike train, Receptive field, Population coding, Information theory, Neuroplasticity