Topic: efficient coding theory

Biological systems must selectively encode partial information about the environment, as dictated by the capacity constraints at work in all living organisms. For example, we cannot see every feature of the light field that reaches our eyes; temporal resolution is limited by transmission noise and delays, and spatial resolution is limited by the finite number of photoreceptors and output cells in the retina. Classical efficient coding theory describes how sensory systems can maximize information transmission given such capacity constraints, but it treats all input features equally. Not all inp

Sensory neurons in different species, brain areas, and modalities adjust their sensitivity (gain) in response to recent stimulus history. This gain control offers a mechanism for single neurons to rapidly and reversibly adapt to different stimulus contexts while preserving synaptic weights that serve to represent features that remain consistent across contexts. From a normative perspective, this allows an individual neuron to adjust the dynamic range of its responses to accommodate changes in input statistics -- a core tenet of Barlow's efficient coding theory. However, experimental measureme