Visual sensitivity to correlation patterns in rats matches that previously measured in humans, as well as predictions from efficient coding theory based on the statistics of natural images.
Neural oscillations are a necessary consequence of efficient coding of sensory signals by a spiking neural network, limited by synaptic delays and noise.
Attractive and repulsive history biases in visual perception occur simultaneously, yet over dissociable timescales, and are explained by efficient encoding and Bayesian decoding of visual information in a stable environment.
An efficient coding theory for higher-level cognitive processes reveals that humans efficiently adapt to contextual distributions by economizing on environmental prior information.
Laura R Edmondson, Alejandro Jiménez Rodríguez, Hannes P Saal
A simple efficient coding model predicts complex trade-offs in resource allocation for sensory inputs with heterogeneous receptor densities and activation levels.
Perceptual haptic representation of materials emerges from unsupervised learning as a consequence of efficient encoding of the physical signals at the input of tactile sensory system.
Neural populations may depend on balanced recurrent connectivity to produce an efficient stimulus representation while also maintaining an accurate stimulus encoding despite the variability introduced by adapting neural responses.
To make reliable but metabolically efficient perceptual inferences in a changing world, neural systems should dynamically adapt based on surprise and uncertainty about the sensory environment.