Topic: Efficient coding hypothesis

The efficient coding hypothesis posits that sensory systems are adapted to the statistics of their inputs, capturing essential structure while minimizing the use of resources (neurons, spikes, etc). A variety of formulations have been developed and, differing primarily in their definition of efficiency. For example, Independent Components Analysis [Bell and Sejnowski, 1997] seeks a complete set of axes along which the data distribution is heavy-tailed. Sparse Coding [Olshausen and Field, 1996] learns a set of basis functions that can sparsely reconstruct natural image patches (

A major goal of sensory neuroscience is to understand the system's response to individual stimuli. Although mutual information (MI) continues to be a useful tool when applying Information theory to neural systems, it does not suffice when trying to understand how informative individual stimuli are. In general such knowledge may be crucial for understanding the functional organization of sensory systems. To investigate this, we focus on ON-OFF Direction Selective Retinal Ganglion Cells (dsRGC). These cells respond robustly to motion in their preferred direction, and sparsely to motion in the op

Recent research in awake, behaving organisms revealed the strong modulatory effects of movement on sensory coding. Surprisingly, these effects are not consistent across species. For example, in rodents and insects locomotion increases the magnitude of visual responses [1-3], while in primates, locomotion has a weak suppressive influence [4]. These differences raise intriguing questions about the computational purpose of such modulations and the generality of the underlying principles of sensory processing. Here, we address these questions from a theoretical perspective. Our approach is groun