Cooperative population coding facilitates efficient sound source separability by adaptation to spatial statistics

Abstract

Our sensory environment changes constantly. Accordingly, neural systems continually adapt to the concurrent stimulus statistics to remain sensitive over a wide range of conditions. Such dynamic range adaptation (DRA) is assumed to increase both the effectiveness of the neuronal code and perceptual sensitivity. However, direct demonstrations of DRA-based efficient neuronal processing that also produces perceptional benefits are lacking. Here we investigated the impact of DRA on spatial coding in the rodent brain and the perception of human listeners. Naturalistic spatial stimulation with dynamically changing source locations elicited prominent DRA already on the initial spatial processing stage, the Lateral Superior Olive (LSO) of gerbils of either sex. Surprisingly, on the level of individual neurons, DRA diminished spatial tuning due to large response variability across trials. However, when considering single-trial population averages of multiple neurons, DRA enhanced the coding efficiency specifically for the concurrently most probable source locations. Intrinsic LSO population imaging of energy consumption combined with pharmacology revealed that a slow-acting LSO gain control mechanism distributes activity across a group of neurons during DRA, thereby enhancing population coding efficiency. Strikingly, such "efficient cooperative coding" also improved neuronal source separability specifically for the locations that were most likely to occur. These location-specific enhancements in neuronal coding were paralleled by human listeners exhibiting a selective improvement in spatial resolution. We conclude that, contrary to canonical models of sensory encoding, the primary motive of early spatial processing is efficiency optimization of neural populations for enhanced source separability in the concurrent environment. Author summaryThe renowned efficient coding hypothesis suggests that neural systems adapt their processing to the statistics of the environment to maximize information while minimizing the underlying energetic costs. It is further assumed that such neuronal adaptations also confer perceptual advantages. Yet direct demonstrations of adaptive mechanisms or strategies that result both in increased neuronal coding efficiency and perceptual benefits are lacking. Here we show that an auditory spatial processing circuit exploits slow-acting gain control to distribute activity across the neuronal population, thereby enhancing coding efficiency based on single-trial population averages. This population-efficiency maximization also results in improved neuronal spatial resolution for the concurrently most probable source locations, which was resembled in a focally improved spatial acuity of human listeners.