Natural Sound Statistics in Auditory Scene Analysis

Picture yourself on a sunny weekend afternoon, sitting by the edge of a stream, waterrushing over a small weir, geese honking in the background, and a bumble bee buzzingpast. All of these sounds are a constant presence, but drift in and out of yourconsciousness only fleetingly, and none prevent you from enjoying a conversation withfriends. Afternoons like those enrich our lives, we accept them gratefully, and few of uswonder how it is possible that we can so effortlessly shift our attention from theconversation to the buzzing bee or the rushing water or the honking geese, given that allthese sounds arrive at our eardrum as an impenetrable mish-mash.So how does normal, healthy hearing take in these sounds all separately and yet all atonce? We believe that neurons in the brain may be sensitive to key, identifyingstatistical properties of the various sound sources, and that this will make them respondselectively to only those sound sources that match the statistics they are tuned to. Wealso believe that two of the most important statistical properties are "sparseness" and"correlation structure". The geese make occasional but relatively loud honks,interspersed with periods of silence. This we would describe as "sparse". Rushing watersound is less sparse because its intensity varies much less over time. If neurons prefersparse sounds, then these would respond strongly to the sound of geese but not thewater, and their responses would thus to an extent separate the sound of the geese fromthe rest of the auditory scene. To distinguish the gurgling water and the buzzing bee, butthose you could separate using "frequency correlations". Water sounds involve countlessbubbles gurgling. Large bubbles make deeper sounds, small bubbles make higher sounds,and high and low bubble sounds are not synchronized. In contrast, each wing beat of abumble bee is a "flap", in which many frequencies all go off together, perfectlycorrelated. Neurons which require high frequency correlation would hear mostly the bee,neurons requiring weak correlation hear mostly the water.We hypothesize that sensitivity to these key statistical properties emerges graduallyalong the ascending auditory pathway, and we propose to investigate neural responsesfrom key stages of the ascending pathway, including the inferior colliculus, primary andsecondary auditory cortex of rats to synthetic auditory texture sounds withsystematically varying statistics, presented in isolation and superposition.