title: Stable encoding of sounds over a broad range of statistical parameters in the auditory cortex.
abstract: Natural auditory scenes possess highly structured statistical regularities, which are dictated by the physics of sound production in nature, such as scale-invariance. We recently identified that natural water sounds exhibit a particular type of scale invariance, in which the temporal modulation within spectral bands scales with the centre frequency of the band. Here, we tested how neurons in the mammalian primary auditory cortex encode sounds that exhibit this property, but differ in their statistical parameters. The stimuli varied in spectro-temporal density and cyclo-temporal statistics over several orders of magnitude, corresponding to a range of water-like percepts, from pattering of rain to a slow stream. We recorded neuronal activity in the primary auditory cortex of awake rats presented with these stimuli. The responses of the majority of individual neurons were selective for a subset of stimuli with specific statistics. However, as a neuronal population, the responses were remarkably stable over large changes in stimulus statistics, exhibiting a similar range in firing rate, response strength, variability and information rate, and only minor variation in receptive field parameters. This pattern of neuronal responses suggests a potentially general principle for cortical encoding of complex acoustic scenes: while individual cortical neurons exhibit selectivity for specific statistical features, a neuronal population preserves a constant response structure across a broad range of statistical parameters.
authors.affiliation: Department of Otorhinolaryngology and Head and Neck Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
authors.forename: Jennifer M
authors.initials: JM
authors.lastname: Blackwell
authors.affiliation: Center for Physics and Biology, Rockefeller University, New York, NY, USA.|Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.
authors.forename: Thibaud O
authors.initials: TO
authors.lastname: Taillefumier
authors.affiliation: Department of Otorhinolaryngology and Head and Neck Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
authors.forename: Ryan G
authors.initials: RG
authors.lastname: Natan
authors.affiliation: Department of Otorhinolaryngology and Head and Neck Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
authors.forename: Isaac M
authors.initials: IM
authors.lastname: Carruthers
authors.affiliation: Center for Physics and Biology, Rockefeller University, New York, NY, USA.
authors.forename: Marcelo O
authors.initials: MO
authors.lastname: Magnasco
authors.affiliation: Department of Otorhinolaryngology and Head and Neck Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.|Center for Physics and Biology, Rockefeller University, New York, NY, USA.
authors.forename: Maria N
authors.initials: MN
authors.lastname: Geffen
mesh_terms: D000161:Acoustic Stimulation; D000818:Animals; D001303:Auditory Cortex / Q000166:cytology / Q000502:physiology*; D001307:Auditory Perception; D005072:Evoked Potentials, Auditory; D008297:Male; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology; D051381:Rats; D020318:Rats, Long-Evans; D017207:Rats, Sprague-Dawley
keywords: auditory cortex; computational neuroscience; electrophysiology; natural scene analysis; rat; receptive field