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Amaro, Diana; Ferreiro, Dardo N.; Grothe, Benedikt ORCID logoORCID: https://orcid.org/0000-0001-7317-0615 and Pecka, Michael ORCID logoORCID: https://orcid.org/0000-0001-8960-1651 (13. September 2021): Source identity shapes spatial preference in primary auditory cortex during active navigation. In: Current biology, Vol. 31, No. 17, e5: pp. 3875-3883 [PDF, 2MB]


Information about the position of sensory objects and identifying their concurrent behavioral relevance is vital to navigate the environment. In the auditory system, spatial information is computed in the brain based on the position of the sound source relative to the observer and thus assumed to be egocentric throughout the auditory pathway. This assumption is largely based on studies conducted in either anesthetized or head-fixed and passively listening animals, thus lacking self-motion and selective listening. Yet these factors are fundamental components of natural sensing1 that may crucially impact the nature of spatial coding and sensory object representation.2 How individual objects are neuronally represented during unrestricted self-motion and active sensing remains mostly unexplored. Here, we trained gerbils on a behavioral foraging paradigm that required localization and identification of sound sources during free navigation. Chronic tetrode recordings in primary auditory cortex during task performance revealed previously unreported sensory object representations. Strikingly, the egocentric angle preference of the majority of spatially sensitive neurons changed significantly depending on the task-specific identity (outcome association) of the sound source. Spatial tuning also exhibited large temporal complexity. Moreover, we encountered egocentrically untuned neurons whose response magnitude differed between source identities. Using a neural network decoder, we show that, together, these neuronal response ensembles provide spatiotemporally co-existent information about both the egocentric location and the identity of individual sensory objects during self-motion, revealing a novel cortical computation principle for naturalistic sensing.

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