Abstract

BackgroundThe systematic characterization of receptive fields (RF) is essential for understanding visual motion processing. The performance of RF estimation depends on the employed stimuli, the complexity of the encoded features, and the quality of the activity readout. Calcium imaging is an attractive readout method for high-throughput neuronal activity recordings. However, calcium recordings are oftentimes noisy and of low temporal resolution. The RF estimation of neurons sensitive to global motion is particularly challenging due to their potentially complex combination of preferred directions across visual field positions. New methodHere, we present a novel noise stimulus, which is enriched with spatiotemporally contiguous motion and thus triggers robust calcium responses. We combined this contiguous motion noise (CMN) stimulus with reverse correlation followed by a two-step nonparametric cluster-based bootstrapping test for efficient and reliable RF estimation. ResultsThe in silico evaluation of our approach showed that RF centre positions and preferred directions are reliably detected in most of the simulated neurons. Suppressive RF components were detected in 40% of the simulated neurons. We successfully applied our approach to estimate the RFs of 163 motion-sensitive neurons in vivo within 40 min in the pretectum of zebrafish. Many in vivo neurons were sensitive to elaborate directional flow fields in their RFs. Comparison with existing methodsOur approach outperforms white noise methods and others due to the optimized motion stimulus statistics and ascertainable fine RF structures. ConclusionsThe CMN method enables efficient, non-biased RF estimation and will benefit systematic high-throughput investigations of RFs using calcium imaging.

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