Correlations across timing cues in natural vocalizations predict biases in judging synthetic sound burst durations

Abstract

AbstractIt is well known that animals rely on multiple sources of information in order to successfully identify sounds in natural environments, to make decisions that are optimal for their survival. For example, rats use duration and pitch cues to respond appropriately to prosocial and distress vocalizations (Saito et al., 2019). Vocalization duration cues are known to co-vary with other temporal cues (Khatami et al., 2018), yet little is known about whether animals rely upon such co-variations to successfully discriminate sounds. In the current study, we find natural alarm vocalizations in rats have onset and offset slopes that are correlated with their duration. Accordingly, vocalizations with faster onset slopes are more likely to have shorter durations. Given that vocalization slopes begin and end within milliseconds, they could provide rapid perceptual cues for predicting and discriminating vocalization duration. To examine this possibility, we train rodents to discriminate duration differences in sequences of synthetic vocalizations and examine how artificially changing the slope impacts duration judgments. We find animals are biased to misjudge a range of synthetic vocalizations as being shorter in duration when the onset and offset slopes are artificially fast. Moreover, this bias is reduced when rats are exposed to multiple synthetic vocalization bursts. The observed perceptual bias is accurately captured by a Bayesian decision-theoretic model that utilizes the empirical joint distribution of duration and onset slopes in natural vocalizations as a prior during duration judgements of synthetic vocalizations. This model also explains why the bias is reduced when more evidence is accumulated across multiple bursts, reducing the prior’s influence. These results support the theory that animals are sensitive to fine-grained statistical co-variations in auditory timing cues and integrate this information optimally with incoming sensory evidence to guide their decisions.