Abstract
Recently developed methods in computational neuroethology have enabled increasingly detailed and comprehensive quantification of animal movements and behavioral kinematics. Vocal communication behavior is well poised for application of similar large-scale quantification methods in the service of physiological and ethological studies. This review describes emerging techniques that can be applied to acoustic and vocal communication signals with the goal of enabling study beyond a small number of model species. We review a range of modern computational methods for bioacoustics, signal processing, and brain-behavior mapping. Along with a discussion of recent advances and techniques, we include challenges and broader goals in establishing a framework for the computational neuroethology of vocal communication.
Highlights
Over the past several years emerging methods have enabled biologists to capture and quantify ethological data in ways that yield new insights into the structure and organization of behavior
Many of the challenges that exist in the computational neuroethology of vocal behavior are neither new nor unique and parallel those in other areas of human and animal behavior
We discussed how relational structure can be extracted from vocal signals, how these signals can be clustered in learned latent spaces, and how these latent spaces capture different aspects of the information contained within the underlying signals
Summary
Over the past several years emerging methods have enabled biologists to capture and quantify ethological data in ways that yield new insights into the structure and organization of behavior. The computational neuroethology of vocal communication parallels the emerging field of motion sequencing and the mapping behavioral kinematics, where new technologies allowing researchers to map postures and behavioral kinematics have facilitated new understandings of behavioral dynamics across scales (Anderson and Perona, 2014; Berman, 2018; Brown and De Bivort, 2018; Christin et al, 2019; Datta et al, 2019; Pereira et al, 2019). It is the goal of computational neuroethology to develop an understanding of the organization of behaviors, and the neural and cognitive mechanisms that facilitate behavior. Throughout our review of current approaches, we relay ongoing challenges, discuss future directions, and attempt to give practical advice on vocal analyses
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