Vocalization categorization behavior explained by a feature-based auditory categorization model

Abstract

Vocal animals produce multiple categories of calls with high between- and within-subject variability, over which listeners must generalize to accomplish call categorization. The behavioral strategies and neural mechanisms that support this ability to generalize are largely unexplored. We previously proposed a theoretical model that accomplished call categorization by detecting features of intermediate complexity that best contrasted each call category from all other categories. We further demonstrated that some neural responses in the primary auditory cortex were consistent with such a model. Here, we asked whether a feature-based model could predict call categorization behavior. We trained both the model and guinea pigs on call categorization tasks using natural calls. We then tested categorization by the model and guinea pigs using temporally and spectrally altered calls. Both the model and guinea pigs were surprisingly resilient to temporal manipulations, but sensitive to moderate frequency shifts. Critically, the model predicted about 50% of the variance in guinea pig behavior. By adopting different model training strategies and examining features that contributed to solving specific tasks, we could gain insight into possible strategies used by animals to categorize calls. Our results validate a model that uses the detection of intermediate-complexity contrastive features to accomplish call categorization.

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting file; Source Data files have been provided for Figures 3 - 12.

Article and author information

Author details

  1. Manaswini Kar

    Center for Neuroscience, University of Pittsburgh, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Marianny Pernia

    Department of Neurobiology, University of Pittsburgh, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9889-3577
  3. Kayla Williams

    Department of Neurobiology, University of Pittsburgh, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Satyabrata Parida

    Department of Neurobiology, University of Pittsburgh, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2896-2522
  5. Nathan Alan Schneider

    Center for Neuroscience, University of Pittsburgh, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9145-5427
  6. Madelyn McAndrew

    Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Isha Kumbam

    Department of Neurobiology, University of Pittsburgh, Pittsburgh, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Srivatsun Sadagopan

    Center for Neuroscience, University of Pittsburgh, Pittsburgh, United States
    For correspondence
    vatsun@pitt.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1116-8728

Funding

National Institutes of Health (R01DC017141)

  • Srivatsun Sadagopan

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: All experimental procedures conformed to the NIH Guide for the Care and Use of Laboratory Animals and were approved by the institutional animal care and use committee of the University of Pittsburgh (protocol number 21069431).

Copyright

© 2022, Kar et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Manaswini Kar
  2. Marianny Pernia
  3. Kayla Williams
  4. Satyabrata Parida
  5. Nathan Alan Schneider
  6. Madelyn McAndrew
  7. Isha Kumbam
  8. Srivatsun Sadagopan
(2022)
Vocalization categorization behavior explained by a feature-based auditory categorization model
eLife 11:e78278.
https://doi.org/10.7554/eLife.78278

Share this article

https://doi.org/10.7554/eLife.78278

Further reading

    1. Evolutionary Biology
    2. Neuroscience
    Jenny Chen, Phoebe R Richardson ... Hopi E Hoekstra
    Research Article

    Genetic variation is known to contribute to the variation of animal social behavior, but the molecular mechanisms that lead to behavioral differences are still not fully understood. Here, we investigate the cellular evolution of the hypothalamic preoptic area (POA), a brain region that plays a critical role in social behavior, across two sister species of deer mice (Peromyscus maniculatus and P. polionotus) with divergent social systems. These two species exhibit large differences in mating and parental care behavior across species and sex. Using single-nucleus RNA-sequencing, we build a cellular atlas of the POA for males and females of both Peromyscus species. We identify four cell types that are differentially abundant across species, two of which may account for species differences in parental care behavior based on known functions of these cell types. Our data further implicate two sex-biased cell types to be important for the evolution of sex-specific behavior. Finally, we show a remarkable reduction of sex-biased gene expression in P. polionotus, a monogamous species that also exhibits reduced sexual dimorphism in parental care behavior. Our POA atlas is a powerful resource to investigate how molecular neuronal traits may be evolving to give rise to innate differences in social behavior across animal species.

    1. Neuroscience
    Julieta Gomez-Frittelli, Gabrielle Frederique Devienne ... Julia A Kaltschmidt
    Research Article

    Intrinsic sensory neurons are an essential part of the enteric nervous system (ENS) and play a crucial role in gastrointestinal tract motility and digestion. Neuronal subtypes in the ENS have been distinguished by their electrophysiological properties, morphology, and expression of characteristic markers, notably neurotransmitters and neuropeptides. Here, we investigated synaptic cell adhesion molecules as novel cell-type markers in the ENS. Our work identifies two type II classic cadherins, Cdh6 and Cdh8, specific to sensory neurons in the mouse colon. We show that Cdh6+ neurons demonstrate all other distinguishing classifications of enteric sensory neurons including marker expression of Calcb and Nmu, Dogiel type II morphology and AH-type electrophysiology and IH current. Optogenetic activation of Cdh6+ sensory neurons in distal colon evokes retrograde colonic motor complexes (CMCs), while pharmacologic blockade of rhythmicity-associated current IH disrupts the spontaneous generation of CMCs. These findings provide the first demonstration of selective activation of a single neurochemical and functional class of enteric neurons and demonstrate a functional and critical role for sensory neurons in the generation of CMCs.