Statistical structure of locomotion and its modulation by odors

  1. Liangyu Tao
  2. Siddhi Ozarkar
  3. Jeffrey M Beck
  4. Vikas Bhandawat  Is a corresponding author
  1. Duke University, United States

Abstract

Most behaviors such as making tea are not stereotypical but have an obvious structure. However, analytical methods to objectively extract structure from non-stereotyped behaviors are immature. In this study, we analyze the locomotion of fruit flies and show that this non-stereotyped behavior is well-described by a Hierarchical Hidden Markov Model (HHMM). HHMM shows that a fly's locomotion can be decomposed into a few locomotor features, and odors modulate locomotion by altering the time a fly spends performing different locomotor features. Importantly, although all flies in our dataset use the same set of locomotor features, individual flies vary considerably in how often they employ a given locomotor feature, and how this usage is modulated by odor. This variation is so large that the behavior of individual flies is best understood as being grouped into at least 3-5 distinct clusters, rather than variations around an average fly.

Data availability

Data has been deposited in Dryad Data Repository and is available at doi:10.5061/dryad.m930f2m.

The following data sets were generated

Article and author information

Author details

  1. Liangyu Tao

    Department of Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Siddhi Ozarkar

    Department of Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Jeffrey M Beck

    Department of Neurobiology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Vikas Bhandawat

    Department of Biology, Duke University, Durham, United States
    For correspondence
    vb37@duke.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2608-0403

Funding

National Institute of Neurological Disorders and Stroke

  • Vikas Bhandawat

National Institute on Deafness and Other Communication Disorders

  • Vikas Bhandawat

National Science Foundation

  • Vikas Bhandawat

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

Copyright

© 2019, Tao 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.

Metrics

  • 3,748
    views
  • 464
    downloads
  • 35
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

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. Liangyu Tao
  2. Siddhi Ozarkar
  3. Jeffrey M Beck
  4. Vikas Bhandawat
(2019)
Statistical structure of locomotion and its modulation by odors
eLife 8:e41235.
https://doi.org/10.7554/eLife.41235

Share this article

https://doi.org/10.7554/eLife.41235

Further reading

    1. Genetics and Genomics
    2. Neuroscience
    Monique Marylin Alves de Almeida, Yves De Repentigny ... Rashmi Kothary
    Research Article

    Spinal muscular atrophy (SMA) is caused by mutations in the Survival Motor Neuron 1 (SMN1) gene. While traditionally viewed as a motor neuron disorder, there is involvement of various peripheral organs in SMA. Notably, fatty liver has been observed in SMA mouse models and SMA patients. Nevertheless, it remains unclear whether intrinsic depletion of SMN protein in the liver contributes to pathology in the peripheral or central nervous systems. To address this, we developed a mouse model with a liver-specific depletion of SMN by utilizing an Alb-Cre transgene together with one Smn2B allele and one Smn1 exon 7 allele flanked by loxP sites. Initially, we evaluated phenotypic changes in these mice at postnatal day 19 (P19), when the severe model of SMA, the Smn2B/- mice, exhibit many symptoms of the disease. The liver-specific SMN depletion does not induce motor neuron death, neuromuscular pathology or muscle atrophy, characteristics typically observed in the Smn2B/- mouse at P19. However, mild liver steatosis was observed, although no changes in liver function were detected. Notably, pancreatic alterations resembled that of Smn2B/-mice, with a decrease in insulin-producing β-cells and an increase in glucagon-producingα-cells, accompanied by a reduction in blood glucose and an increase in plasma glucagon and glucagon-like peptide (GLP-1). These changes were transient, as mice at P60 exhibited recovery of liver and pancreatic function. While the mosaic pattern of the Cre-mediated excision precludes definitive conclusions regarding the contribution of liver-specific SMN depletion to overall tissue pathology, our findings highlight an intricate connection between liver function and pancreatic abnormalities in SMA.

    1. Neuroscience
    Maren Klingelhöfer-Jens, Katharina Hutterer ... Tina B Lonsdorf
    Research Article

    Childhood adversity is a strong predictor of developing psychopathological conditions. Multiple theories on the mechanisms underlying this association have been suggested which, however, differ in the operationalization of ‘exposure.’ Altered (threat) learning mechanisms represent central mechanisms by which environmental inputs shape emotional and cognitive processes and ultimately behavior. 1402 healthy participants underwent a fear conditioning paradigm (acquisition training, generalization), while acquiring skin conductance responses (SCRs) and ratings (arousal, valence, and contingency). Childhood adversity was operationalized as (1) dichotomization, and following (2) the specificity model, (3) the cumulative risk model, and (4) the dimensional model. Individuals exposed to childhood adversity showed blunted physiological reactivity in SCRs, but not ratings, and reduced CS+/CS- discrimination during both phases, mainly driven by attenuated CS+ responding. The latter was evident across different operationalizations of ‘exposure’ following the different theories. None of the theories tested showed clear explanatory superiority. Notably, a remarkably different pattern of increased responding to the CS- is reported in the literature for anxiety patients, suggesting that individuals exposed to childhood adversity may represent a specific sub-sample. We highlight that theories linking childhood adversity to (vulnerability to) psychopathology need refinement.