Abstract

String-pulling by rodents is a behavior in which animals make rhythmical body, head, and bilateral forearm as well as skilled hand movements to spontaneously reel in a string. Typical analysis includes kinematic assessment of hand movements done by manually annotating frames. Here, we describe a Matlab® based software that allows whole-body motion characterization using optical flow estimation, descriptive statistics, principal component, and independent component analyses as well as temporal measures of Fano factor, entropy, and Higuchi fractal dimension. Based on image-segmentation and heuristic algorithms for object tracking, the software also allows tracking of body, ears, nose, and forehands for estimation of kinematic parameters such as body length, body angle, head roll, head yaw, head pitch, and path and speed of hand movements. The utility of the task and software is demonstrated by characterizing postural and hand kinematic differences in string-pulling behavior of two strains of mice, C57BL/6 and Swiss Webster.

Data availability

The software is available to download from https://github.com/samsoon-inayat/string_pulling_mouse_matlab. All video source and processed data is made available at the following website https://osf.io/gmk9y/?view_only=cdf229798f2d40e08b98aeadd927f1c2

The following data sets were generated
    1. Samsoon Inayat
    (2019) Mouse String-Pulling Data
    Open Science Framework, DOI 10.17605/OSF.IO/GMK9Y.

Article and author information

Author details

  1. Samsoon Inayat

    Neuroscience, University of Lethbridge, Lethbridge, Canada
    For correspondence
    samsoon.inayat@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1966-7967
  2. Surjeet Singh

    Neuroscience, University of Lethbridge, Lethbridge, Canada
    Competing interests
    The authors declare that no competing interests exist.
  3. Arashk Ghasroddashti

    Neuroscience, University of Lethbridge, Lethbridge, Canada
    Competing interests
    The authors declare that no competing interests exist.
  4. Qandeel Qandeel

    Neuroscience, University of Lethbridge, Lethbridge, Canada
    Competing interests
    The authors declare that no competing interests exist.
  5. Pramuka Egodage

    Neuroscience, University of Lethbridge, Lethbridge, Canada
    Competing interests
    The authors declare that no competing interests exist.
  6. Ian Q Whishaw

    Neuroscience, University of Lethbridge, Lethbridge, Canada
    Competing interests
    The authors declare that no competing interests exist.
  7. Majid H Mohajerani

    Canadian Centre for Behavioral Neuroscience, University of Lethbridge, Lethbridge, Canada
    For correspondence
    mohajerani@uleth.ca
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0964-2977

Funding

Canadian Institutes of Health Research (390930)

  • Majid H Mohajerani

Natural Sciences and Engineering Research Council of Canada (40352)

  • Majid H Mohajerani

Alberta Innovates (43568)

  • Majid H Mohajerani

Alberta Alzheimer Research Program Grant (PAZ15010)

  • Majid H Mohajerani

Alberta Alzheimer Research Program Grant (PAZ17010)

  • Majid H Mohajerani

Alzheimer Society of Canada (43674)

  • Majid H Mohajerani

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 experiments were performed in strict accordance with the Canadian Council of Animal Care and were approved by the University of Lethbridge Animal Welfare Committee (Protocol 1812).

Copyright

© 2020, Inayat 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

  • 3,851
    views
  • 358
    downloads
  • 21
    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. Samsoon Inayat
  2. Surjeet Singh
  3. Arashk Ghasroddashti
  4. Qandeel Qandeel
  5. Pramuka Egodage
  6. Ian Q Whishaw
  7. Majid H Mohajerani
(2020)
A Matlab-based toolbox for characterizing behavior of rodents engaged in string-pulling
eLife 9:e54540.
https://doi.org/10.7554/eLife.54540

Share this article

https://doi.org/10.7554/eLife.54540

Further reading

    1. Neuroscience
    John P Grogan, Matthias Raemaekers ... Sanjay G Manohar
    Research Article

    Motivation depends on dopamine, but might be modulated by acetylcholine which influences dopamine release in the striatum, and amplifies motivation in animal studies. A corresponding effect in humans would be important clinically, since anticholinergic drugs are frequently used in Parkinson’s disease, a condition that can also disrupt motivation. Reward and dopamine make us more ready to respond, as indexed by reaction times (RT), and move faster, sometimes termed vigour. These effects may be controlled by preparatory processes that can be tracked using electroencephalography (EEG). We measured vigour in a placebo-controlled, double-blinded study of trihexyphenidyl (THP), a muscarinic antagonist, with an incentivised eye movement task and EEG. Participants responded faster and with greater vigour when incentives were high, but THP blunted these motivational effects, suggesting that muscarinic receptors facilitate invigoration by reward. Preparatory EEG build-up (contingent negative variation [CNV]) was strengthened by high incentives and by muscarinic blockade, although THP reduced the incentive effect. The amplitude of preparatory activity predicted both vigour and RT, although over distinct scalp regions; frontal activity predicted vigour, whereas a larger, earlier, central component predicted RT. The incentivisation of RT was partly mediated by the CNV, though vigour was not. Moreover, the CNV mediated the drug’s effect on dampening incentives, suggesting that muscarinic receptors underlie the motivational influence on this preparatory activity. Taken together, these findings show that a muscarinic blocker impairs motivated action in healthy people, and that medial frontal preparatory neural activity mediates this for RT.

    1. Neuroscience
    Samyogita Hardikar, Bronte Mckeown ... Jonathan Smallwood
    Research Article

    Complex macro-scale patterns of brain activity that emerge during periods of wakeful rest provide insight into the organisation of neural function, how these differentiate individuals based on their traits, and the neural basis of different types of self-generated thoughts. Although brain activity during wakeful rest is valuable for understanding important features of human cognition, its unconstrained nature makes it difficult to disentangle neural features related to personality traits from those related to the thoughts occurring at rest. Our study builds on recent perspectives from work on ongoing conscious thought that highlight the interactions between three brain networks – ventral and dorsal attention networks, as well as the default mode network. We combined measures of personality with state-of-the-art indices of ongoing thoughts at rest and brain imaging analysis and explored whether this ‘tri-partite’ view can provide a framework within which to understand the contribution of states and traits to observed patterns of neural activity at rest. To capture macro-scale relationships between different brain systems, we calculated cortical gradients to describe brain organisation in a low-dimensional space. Our analysis established that for more introverted individuals, regions of the ventral attention network were functionally more aligned to regions of the somatomotor system and the default mode network. At the same time, a pattern of detailed self-generated thought was associated with a decoupling of regions of dorsal attention from regions in the default mode network. Our study, therefore, establishes that interactions between attention systems and the default mode network are important influences on ongoing thought at rest and highlights the value of integrating contemporary perspectives on conscious experience when understanding patterns of brain activity at rest.