Motor memories of object dynamics are categorically organized

  1. Evan Cesanek  Is a corresponding author
  2. Zhaoran Zhang
  3. James N Ingram
  4. Daniel M Wolpert
  5. J Randall Flanagan
  1. Columbia University, United States
  2. Queen's University, Canada

Abstract

The ability to predict the dynamics of objects, linking applied force to motion, underlies our capacity to perform many of the tasks we carry out on a daily basis. Thus, a fundamental question is how the dynamics of the myriad objects we interact with are organized in memory. Using a custom-built three-dimensional robotic interface that allowed us to simulate objects of varying appearance and weight, we examined how participants learned the weights of sets of objects that they repeatedly lifted. We find strong support for the novel hypothesis that motor memories of object dynamics are organized categorically, in terms of families, based on covariation in their visual and mechanical properties. A striking prediction of this hypothesis, supported by our findings and not predicted by standard associative map models, is that outlier objects with weights that deviate from the family-predicted weight will never be learned despite causing repeated lifting errors.

Data availability

All source data, analysis code, and figure generation code is available in the supplementary files.

Article and author information

Author details

  1. Evan Cesanek

    Department of Neuroscience, Columbia University, New York, United States
    For correspondence
    evan.cesanek@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5335-6604
  2. Zhaoran Zhang

    Department of Neuroscience, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. James N Ingram

    Department of Neuroscience, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Daniel M Wolpert

    Department of Neuroscience, Columbia University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2011-2790
  5. J Randall Flanagan

    Centre for Neuroscience Studies, Queen's University, Kingston, Canada
    Competing interests
    The authors declare that no competing interests exist.

Funding

No external funding was received for this work.

Ethics

Human subjects: All experiments were conducted in accordance with the 1964 Declaration of Helsinki, following protocol approved by the Columbia University Institutional Review Board (IRB-AAAR9148). Written informed consent was obtained from all participants prior to their participation.

Copyright

© 2021, Cesanek 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

  • 1,181
    views
  • 173
    downloads
  • 16
    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. Evan Cesanek
  2. Zhaoran Zhang
  3. James N Ingram
  4. Daniel M Wolpert
  5. J Randall Flanagan
(2021)
Motor memories of object dynamics are categorically organized
eLife 10:e71627.
https://doi.org/10.7554/eLife.71627

Share this article

https://doi.org/10.7554/eLife.71627

Further reading

    1. Neuroscience
    Poortata Lalwani, Thad Polk, Douglas D Garrett
    Research Article

    Moment-to-moment neural variability has been shown to scale positively with the complexity of stimulus input. However, the mechanisms underlying the ability to align variability to input complexity are unknown. Using a combination of behavioral methods, computational modeling, fMRI, MR spectroscopy, and pharmacological intervention, we investigated the role of aging and GABA in neural variability during visual processing. We replicated previous findings that participants expressed higher variability when viewing more complex visual stimuli. Additionally, we found that such variability modulation was associated with higher baseline visual GABA levels and was reduced in older adults. When pharmacologically increasing GABA activity, we found that participants with lower baseline GABA levels showed a drug-related increase in variability modulation while participants with higher baseline GABA showed no change or even a reduction, consistent with an inverted-U account. Finally, higher baseline GABA and variability modulation were jointly associated with better visual-discrimination performance. These results suggest that GABA plays an important role in how humans utilize neural variability to adapt to the complexity of the visual world.

    1. Neuroscience
    Roshani Nhuchhen Pradhan, Craig Montell, Youngseok Lee
    Research Article

    The question as to whether animals taste cholesterol taste is not resolved. This study investigates whether the fruit fly, Drosophila melanogaster, is capable of detecting cholesterol through their gustatory system. We found that flies are indifferent to low levels of cholesterol and avoid higher levels. The avoidance is mediated by gustatory receptor neurons (GRNs), demonstrating that flies can taste cholesterol. The cholesterol-responsive GRNs comprise a subset that also responds to bitter substances. Cholesterol detection depends on five ionotropic receptor (IR) family members, and disrupting any of these genes impairs the flies' ability to avoid cholesterol. Ectopic expressions of these IRs in GRNs reveals two classes of cholesterol receptors, each with three shared IRs and one unique subunit. Additionally, expressing cholesterol receptors in sugar-responsive GRNs confers attraction to cholesterol. This study reveals that flies can taste cholesterol, and that the detection depends on IRs in GRNs.