Cited by 453Memory and Neural MechanismsNeural dynamics and brain functionUndergraduate Neuroscience Education and Research

Computational Neuroethology: A Call to Action

Open access
Datta, Sandeep Robert, Anderson, David J., Branson, Kristin, Perona, Pietro, Leifer, Andrew·2019·Neuron

Abstract

The brain is worthy of study because it is in charge of behavior. A flurry of recent technical advances in measuring and quantifying naturalistic behaviors provide an important opportunity for advancing brain science. However, the problem of understanding unrestrained behavior in the context of neural recordings and manipulations remains unsolved, and developing approaches to addressing this challenge is critical. Here we discuss considerations in computational neuroethology-the science of quantifying naturalistic behaviors for understanding the brain-and propose strategies to evaluate progress. We point to open questions that require resolution and call upon the broader systems neuroscience community to further develop and leverage measures of naturalistic, unrestrained behavior, which will enable us to more effectively probe the richness and complexity of the brain.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.neuron.2019.09.038

Cites

142 of 142 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Neuroscience studies in particular have embraced novel tools for motion tracking, pose estimation, and behavioral classification.

    “Neuroscience studies in particular have embraced novel tools for motion tracking, pose estimation (Fig. 1d, e), and behavioral classification (e.g., ref. 141).”

    From Perspectives in machine learning for wildlife conservation (2022) · cites this paper as [141]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

6 of the 148 references couldn’t be matched to a known paper.

Research works printed but not linked: 4

  1. Liu M, Sharma AK, Shaevitz JW, and Leifer AM (2018b). Temporal processing and context dependency in C. elegans mechanosensation. arXiv:180304085 [physics, q-bio]. PMC6054533 29943731
  2. Musall S, Kaufman MT, Gluf S, and Churchland A (2018). Movement-related activity dominates cortex during sensory-guided decision making. bioRxiv, 308288.
  3. Scholz M, Linder AN, Randi F, Sharma AK, Yu X, Shaevitz JW, and Leifer A (2018). Predicting natural behavior from whole-brain neural dynamics. bioRxiv, 445643.
  4. Sutton RS, and Barto AG (1998). Introduction to reinforcement learning, Vol 2 (MIT press Cambridge).

Cited by

Sorted by citations

Authors
Datta, S. R., Anderson, D. J., Branson, K., Perona, P., & Leifer, A.
Affiliations
  • Harvard University (US)
  • California Institute of Technology (US)
  • Howard Hughes Medical Institute (US)
  • Princeton University (US)
Corresponding author
  • Datta, Sandeep Robert
  • Leifer, Andrew
Venue
Neuron
Publisher
Elsevier BV
Published
2019-10
Volume
104
Issue
1
Pages
11-24
ISSN
0896-6273 (ISSN-L)
OpenAlex
W2980030724
Cited by
453
References
148
Citations by year
2026: 61 · 2025: 71 · 2024: 73 · 2023: 66 · 2022: 68 · 2021: 65 · 2020: 46 · 2019: 3
FWCI
5.84
Type
journal article
Language
en
Open access
Locations
  • Neuron (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • CaltechAUTHORS (California Institute of Technology) (submittedVersion)
Funders
  • Simons Foundation
  • National Institutes of Health (U24NS109520, U19NS112953, RO1MH112593, U19NS108179, RO1DC016222)
  • National Science Foundation (1845137, PHY-1734030)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Undergraduate Neuroscience Education and Research
Keywords
naturalistic behavior, behavior quantification, neural recording, neural manipulation, systems neuroscience
MeSH terms
Machine Learning, Animals, Behavior, Animal, Brain, Ethology, Neurosciences, Electrophysiological Phenomena

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review