If a fish can pass the mark test, what are the implications for consciousness and self-awareness testing in animals? DOI Creative Commons
Masanori Kohda, Takashi Hotta, Tomohiro Takeyama

et al.

PLoS Biology, Journal Year: 2019, Volume and Issue: 17(2), P. e3000021 - e3000021

Published: Feb. 7, 2019

The ability to perceive and recognise a reflected mirror image as self (mirror self-recognition, MSR) is considered hallmark of cognition across species. Although MSR has been reported in mammals birds, it not known occur any other major taxon. Potentially limiting our test for taxa that the established assay, mark test, requires animals display contingency testing self-directed behaviour. These behaviours may be difficult humans interpret taxonomically divergent animals, especially those lack dexterity (or limbs) required touch mark. Here, we show fish, cleaner wrasse Labroides dimidiatus, shows behaviour reasonably interpreted passing through all phases test: (i) social reactions towards reflection, (ii) repeated idiosyncratic mirror, (iii) frequent observation their reflection. When subsequently provided with coloured tag modified fish attempt remove by scraping body presence but no response transparent marks or absence mirror. This remarkable finding presents challenge interpretation test—do accept these behavioural responses, which are taken evidence self-recognition species during lead conclusion self-aware? Or do rather decide patterns have basis cognitive process than pass test? If former, what does this mean understanding animal intelligence? latter, application metric abilities?This Short Report received both positive negative reviews experts. Academic Editor written an accompanying Primer publishing alongside article (https://doi.org/10.1371/journal.pbio.3000112). linked complementary expert perspective; discusses how current study should context against self-awareness wide range animals.

Language: Английский

DeepLabCut: markerless pose estimation of user-defined body parts with deep learning DOI
Alexander Mathis, Pranav Mamidanna, Kevin M. Cury

et al.

Nature Neuroscience, Journal Year: 2018, Volume and Issue: 21(9), P. 1281 - 1289

Published: Aug. 10, 2018

Language: Английский

Citations

3961
Neuroscience Needs Behavior: Correcting a Reductionist Bias DOI Creative Commons
John W. Krakauer, Asif A. Ghazanfar,

Àlex Gómez-Marín

et al.

Neuron, Journal Year: 2017, Volume and Issue: 93(3), P. 480 - 490

Published: Feb. 1, 2017

Language: Английский

Citations

1280
Using DeepLabCut for 3D markerless pose estimation across species and behaviors DOI
Tanmay Nath, Alexander Mathis,

An Chi Chen

et al.

Nature Protocols, Journal Year: 2019, Volume and Issue: 14(7), P. 2152 - 2176

Published: June 21, 2019

Language: Английский

Citations

1142
Mapping Sub-Second Structure in Mouse Behavior DOI Creative Commons
Alexander B. Wiltschko, Matthew J. Johnson, Giuliano Iurilli

et al.

Neuron, Journal Year: 2015, Volume and Issue: 88(6), P. 1121 - 1135

Published: Dec. 1, 2015

Language: Английский

Citations

739
Fast animal pose estimation using deep neural networks DOI
Talmo Pereira, Diego Aldarondo, Lindsay Willmore

et al.

Nature Methods, Journal Year: 2018, Volume and Issue: 16(1), P. 117 - 125

Published: Dec. 11, 2018

Language: Английский

Citations

590
Global Brain Dynamics Embed the Motor Command Sequence of Caenorhabditis elegans DOI Creative Commons
Saul Kato, Harris S. Kaplan,

Tina Schrödel

et al.

Cell, Journal Year: 2015, Volume and Issue: 163(3), P. 656 - 669

Published: Oct. 1, 2015

While isolated motor actions can be correlated with activities of neuronal networks, an unresolved problem is how the brain assembles these into organized behaviors like action sequences. Using brain-wide calcium imaging in Caenorhabditis elegans, we show that a large proportion neurons across share information by engaging coordinated, dynamical network activity. This state evolves on cycle, each segment which recruits different sub-populations and explicitly mapped, single trial basis, to animals' major commands. organization defines assembly commands string run-and-turn sequence cycles, including decisions between alternative behaviors. These dynamics serve as robust scaffold for selection response sensory input. study shows coordination activity patterns global underlies high-level behavior.

Language: Английский

Citations

545
DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning DOI Creative Commons
Jacob M. Graving,

Daniel H. Chae,

Hemal Naik

et al.

eLife, Journal Year: 2019, Volume and Issue: 8

Published: Oct. 1, 2019

Quantitative behavioral measurements are important for answering questions across scientific disciplines-from neuroscience to ecology. State-of-the-art deep-learning methods offer major advances in data quality and detail by allowing researchers automatically estimate locations of an animal's body parts directly from images or videos. However, currently available animal pose estimation have limitations speed robustness. Here, we introduce a new easy-to-use software toolkit, DeepPoseKit, that addresses these problems using efficient multi-scale model, called Stacked DenseNet, fast GPU-based peak-detection algorithm estimating keypoint with subpixel precision. These improve processing >2x no loss accuracy compared methods. We demonstrate the versatility our multiple challenging tasks laboratory field settings-including groups interacting individuals. Our work reduces barriers advanced tools measuring behavior has broad applicability sciences.

Language: Английский

Citations

463
Neural Circuit Mechanisms of Social Behavior DOI Creative Commons
Patrick Chen, Weizhe Hong

Neuron, Journal Year: 2018, Volume and Issue: 98(1), P. 16 - 30

Published: April 1, 2018

Language: Английский

Citations

460
The Role of Variability in Motor Learning DOI Open Access
Ashesh K. Dhawale, Maurice A. Smith, Bence P. Ölveczky

et al.

Annual Review of Neuroscience, Journal Year: 2017, Volume and Issue: 40(1), P. 479 - 498

Published: May 10, 2017

Trial-to-trial variability in the execution of movements and motor skills is ubiquitous widely considered to be unwanted consequence a noisy nervous system. However, recent studies have suggested that may also feature how sensorimotor systems operate learn. This view, rooted reinforcement learning theory, equates with purposeful exploration space that, when coupled reinforcement, can drive learning. Here we review explore relationship between both humans animal models. We discuss neural circuit mechanisms underlie generation regulation consider implications this work has for our understanding

Language: Английский

Citations

438
Computational Neuroethology: A Call to Action DOI Creative Commons
Sandeep Robert Datta, David J. Anderson, Kristin Branson

et al.

Neuron, Journal Year: 2019, Volume and Issue: 104(1), P. 11 - 24

Published: Oct. 1, 2019

Language: Английский

Citations

392