Systems Neuroscience of Natural Behaviors in Rodents DOI Creative Commons
Emily Jane Dennis, Ahmed El Hady, Angie Michaiel

et al.

Journal of Neuroscience, Journal Year: 2020, Volume and Issue: 41(5), P. 911 - 919

Published: Dec. 18, 2020

Animals evolved in complex environments, producing a wide range of behaviors, including navigation, foraging, prey capture, and conspecific interactions, which vary over timescales ranging from milliseconds to days. Historically, these behaviors have been the focus study for ecology ethology, while systems neuroscience has largely focused on short timescale that can be repeated thousands times occur highly artificial environments. Thanks recent advances machine learning, miniaturization, computation, it is newly possible freely moving animals more natural conditions applying techniques: performing temporally specific perturbations, modeling behavioral strategies, recording large numbers neurons are moving. The authors this review group scientists with deep appreciation common aims neuroscience, ecology, ethology. We believe an extremely exciting time neuroscientist, as we opportunity grow field, embrace interdisciplinary, open, collaborative research provide new insights allow researchers link knowledge across disciplines, species, scales. Here discuss origins context our own work highlight how combining approaches fields provided fresh into research. hope facilitates some interactions alliances helps us all do even better science, together.

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

3988
Spontaneous behaviors drive multidimensional, brainwide activity DOI Open Access
Carsen Stringer, Marius Pachitariu, Nicholas A. Steinmetz

et al.

Science, Journal Year: 2019, Volume and Issue: 364(6437)

Published: April 19, 2019

Neuron activity across the brain How is it that groups of neurons dispersed through interact to generate complex behaviors? Three papers in this issue present brain-scale studies neuronal and dynamics (see Perspective by Huk Hart). Allen et al. found thirsty mice, there widespread neural related stimuli elicit licking drinking. Individual encoded task-specific responses, but every area contained with different types response. Optogenetic stimulation thirst-sensing one reinstated drinking previously signaled thirst. Gründemann investigated mouse basal amygdala relation behavior during tasks. Two ensembles showed orthogonal exploratory nonexploratory behaviors, possibly reflecting levels anxiety experienced these areas. Stringer analyzed spontaneous firing, finding primary visual cortex both information motor facial movements. The variability responses mainly arousal reflects encoding latent behavioral states. Science , p. eaav3932 eaav8736 eaav7893 ; see also 236

Language: Английский

Citations

1396
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
Midbrain circuits that set locomotor speed and gait selection DOI
Vittorio Caggiano, Roberto Leiras, Haizea Goñi-Erro

et al.

Nature, Journal Year: 2018, Volume and Issue: 553(7689), P. 455 - 460

Published: Jan. 1, 2018

Language: Английский

Citations

403
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
Large-scale neural recordings call for new insights to link brain and behavior DOI
Anne E. Urai, Brent Doiron, Andrew M. Leifer

et al.

Nature Neuroscience, Journal Year: 2022, Volume and Issue: 25(1), P. 11 - 19

Published: Jan. 1, 2022

Language: Английский

Citations

255
Structure of the Zebrafish Locomotor Repertoire Revealed with Unsupervised Behavioral Clustering DOI Creative Commons
João C. Marques, Simone Lackner, Rita Félix

et al.

Current Biology, Journal Year: 2018, Volume and Issue: 28(2), P. 181 - 195.e5

Published: Jan. 1, 2018

Language: Английский

Citations

232
Simple Behavioral Analysis (SimBA) – an open source toolkit for computer classification of complex social behaviors in experimental animals DOI Creative Commons
Simon Nilsson, Nastacia L. Goodwin,

Jia Jie Choong

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2020, Volume and Issue: unknown

Published: April 20, 2020

Abstract Aberrant social behavior is a core feature of many neuropsychiatric disorders, yet the study complex in freely moving rodents relatively infrequently incorporated into preclinical models. This likely contributes to limited translational impact. A major bottleneck for adoption socially complex, ethology-rich, procedures are technical limitations consistently annotating detailed behavioral repertoires rodent behavior. Manual annotation subjective, prone observer drift, and extremely time-intensive. Commercial approaches expensive inferior manual annotation. Open-source alternatives often require significant investments specialized hardware computational programming knowledge. By combining recent advances convolutional neural networks pose-estimation with further machine learning analysis, primed inclusion under umbrella neuroethology. Here we present an open-source package graphical interface workflow (Simple Behavioral Analysis, SimBA) that uses create supervised predictive classifiers behavior, millisecond resolution accuracies can out-perform human observers. SimBA does not video acquisition nor extensive background. Standard descriptive statistical along region interest annotation, provided addition classifier generation. To increase ease-of-use behavioural neuroscientists, designed accessible menus pre-processing videos, training datasets, selecting advanced options, robust validation functions flexible visualizations tools. allows transparency, explainability tunability prior to, during, experimental use. We demonstrate this approach both mice rats by classifying behaviors commonly central brain function motivation. Finally, provide library poseestimation weights resident-intruder rats. All code data, together tutorials documentation, available on GitHub repository . Graphical abstract (GUI) creating (a) Pre-process videos supports common (e.g., cropping, clipping, sampling, format conversion, etc.) be performed either single or as batch. (b) Managing data classification projects Pose-estimation tracking DeepLabCut DeepPoseKit imported created managed within user interface, results projects. also userdrawn region-of-interests (ROIs) statistics animal movements, features (c) Create classifiers, perform classifications, analyze has tools correcting inaccuracies when multiple subjects frame, events from optimizing hyperparameters discrimination thresholds. number checkpoints logs included increased Both summary at end analysis. accepts annotations generated elsewhere (such through JWatcher) (d) Visualize several options visualizing movements ROI analyzing durations frequencies classified behaviors. See comprehensive documentation tutorials.

Language: Английский

Citations

230
Anipose: A toolkit for robust markerless 3D pose estimation DOI Creative Commons
Pierre Karashchuk, Katie L. Rupp, Evyn S Dickinson

et al.

Cell Reports, Journal Year: 2021, Volume and Issue: 36(13), P. 109730 - 109730

Published: Sept. 1, 2021

Quantifying movement is critical for understanding animal behavior. Advances in computer vision now enable markerless tracking from 2D video, but most animals move 3D. Here, we introduce Anipose, an open-source toolkit robust 3D pose estimation. Anipose built on the method DeepLabCut, so users can expand their existing experimental setups to obtain accurate tracking. It consists of four components: (1) a calibration module, (2) filters resolve errors, (3) triangulation module that integrates temporal and spatial regularization, (4) pipeline structure processing large numbers videos. We evaluate board as well mice, flies, humans. By analyzing leg kinematics tracked with identify key role joint rotation motor control fly walking. To help get started tracking, provide tutorials documentation at http://anipose.org/.

Language: Английский

Citations

201
Measuring behavior across scales DOI Creative Commons
Gordon J Berman

BMC Biology, Journal Year: 2018, Volume and Issue: 16(1)

Published: Feb. 23, 2018

The need for high-throughput, precise, and meaningful methods measuring behavior has been amplified by our recent successes in manipulating neural circuitry. largest challenges associated with moving this direction, however, are not technical but instead conceptual: what numbers should one put on the movements an animal is performing (or performing)? In review, I will describe how theoretical data analytical ideas interfacing recently-developed computational experimental methodologies to answer these questions across a variety of contexts, length scales, time scales. attempt highlight commonalities between approaches areas where further advances necessary place same quantitative footing as other scientific fields.

Language: Английский

Citations

192