| Year |
Citation |
Score |
| 2023 |
Sandbrink KJ, Mamidanna P, Michaelis C, Bethge M, Mathis MW, Mathis A. Contrasting action and posture coding with hierarchical deep neural network models of proprioception. Elife. 12. PMID 37254843 DOI: 10.7554/eLife.81499 |
0.765 |
|
| 2023 |
Weinreb C, Osman MAM, Zhang L, Lin S, Pearl J, Annapragada S, Conlin E, Gillis WF, Jay M, Ye S, Mathis A, Mathis MW, Pereira T, Linderman SW, Datta SR. Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics. Biorxiv : the Preprint Server For Biology. PMID 36993589 DOI: 10.1101/2023.03.16.532307 |
0.772 |
|
| 2023 |
Frey M, Mathis MW, Mathis A. NeuroAI: If grid cells are the answer, is path integration the question? Current Biology : Cb. 33: R190-R192. PMID 36917942 DOI: 10.1016/j.cub.2023.01.031 |
0.77 |
|
| 2022 |
Akiti K, Tsutsui-Kimura I, Xie Y, Mathis A, Markowitz JE, Anyoha R, Datta SR, Mathis MW, Uchida N, Watabe-Uchida M. Striatal dopamine explains novelty-induced behavioral dynamics and individual variability in threat prediction. Neuron. PMID 36130595 DOI: 10.1016/j.neuron.2022.08.022 |
0.765 |
|
| 2022 |
Lauer J, Zhou M, Ye S, Menegas W, Schneider S, Nath T, Rahman MM, Di Santo V, Soberanes D, Feng G, Murthy VN, Lauder G, Dulac C, Mathis MW, Mathis A. Multi-animal pose estimation, identification and tracking with DeepLabCut. Nature Methods. 19: 496-504. PMID 35414125 DOI: 10.1038/s41592-022-01443-0 |
0.762 |
|
| 2022 |
Tuia D, Kellenberger B, Beery S, Costelloe BR, Zuffi S, Risse B, Mathis A, Mathis MW, van Langevelde F, Burghardt T, Kays R, Klinck H, Wikelski M, Couzin ID, van Horn G, et al. Perspectives in machine learning for wildlife conservation. Nature Communications. 13: 792. PMID 35140206 DOI: 10.1038/s41467-022-27980-y |
0.768 |
|
| 2021 |
Hausmann SB, Vargas AM, Mathis A, Mathis MW. Measuring and modeling the motor system with machine learning. Current Opinion in Neurobiology. 70: 11-23. PMID 34116423 DOI: 10.1016/j.conb.2021.04.004 |
0.774 |
|
| 2020 |
Kane GA, Lopes G, Saunders JL, Mathis A, Mathis MW. Real-time, low-latency closed-loop feedback using markerless posture tracking. Elife. 9. PMID 33289631 DOI: 10.7554/eLife.61909 |
0.788 |
|
| 2020 |
Mathis A, Schneider S, Lauer J, Mathis MW. A Primer on Motion Capture with Deep Learning: Principles, Pitfalls, and Perspectives. Neuron. 108: 44-65. PMID 33058765 DOI: 10.1016/j.neuron.2020.09.017 |
0.772 |
|
| 2019 |
Mathis MW, Mathis A. Deep learning tools for the measurement of animal behavior in neuroscience. Current Opinion in Neurobiology. 60: 1-11. PMID 31791006 DOI: 10.1016/J.Conb.2019.10.008 |
0.78 |
|
| 2019 |
Nath T, Mathis A, Chen AC, Patel A, Bethge M, Mathis MW. Using DeepLabCut for 3D markerless pose estimation across species and behaviors. Nature Protocols. PMID 31227823 DOI: 10.1038/S41596-019-0176-0 |
0.775 |
|
| 2018 |
Mathis A, Mamidanna P, Cury KM, Abe T, Murthy VN, Mathis MW, Bethge M. DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nature Neuroscience. PMID 30127430 DOI: 10.1038/S41593-018-0209-Y |
0.782 |
|
| 2017 |
Li Y, Mathis A, Grewe BF, Osterhout JA, Ahanonu B, Schnitzer MJ, Murthy VN, Dulac C. Neuronal Representation of Social Information in the Medial Amygdala of Awake Behaving Mice. Cell. PMID 29107332 DOI: 10.1016/J.Cell.2017.10.015 |
0.556 |
|
| 2017 |
Herz AV, Mathis A, Stemmler M. Periodic population codes: From a single circular variable to higher dimensions, multiple nested scales, and conceptual spaces. Current Opinion in Neurobiology. 46: 99-108. PMID 28888183 DOI: 10.1016/J.Conb.2017.07.005 |
0.767 |
|
| 2017 |
Mathis MW, Mathis A, Uchida N. Somatosensory Cortex Plays an Essential Role in Forelimb Motor Adaptation in Mice. Neuron. 93: 1493-1503.e6. PMID 28334611 DOI: 10.1016/J.Neuron.2017.02.049 |
0.751 |
|
| 2016 |
Mathis A, Rokni D, Kapoor V, Bethge M, Murthy VN. Reading Out Olfactory Receptors: Feedforward Circuits Detect Odors in Mixtures without Demixing. Neuron. 91: 1110-23. PMID 27593177 DOI: 10.1016/J.Neuron.2016.08.007 |
0.748 |
|
| 2015 |
Stemmler M, Mathis A, Herz AV. Connecting multiple spatial scales to decode the population activity of grid cells. Science Advances. 1: e1500816. PMID 26824061 DOI: 10.1126/Science.1500816 |
0.765 |
|
| 2015 |
Schönenberger AC, Wagner S, Tuten HC, Schaffner F, Torgerson P, Furrer S, Mathis A, Silaghi C. Host preferences in host-seeking and blood-fed mosquitoes in Switzerland. Medical and Veterinary Entomology. PMID 26685926 DOI: 10.1111/Mve.12155 |
0.302 |
|
| 2015 |
Mathis A, Stemmler MB, Herz AV. Probable nature of higher-dimensional symmetries underlying mammalian grid-cell activity patterns. Elife. 4. PMID 25910055 DOI: 10.7554/Elife.05979 |
0.769 |
|
| 2015 |
Mathis A, Stemmler MB, Herz AV. Author response: Probable nature of higher-dimensional symmetries underlying mammalian grid-cell activity patterns Elife. DOI: 10.7554/Elife.05979.011 |
0.748 |
|
| 2013 |
Mathis A, Herz AV, Stemmler MB. Multiscale codes in the nervous system: the problem of noise correlations and the ambiguity of periodic scales. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 88: 022713. PMID 24032870 DOI: 10.1103/Physreve.88.022713 |
0.75 |
|
| 2012 |
Mathis A, Herz AV, Stemmler MB. Resolution of nested neuronal representations can be exponential in the number of neurons. Physical Review Letters. 109: 018103. PMID 23031134 DOI: 10.1103/Physrevlett.109.018103 |
0.755 |
|
| 2012 |
Mathis A, Herz AV, Stemmler M. Optimal population codes for space: grid cells outperform place cells. Neural Computation. 24: 2280-317. PMID 22594833 DOI: 10.1162/Neco_A_00319 |
0.769 |
|
| 2011 |
Kammerer A, Mathis A, Stemmler M, Herz A, Leibold C. A physiologically inspired model for global remapping in the hippocampus Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-P194 |
0.767 |
|
| 2010 |
Mathis A, Stemmler M, Herz A. How good is grid coding versus place coding for navigation using noisy, spiking neurons? Bmc Neuroscience. 11. DOI: 10.1186/1471-2202-11-S1-O20 |
0.764 |
|
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