| Evolving images for visual neurons using a deep generative network reveals coding principles and neuronal preferences CR Ponce, W Xiao, PF Schade, TS Hartmann, G Kreiman, MS Livingstone Cell 177 (4), 999-1009. e10, 2019 | 218 | 2019 |
| End-stopping predicts curvature tuning along the ventral stream CR Ponce, TS Hartmann, MS Livingstone Journal of Neuroscience 37 (3), 648-659, 2017 | 47 | 2017 |
| Receptive field positions in area MT during slow eye movements TS Hartmann, F Bremmer, TD Albright, B Krekelberg Journal of Neuroscience 31 (29), 10437-10444, 2011 | 35 | 2011 |
| Cortical magnification plus cortical plasticity equals vision? RT Born, AR Trott, TS Hartmann Vision research 111, 161-169, 2015 | 29 | 2015 |
| Two types of receptive field dynamics in area V4 at the time of eye movements? TS Hartmann, M Zirnsak, M Marquis, FH Hamker, T Moore Frontiers in systems neuroscience 11, 2017 | 28 | 2017 |
| Motion detection based on recurrent network dynamics J Joukes, TS Hartmann, B Krekelberg Frontiers in systems neuroscience 8, 239, 2014 | 23 | 2014 |
| Livingstone. 2019.“Evolving Images for Visual Neurons Using a Deep Generative Network Reveals Coding Principles and Neuronal Preferences.” CR Ponce, W Xiao, PF Schade, TS Hartmann, G Kreiman, S Margaret Cell 177 (4), 999-1009, 0 | 10 | |
| Cortico-cortical feedback from V2 exerts a powerful influence over the visually evoked local field potential and associated spike timing in V1 TS Hartmann, S Raja, SG Lomber, RT Born bioRxiv, 792010, 2019 | 6 | 2019 |
| Evolving super stimuli for real neurons using deep generative networks CR Ponce, W Xiao, PF Schade, TS Hartmann, G Kreiman, MS Livingstone Biorxiv, 516484, 2019 | 6 | 2019 |
| Seeing in the dark with recurrent convolutional neural networks TS Hartmann arXiv preprint arXiv:1811.08537, 2018 | 5 | 2018 |
| Receptive field shifts in area MT during smooth and rapid eye movements TS Hartmann, F Bremmer, TD Albright, B Krekelberg Journal of Vision 6 (6), 406-406, 2006 | 5 | 2006 |
| Guiding machine perception with psychophysics J Dulay, S Poltoratski, TS Hartmann, SE Anthony, WJ Scheirer arXiv preprint arXiv:2207.02241, 2022 | 4 | 2022 |
| Ground truth based metrics for evaluation of machine learning based models for predicting attributes of traffic entities for navigating autonomous vehicles TS Hartmann, JD Zaremba, SE Anthony US Patent 11,840,261, 2023 | 3 | 2023 |
| Weak evidence for neural correlates of task-switching in macaque V1 RD Lange, C Gómez-Laberge, VK Berezovskii, A Pletenev, A Sherdil, ... Journal of Neurophysiology 129 (5), 1021-1044, 2023 | 3 | 2023 |
| Navigation of autonomous vehicles using turn aware machine learning based models for prediction of behavior of a traffic entity SE Anthony, TS Hartmann, JR Maat, DJ Rose, KW Sylvestre US Patent 11,518,413, 2022 | 3 | 2022 |
| Scenario identification for validation and training of machine learning based models for autonomous vehicles JD Zaremba, TS Hartmann, SE Anthony US Patent 11,919,545, 2024 | | 2024 |
| Informing Machine Perception With Psychophysics J Dulay, S Poltoratski, TS Hartmann, SE Anthony, WJ Scheirer Proceedings of the IEEE 112 (2), 88-96, 2024 | | 2024 |
| Perisaccadic Response Modulations in Area V1 of the Macaque Monkey are stimulus-dependent S Klingenhoefer, TS Hartmann, RT Born, F Bremmer Journal of Vision 14 (10), 581-581, 2014 | | 2014 |
| Synchrony and firing rate modulation in area MT at the time of saccades T Hartmann, B Krekelberg Journal of Vision 12 (9), 933-933, 2012 | | 2012 |
| White noise analysis of visual selectivity in area MT during fixation and eye movements TS Hartmann Rutgers University-Graduate School-Newark, 2012 | | 2012 |
Carlos R. PonceHarvard Medical School在 hms.harvard.edu 的电子邮件经过验证
