| Resting-state functional connectivity predicts cognitive impairment related to Alzheimer's disease Q Lin, MD Rosenberg, K Yoo, TW Hsu, TP O'Connell, MM Chun Frontiers in aging neuroscience 10, 94, 2018 | 95 | 2018 |
| Predicting eye movement patterns from fMRI responses to natural scenes TP O’Connell, MM Chun Nature communications 9 (1), 5159, 2018 | 49 | 2018 |
| Dissociation of salience-driven and content-driven spatial attention to scene category with predictive decoding of gaze patterns TP O'Connell, DB Walther Journal of vision 15 (5), 20-20, 2015 | 26 | 2015 |
| Getting aligned on representational alignment I Sucholutsky, L Muttenthaler, A Weller, A Peng, A Bobu, B Kim, BC Love, ... arXiv preprint arXiv:2310.13018, 2023 | 16 | 2023 |
| Searching through functional space reveals distributed visual, auditory, and semantic coding in the human brain S Kumar, CT Ellis, TP O’Connell, MM Chun, NB Turk-Browne PLOS Computational Biology 16 (12), e1008457, 2020 | 8 | 2020 |
| Representational differences between line drawings and photographs of natural scenes: A dissociation between multi-voxel pattern analysis and repetition suppression TP O’Connell, PB Sederberg, DB Walther Neuropsychologia 117, 513-519, 2018 | 7 | 2018 |
| Zero-shot neural decoding of visual categories without prior exemplars TP O’Connell, MM Chun, G Kreiman bioRxiv, 700344, 2019 | 3 | 2019 |
| Approaching human 3D shape perception with neurally mappable models TP O'Connell, T Bonnen, Y Friedman, A Tewari, JB Tenenbaum, ... arXiv preprint arXiv:2308.11300, 2023 | 1 | 2023 |
| Beyond Flatland: Pre-training with a Strong 3D Inductive Bias S Gupta, TP O'Connell, B Egger arXiv preprint arXiv:2112.00113, 2021 | 1 | 2021 |
| Zero-shot neural decoding from rhesus macaque inferior temporal cortex using deep convolutional neural networks TP O’Connell, MM Chun, G Kreiman Journal of Vision 19 (10), 209a-209a, 2019 | 1 | 2019 |
| Benchmarking Human Mid-Level Scene Understanding Y Friedman, T O'Connell, D Bear, J Wu, J Fan, J Tenenbaum, D Yamins Journal of Vision 23 (9), 5798-5798, 2023 | | 2023 |
| Artificial neural networks predict human eye movement patterns as an emergent property of training for object classification G Santiago-Reyes, T O'Connell, N Kanwisher Journal of Vision 22 (14), 4194-4194, 2022 | | 2022 |
| Benchmarking mid-level vision with texture-defined 3D objects Y Friedman, T O'Connell, M Siegel, DM Bear, TA Le, B Egger, ... Proceedings of the Annual Meeting of the Cognitive Science Society 44 (44), 2022 | | 2022 |
| Predicting eye movements from deep neural network activity decoded from fMRI responses to natural scenes TP O’Connell, MM Chun bioRxiv, 166421, 2017 | | 2017 |
| Temporal consistency of multi-voxel patterns for repeated scenes T O'Connell, E Ward, M Chun Journal of Vision 14 (10), 1078-1078, 2014 | | 2014 |
| fMRI repetition suppression for scenes in PPA depends on identical feature representation T O'Connell, P Sederberg, D Walther Journal of Vision 13 (9), 1066-1066, 2013 | | 2013 |
| Using functional Magnetic Resonance Imaging repetition suppression to explore the neural representation of natural scenes T O'Connell The Ohio State University, 2013 | | 2013 |
| Reconstructing spatial attention in the human brain: Deep neural network activity decoded from fMRI responses to scenes predicts eye movements TP O’Connell, MM Chun | | |
Marvin M. ChunYale University; Richard M. Colgate Professor of Psychology, Neuroscience, Cognitive ScienceZweryfikowany adres z yale.edu
