Human orbitofrontal cortex represents a cognitive map of state space NW Schuck, MB Cai, RC Wilson, Y Niv Neuron 91 (6), 1402-1412, 2016 | 510 | 2016 |
A neural model for temporal order judgments and their active recalibration: a common mechanism for space and time? M Cai, C Stetson, DM Eagleman Frontiers in psychology 3, 470, 2012 | 88 | 2012 |
Transfer learning via minimizing the performance gap between domains B Wang, JA Mendez, MB Cai, E Eaton Advances in Neural Information Processing Systems 32, 10645-10655, 2019 | 59 | 2019 |
Perceived duration is reduced by repetition but not by high-level expectation MB Cai, DM Eagleman, WJ Ma Journal of Vision 15 (13), 19-19, 2015 | 50 | 2015 |
Representational structure or task structure? Bias in neural representational similarity analysis and a Bayesian method for reducing bias MB Cai, NW Schuck, JW Pillow, Y Niv PLoS computational biology 15 (5), e1006299, 2019 | 47 | 2019 |
BrainIAK: The brain imaging analysis kit M Kumar, MJ Anderson, JW Antony, C Baldassano, PP Brooks, MB Cai, ... Aperture neuro 1 (4), 2021 | 40 | 2021 |
Facilitating open-science with realistic fMRI simulation: validation and application C Ellis, C Baldassano, AC Schapiro, MB Cai, JD Cohen PeerJ 8, e8564, 2020 | 33 | 2020 |
A Bayesian method for reducing bias in neural representational similarity analysis MB Cai, NW Schuck, JW Pillow, Y Niv Advances In Neural Information Processing Systems, 4952-4960, 2016 | 32 | 2016 |
Duration estimates within a modality are integrated sub-optimally MB Cai, DM Eagleman Frontiers in Psychology 6, 2015 | 14 | 2015 |
Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis MB Cai, M Shvartsman, A Wu, H Zhang, X Zhu Neuropsychologia 144, 107500, 2020 | 13 | 2020 |
A novel approach to activation detection in fMRI based on empirical mode decomposition T Zheng, M Cai, T Jiang Journal of integrative neuroscience 9 (04), 407-427, 2010 | 8 | 2010 |
Humans combine value learning and hypothesis testing strategically in multi-dimensional probabilistic reward learning M Song, PA Baah, MB Cai, Y Niv PLOS Computational Biology 18 (11), e1010699, 2022 | 5 | 2022 |
Using Recurrent Neural Networks to Understand Human Reward Learning M Song, Y Niv, MB Cai Proceedings of the Annual Meeting of the Cognitive Science Society 43 (43), 2021 | 4 | 2021 |
Learning what is relevant for rewards via value-based serial hypothesis testing M Song, Y Niv, MB Cai 42nd Annual Meeting of the Cognitive Science Society, July 29, 2020 | 4* | 2020 |
Disentangled Deep Autoencoding Regularization for Robust Image Classification Z Duan, MR Min, LE Li, M Cai, Y Xu, B Ni arXiv preprint arXiv:1902.11134, 2019 | 4 | 2019 |
Learning to perceive objects by prediction T Arora, LE Li, MB Cai SVRHM 2021 Workshop@ NeurIPS, 2021 | 3 | 2021 |
Real time functional MRI training to decrease motion in imaging studies: lack of significant improvement TM Lal, PR Baldwin, MB Cai, RR Savjani, DM Eagleman, D Ress, R Salas Bulletin of the Menninger Clinic 80 (4), 348-356, 2016 | 3 | 2016 |
A neural model for temporal order judgments and their active recalibration: a common mechanism for space and time? D Eagleman, M Cai, C Stetson Journal of Vision 9 (8), 2-2, 2009 | 1 | 2009 |
Learning 3D object-centric representation through prediction J Day, T Arora, J Liu, LE Li, MB Cai arXiv preprint arXiv:2403.03730, 2024 | | 2024 |
Should you trust your RSA result? A Bayesian method for reducing bias in neural representational similarity analysis. MB Cai, N Schuck, M Anderson, J Pillow, Y Niv Journal of Vision 17 (10), 571-571, 2017 | | 2017 |