NYU Shanghai, in partnership with the NYU Graduate School of Arts and Science and the NYU Center for Neural Science, invites applications from exceptional students for PhD study and research in Neural Science.
Participating students are enrolled in the NYU GSAS Neural Science PhD program, complete their coursework at the NYU Center for Neural Science in New York, and then transition to full-time residence at NYU Shanghai where they undertake their doctoral research under the supervision of NYU Shanghai faculty.
Highlights of the Program
- NYU degree upon graduation
- Graduate coursework at the NYU Center for Neural Science in New York
- Research opportunities with and close mentorship by NYU Shanghai faculty
- Access to the vast intellectual resources of NYU GSAS and NYU Center for Neural Science
- Cutting-edge research environment at NYU Shanghai, including the Institute of Brain and Cognitive Science, activities such as a regular program of seminars and visiting academics, a thriving community of PhD students, post-doctoral fellows, and research associates, and links with other universities within and outside China
- Financial aid through the NYU Shanghai Doctoral Fellowship, including tuition, fees, and an annual stipend equal to stipends received by all NYU Neural Science PhD students
- Additional benefits exclusive to the NYU Shanghai program, including international health insurance, housing assistance in New York, and travel funds
Neural Mechanisms of Economic Decision-Making, Reward and Working Memory, Neuropsychiatry of the Prefrontal-Basal Ganglia Loops
Neuroeconomics, Decision-Making, Spatial Cognition, Reinforcement Learning
Human Perception and Action, Eye-Hand Coordination, Virtual Reality
Computational Neuroscience, Network Models for Learning and Memory
Visual Perception, Perceptual Learning, Attention, Amblyopia, Myopia, Adaptive Testing, Brain Imaging, Hierarchical Bayesian Models
Speech and Language, Sensorimotor Integration and Transformation, Memory, Mental Imagery
Recent Publications by NYU Shanghai Faculty
- Wang, K., Banich, M. T., Reinberg, A., Willcutt, E., Cutting, L., Thompson, L., Tufo, S. D., Opfer, J., Lu, Z.-L. & Petrill, S. A., Characterizing and Decomposing the Brain Correlates of Individual Reading Ability
in Adolescents with task-based fMRI, Developmental Cognitive Neuroscience, 37, 100647. (2019)
- Lim S, Mechanisms underlying sharpening of visual response dynamics with familiarity, eLife 8, e44098 (2019)
- Zhao, Y, Lesmes, L. A. & Lu, Z.-L. (2019). Efficient Measurement of the Time Course of Perceptual Sensitivity Change, Vision Research, 154, 21-43.
- Lukinova, E., Wang, Y., Lehrer, S. F., & Erlich, J. C. (2019). Time preferences are reliable across time- horizons and verbal versus experiential tasks. eLife, 27. https://doi.org/10.7554/eLife.39656.001
- Stillman, P., Wilson, J., Denny, M., Desmarais, B., Bhamidi, S., Cranmer, S. & Lu, Z.-L., A Consistent Organizational Structure Across Multiple Functional Subnetworks of the Human Brain, NeuroImage, 197, 24-36. (2019)
- Stillman, P., Lu, Z.-L., Fujita, K., Level of construal shifts functional organization of the brain network, JEP General, doi: 10.1037/xge0000637. (2019)
- Dorr, M., Kwon, M., Lesmes, L., Miller, A., Kazlas, M., Chan, K., Lu, Z.-L., Hunter, D. G. & Bex, P. J. (2019). Binocular Summation and Suppression of Contrast Sensitivity in Strabismus, Fusion and Amblyopia, Frontiers in Neuroscience, https://doi.org/10.3389/fnhum.2019.00234
- Gaut, G., Li, X., Lu, Z.-L. & Steyvers, M. Experimental Design Modulates Variance in BOLD Activation: The Variance Design General Linear Model, Human Brain Mapping, 40, 3918–3929. (2019)
- Gaut, G., Li, X., Turner, B., Cunningham, W. A., Lu, Z.-L. & Steyvers, M., Predicting Task and Subject Differences with Functional Connectivity and BOLD Variability, Brain Connectivity, in press. (2019)
- Molloy, M. F., Bahg, G., Lu, Z.-L. & Turner, B. M.,Individual Differences in the Neural Dynamics of Response Inhibition, Journal of Cognitive Neuroscience, in press. (2019)
- Golubitsky, M., Zhao, Y., Wang, Y. & Lu, Z.-L., Predicting Percepts from the Symmetry of Generalized Rivalry Network Models, Journal of Neurophysiology, in press. (2019)
- Li, L.*, Ni, L., Lappe, M., Niehorster, D.C., & Sun, Q. (2018). No special treatment of independent object motion for heading perception. Journal of Vision, 18(4):19. DOI: 10.1167/18.4.19
- Ebbesen, C. L., Insanally, M. N., Kopec, C. D., Murakami, M., Saiki, A., & Erlich, J. C. (2018). More than Just a “Motor”: Recent Surprises from the Frontal Cortex. The Journal of Neuroscience, 38(44), 9402–9413. https://doi.org/10.1523/JNEUROSCI.1671-18. (2018)
- Tian, X., Ding, N., Teng, X., Bai, F., & Poeppel, D. (2018) Imagined speech influences perceived loudness of sound. Nature Human Behaviour, 2, 225–234. doi:10.1038/s41562-018-0305-8
- Juavinett, A. L., Erlich, J. C. & Churchland, A. K. Decision-making behaviors: weighing ethology, complexity, and sensorimotor compatibility. Current Opinion in Neurobiology 49, 42–50 (2018)
- Rushton, S.K.*, Niehorster, D.C., Warren, P.A, & Li, L.* (2018). The primary role of flow processing in the identification of scene-relative object movement. The Journal of Neuroscience, 38(7),1737-1743
- Lukinova, E., Wang, Y., Lehrer, S. F. & Erlich, J. C. Time preferences are reliable across time-horizons and verbal vs. experiential tasks. bioRxiv (2018). doi:10.1101/351312
- Liu, X., & Tian, X. (2018). The functional relations among motor-based prediction, sensory goals and feedback in learning non-native speech sounds: Evidence from adult Mandarin Chinese speakers with an auditory feedback masking paradigm. Scientific Reports, 8:11910. doi:10.1038/s41598-018-30399-5
- Rustichini, A, Conen KE, Cai X and Padoa-Schioppa C (2017). "Optimal coding and neuronal adaptation in economic decisions." Nat Commun 8(1): 1208
- Lim S, McKee JL, Woloszyn L, Amit Y, Freedman DJ, Sheinberg DL, Brunel N, Inferring learning rules from distributions of firing rates in cortical neurons, Nature Neuroscience 18, 1804-1810 (2015)
- Murray JD, Bernacchia A, Freedman DJ, Romo R, Wallis JD, Cai X, Padoa-Schioppa C, Pasternak T, Seo H, Lee D, Wang XJ (2014) A hierarchy of intrinsic timescales across primate cortex. Nature Neuroscience 17, 1661–1663
- Lim S, Goldman MS, Balanced cortical microcircuitry for spatial working memory based on corrective feedback control, Journal of Neuroscience 34, 6790-6806 (2014)
Selected Faculty and Student Features
"Top Neuroscientist to Lead Research at NYU Shanghai" (Zhong-Lin Lu)
"Studying Rodents to Understand How We Make Decisions" (Jeffrey Erlich, Liujunli Li, Joshua Mōller-Mara , Xiaoyue Zhu)
"Xinying Cai Awarded NSFC Grant" (Xinying Cai)
"Finding a Drive to Drive in Gaming" (Li Li)
"Rats Show Importance of Gradual Accumulation of Evidence in Decision-Making" (Jeffrey Erlich)
Structure of Program
Participating students complete the PhD degree requirements set by the NYU Center for Neural Science and in accordance with the academic policies of NYU GSAS. Each student develops an individualized course and research plan in consultation with the Director of Graduate Study at the NYU Center for Neural Science and the student’s NYU Shanghai faculty advisor. A typical sequence follows:
Begin program with funded research rotation, up to 3 months preceding first Fall semester, to familiarize with NYU Shanghai and faculty as well as lay a foundation for future doctoral study.
(Fall and Spring)
in New York
Complete PhD coursework at Center for Neural Science alongside other NYU PhD students.
Return to Shanghai for second funded research rotation to solidify relationships with NYU Shanghai faculty and make further progress in research.
through Year 5
Under supervision of NYU Shanghai faculty advisor, pursue dissertation research and continue coursework. Depending on each student’s individualized course of study, return visits to New York may also occur. Complete all required examinations and progress evaluations, both oral and written, leading up to submission and defense of doctoral thesis.
To learn more about the NYU Center for Neural Science PhD program degree requirements, please visit this page.
|Xingyu Ding||Computational Neuroscience, Modeling of High-Level Cognitive Function Using Biophysical Circuit Models|
|Jintao Gu||Memory and Plasticity|
|Liujunli Li||Neuroeconomics, Decision-Making, Spatial Cognition, Reinforcement Learning|
|Josh Mōller-Mara||Neuroeconomics, Probabilistic Models of Cognition, Bayesian Inference, Computational Psychiatry|
|Yalun Peng||Involvement of Orbitofrontal Cortex in Economic Decision Making|
|Chengze Xu||Decision Making|
|Xiaoyue Zhu||Neural Mechanisms of Decision-Making Using Rodents|
|Jingjie Li||Rodent Decision-Making, Sensory Processing, In Vivo Electrophysiology and Imaging, Neural Dynamics, High Performance Neuroscience Hardware|
|Hao Zhu||Motor-Sensory Transformation in Human Speech and Language, Neurophysiology, Neuroimaging, Bayesian Inference|
Application Process and Dates
Applications are to be submitted through the NYU GSAS Application portal, within which students should select the Neural Science PhD as their program of interest, and then indicate their preference for NYU Shanghai by marking the appropriate checkbox when prompted. Applicants will be evaluated by a joint admissions committee of New York and Shanghai faculty. Application requirements are set by the NYU Center for Neural Science and are the same as those for all NYU PhD applicants; however, candidates are recommended to elaborate in their application and personal statements about their specific interests in the NYU Shanghai program and faculty.
The NYU GSAS Application portal is now open for Fall 2020 admission, and the deadline is December 1, 2019. Applications are only accepted for Fall admission.
Interested students are welcome to contact Vivien Du, program coordinator of the NYU Shanghai Neural Science PhD, via email at firstname.lastname@example.org with any inquiries or to request more information.