Software & Tools
See my Github profile.
Team MCPA hosts our latest work in MVPA / multichannel pattern analysis for fNIRS. We release fNIRS data and analysis code with each publication to promote replicability and encourage methodological advancements in fNIRS.
Infant MVPA with fNIRS - (Download at Github) Software package for multichannel pattern analysis of fNIRS data. Manuscript at PLoS ONE or see CNS 2016 poster for a preview.
Connectivity Modeling Tutorial - (Download pdf) Tutorial on performing effective connectivity modeling with the euSEM model and GIMME software. You can also download the full GIMME manual by Kathleen Gates and Peter Molenaar. GIMME package for Matlab available on NITRC.
My research explores a particular kind of organized (or structured) knowledge: the links between lexical (word) representations and semantic (meaning) representations. I'm interested in how these systems differ and interact across different languages, especially for bilinguals who not only learn two languages' worth of information, but also deal with conflicts between the ways these languages organize the world. This work includes bilinguals at all levels of proficiency and people who are just starting to learn a language. I use a combination of behavioral methods, computer simulations, and neuroimaging technology (such as MRI and near-infrared spectroscopy) to probe the highly dynamic and interactive cognitive and neural systems that represent linguistic knowledge in humans who speak one, two, or many languages.
Here are a couple of fun popular press pieces related to my research that I've contributed to:
- Making Language Research Less Alien: The Science of Arrival by Lisa M.P. Munoz, Cognitive Neuroscience Society, December 2016
- Bilingual Power by Mary Stone, POST, Summer 2017
For more information, see my publications listed below or visit the websites of my collaborators' labs
- Rochester Baby Lab, University of Rochester
- Raizada Lab, University of Rochester
- Princeton Baby Lab, Princeton University
- Calla Lab, University of California, Riverside
- Brain, Language, and Computation Lab, Penn State University
- Language and Thought Lab, Lehigh University
- Comparative Communication Lab, Penn State University
- Wang Lab, Department of Psychology, South China Normal University
- State Key Lab for Cognitive Neuroscience and Learning, Beijing Normal University
- Guangwai Brain and Language Lab, Guangdong University of Foreign Studies
Publications by Topic
- Zinszer, B. D., Anderson, A. J., Kang, O., Wheatley, T., & Raizada, R. D. S. (2016). Semantic structural alignment of neural representational spaces enables translation between English and Chinese words. Journal of Cognitive Neuroscience, 28(11), 1749-1759. doi:10.1162/jocn_a_01000
- Fang, S., Zinszer, B. D., Malt, B., & Li, P. (2016). Bilingual object naming: A connectionist model. Frontiers in Psychology. doi:10.3389/fpsyg.2016.00644.
- Zinszer, B. D., Malt, B., Ameel, E., & Li, P. (2014). Native-likeness in second language lexical categorization reflects individual language history and linguistic community norms. Frontiers in Psychology, 5(01203). doi:10.3389/fpsyg.2014.01203.
Multivariate Methods for Neuroimaging
- Zinszer, B. D., Bayet, L., Emberson, L. E., Raizada, R. D. S., & Aslin, R. N. (2018). Decoding semantic representations from fNIRS signals. Neurophotonics, 5(1), 011003. doi:10.1117/1.NPh.5.1.011003
- Emberson, L., Zinszer, B. D., Raizada, R. D. S., & Aslin, R. (2017) Decoding the infant mind: Multivariate pattern analysis (MVPA) using fNIRS. PLoS ONE, 12(4): e0172500. doi:10.1371/journal.pone.0172500
- Anderson, A. J., Zinszer, B. D., & Raizada, R. (2016). Representational similarity encoding for fMRI: Pattern-based synthesis to predict brain activity using stimulus-model-similarities. Neuroimage, 128, 44-53. doi:10.1016/j.neuroimage.2015.12.035
- Wu, R., Pruitt, Z., Zinszer, B., & Cheung, O. (2017). Increased experience amplifies the activation of task-irrelevant category representations. Attention, Perception, and Psychophysics, 79(2), 522-532.
Bilingualism & Language Learning
- Zinszer, B. D., Rolotti, S. V., & Li, P. (under revision) Bayesian word learning in multiple language environments.
- Zinszer, B. D., Chen, P., Wu, H., Shu, H., & Li, P. (2015). Second language experience modulates neural specialization for L1 lexical tones. Journal of Neurolinguistics, 33, 50-66. doi:10.1016/j.jneuroling.2014.09.005
- Zou, L., Abutalebi, J., Zinszer, B., Yan, X., Shu, H., Peng, D., & Ding, G. (2012). Second language experience modulates functional brain network for the native language production in bimodal bilinguals. Neuroimage, 62(3), 1367-75.
- Zinszer, B. D. & Li, P. (2010). A SOM model of first language lexical attrition. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
- Karuza, E., Li, P., Weiss, D. J., Bulgarelli, F., Zinszer, B. D., & Aslin, R. (2016). Sampling over non-uniform distributions: A neural efficiency account of the primacy effect in statistical learning. Journal of Cognitive Neuroscience, 28(10), 1484-1500. doi:10.1162/jocn_a_00990.
- Zinszer, B. D. & Weiss, D. J. (2013). When to hold and when to fold: Detecting structural changes in statistical learning. Proceedings of the 35th Annual Conference of the Cognitive Science Society.