Research

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.

SPIN Scorcerer is an automated tool for getting more and better data from speech-perception-in-noise (SPIN) experiments. Papers, code, and datasets available for download.

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.

Overview

My research explores the structured, nuanced relationships between word representations and meaning in the brain and behavior. I'm interested in how lexical (word) and semantic (meaning) 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, EEG, 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.

For more information, see my publications listed below:
Multivariate Methods for Neuroimaging | Linguistic & Nonlinguistic Categorization | Bilingualism & Language Learning | Statistical Learning | Speech Perception

Popular Press Coverage

Here are a few fun 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
Yanny or Laurel? by Rebeca Trejo, KVUE News, May 2018
Kids Put Their Minds to Brain Science by Christy Fleming, Town Square Delaware, April 2019

Scientific Publications by Topic

Multivariate Methods for Neuroimaging

Ashton, K., Zinszer, B. D., Cichy, R. M., Nelson, C. A., Aslin, R. N., & Bayet, L. Time-resolved multivariate pattern analysis of infant EEG data: A practical tutorial. Preprint under revision. https://doi.org/10.1101/2021.06.16.448720.
Bayet, L., Zinszer, B. D., Reilly, E., Cataldo, J., Pruitt, Z., Cichy, R. M., Nelson, C. A., & Aslin, R. N. (2020). Temporal dynamics of visual representations in the infant brain. Developmental Cognitive Neuroscience, 45(100860), 1-10. doi:10.1016/j.dcn.2020.100860
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. Data and code available on Github
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. Data and code available on Github
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

Categorization

Bayet, L., Zinszer, B., Pruitt, Z., Aslin, R. N., & Wu, R. (2018). Dynamics of neural representations when searching for exemplars and categories of human and non-human faces. Scientific Reports, 8(1), 13277. Data available on Figshare
Wu, R., McGee, B., Ecchiveri, C., & Zinszer, B. D. (2018). Prior knowledge of category size impacts visual search. Psychophysiology, e13075, 1-18.
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.
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.

Bilingualism & Language Learning

Zinszer, B. D., Yuan, Q., Zhang, Z., Chandrasekaran, B., & Guo, T. Comprehension under noise in L1 and L2: Acoustic entrainment of speech envelope. Preprint under revision.
Wang, D., Wang, S., Zinszer, B. D., Sheng, L., & Jasińska, K. (in press). Cross-linguistic influences of L1 on L2 morphosyntactic processing: An fNIRS study. Journal of Neurolinguistics.
Zinszer, B. D., Rolotti, S. V., Li, F., & Li, P. (2018). Bayesian word learning in multiple language environments. Cognitive Science.Data available on Github
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.

Statistical Learning

Zinszer, B. D., Hannon, J., Kouadio, A. E., Akpé, H., Tanoh, F., Hu, A., Qi, Z., & Jasińska, K. Does non-linguistic segmentation still predict literacy in an L2 education? Statistical learning in Ivorian primary schools. Stage 1 Registered Report, with In-Principle Acceptance at Language Learning. (Forthcoming special issue here)
Zinszer, B. D., Hannon, J., Kouadio, A. E., Akpé, H., Tanoh, F., Hu, A., Qi, Z., & Jasińska, K.Statistical learning and children's emergent literacy in rural Côte d'Ivoire. Preprint under revision for resubmission. https://osf.io/preprints/africarxiv/q8k5w/.
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.

Speech Perception

McHaney, J.R., Gnanateja, G.N., Smayda, K.E., Zinszer, B.D., & Chandrasekaran, B. (2020). Cortical tracking of speech in delta band relates to individual differences in speech in noise comprehension in older adults. Ear and Hearing, 42(2), 343-354.
Xie, Z., Zinszer, B. D., Riggs, M., Beevers, C. G., & Chandrasekaran, B. (in press). Impact of depression on speech perception in noise. PLoS ONE. Data available on Github
Zinszer, B. D., Riggs, M., Reetzke, R., & Chandrasekaran, B. (2019). Error patterns of native and non-native listeners’ perception of speech in noise. JASA Express Letters, 145(2), EL129-EL135. Statistical supplement, code, and data available on Github