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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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Posts
Blog Post number 4
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Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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portfolio
Multimodal Neural Recording: fMRI-EEG-TMS (fET) System
We developed a functional magnetic resonance imaging (fMRI)-electroencephalogram (EEG)-transcranial magnetic stimulation (TMS) instrument (fET instrument) capable of acquiring simultaneous fMRI and EEG during noninvasive single pulse TMS. We used this instrument to apply single-pulse TMS to the left DLPFC and test whether prefrontal EEG alpha phase moderates TMS-evoked top-down influences on subgenual, rostral and dorsal ACC. 
Portfolio item number 2
Short description of portfolio item number 2
publications
Delay discounting and neurocognitive correlates among inner city adolescents with and without family history of substance use disorder
Rodriguez-Moreno, D. V., Cycowicz, Y. M., Figner, B., Wang, Z., He, X., Geronazzo-Alman, Sun, X., Cheslack-Postava, K., Bisaga, A., Hoven, C.W., & Amsel, L.V. (2021). Delay discounting and neurocognitive correlates among inner city adolescents with and without family history of substance use disorder. Developmental cognitive neuroscience, 48, 100942.
Daily prefrontal closed-loop repetitive transcranial magnetic stimulation (rTMS) produces progressive EEG quasi-alpha phase entrainment in depressed adults
Faller, J.*, Doose, J.*, Sun, X.*, Mclntosh, J. R., Saber, G. T., Lin, Y., ... & Sajda, P. (2022). Daily prefrontal closed-loop repetitive transcranial magnetic stimulation (rTMS) produces progressive EEG quasi-alpha phase entrainment in depressed adults. Brain stimulation, 15(2), 458-471.
The timing of transcranial magnetic stimulation relative to the phase of prefrontal alpha EEG modulates downstream target engagement
Pantazatos, S. P.*, Mclntosh, J. R.*, Saber, G. T.*, Sun, X., Doose, J., Faller, J., ... & Brown, T. R. (2023). The timing of transcranial magnetic stimulation relative to the phase of prefrontal alpha EEG modulates downstream target engagement. Brain Stimulation, 16(3), 830-839.
Neurophysiological markers of emotion regulation predict efficacy of entrepreneurship education
Egana-delSol, P., Sun, X., & Sajda, P. (2023). Neurophysiological markers of emotion regulation predict efficacy of entrepreneurship education. Scientific Reports, 13(1), 7206.
A non-canonical striatopallidal Go pathway that supports motor control
Labouesse, M., Torres-Herraez, A., Chohan, M., Villarin, J., Greenwald, J., Sun, X., ... & Kellendonk, C. (2023). A non-canonical striatopallidal Go pathway that supports motor control. Nature Communications, 14, 6712.
EEG synchronized left prefrontal transcranial magnetic stimulation (TMS) for treatment resistant depression is feasible and produces an entrainment dependent clinical response: a randomized controlled double blind clinical trial
George, M. S., Huffman, S., Doose, J., Sun, X., Dancy, M., Faller, J., ... & Brown, T. (2023). EEG synchronized left prefrontal transcranial magnetic stimulation (TMS) for treatment resistant depression is feasible and produces an entrainment dependent clinical response: a randomized controlled double blind clinical trial. Brain Stimulation, 16(6), 1753-1763.
Uncovering invariant representations in functional neuroimaging with deep metric learning
Mittal, A., Sun, X., Paisley, J., & Sajda, P. (2023). Uncovering invariant representations in functional neuroimaging with deep metric learning. bioRxiv, 2023-09.
Increased entrainment and decreased excitability predict efficacious treatment of EEG-synchronized rTMS for treatment-resistant depression patients
Sun, X., Doose, J., Faller, J., McIntosh, J., Saber, G. T., Huffman, S., ... & Sajda, P. (2023). Increased entrainment and decreased excitability predict efficacious treatment of closed-loop phase-locked rTMS for treatment-resistant depression. medRxiv, 2023-10.
Fixating on attention: integrating human eye tracking into vision transformers
Koorathota, S.*, Papadopoulos, N.*, Ma, J. L., Kumar, S., Sun, X., Mittal, A., Adelman, P., & Sajda, P. (2023). Fixating on attention: integrating human eye tracking into vision transformers. arXiv preprint arXiv:2308.13969.
Circular clustering with polar coordinate reconstruction
Sun, X., & Sajda, P. (2024). Circular clustering with polar coordinate reconstruction. IEEE/ACM Transactions on Computational Biology and Bioinformatics.
Racial, ethnic, and socioeconomic disparities in Covid-19 pandemic worries
Hoven, C. W., Krasnova, A., Bresnahan, M., Sun, X., Musa, G., Geronazzo-Alman, L., ... & Cheslack-Postava, K. (2024). Racial, ethnic, and socioeconomic disparities in Covid-19 pandemic worries. Journal of racial and ethnic health disparities, 1-9.
talks
teaching
Signal Modeling (BMEN E4420), Spring2022
Teaching Assistant, Columbia University, Department of Biomedical Engineering, 2022
Description: Fundamental concepts of signal processing in linear systems and stochastic processes. Estimation, detection and filtering methods applied to biomedical signals. Harmonic analysis, auto-regressive model, Wiener and Matched filters, linear discriminants, and independent components. Methods are developed to answer concrete questions on specific data sets in modalities such as ECG, EEG, MEG, Ultrasound. Lectures accompanied by data analysis assignments using MATLAB (more information).
Biostatistics (BMEN E4110), Fall2022
Teaching Assistant, Columbia University, Department of Biomedical Engineering, 2022
Description: Fundamental concepts of probability and statistics applied to biology and medicine. Probability distributions, hypothesis testing and inference, summarizing data and testing for trends. Signal detection theory and the receiver operator characteristic. Lectures accompanied by data analysis assignments using MATLAB as well as discussion of case studies in biomedicine (more information).
Signal Modeling (BMEN E4420), Spring2023
Teaching Assistant, Columbia University, Department of Biomedical Engineering, 2023
Description: Fundamental concepts of signal processing in linear systems and stochastic processes. Estimation, detection and filtering methods applied to biomedical signals. Harmonic analysis, auto-regressive model, Wiener and Matched filters, linear discriminants, and independent components. Methods are developed to answer concrete questions on specific data sets in modalities such as ECG, EEG, MEG, Ultrasound. Lectures accompanied by data analysis assignments using MATLAB (more information).