My Google Scholar page is https://scholar.google.com/citations?user=drvJ7vsAAAAJ&hl=en
JOURNAL ARTICLES
J11. Fang, H., Yang, Y.#, 2022. Designing and Validating a Robust Adaptive Neuromodulation Algorithm for Closed-Loop Control of Brain States. Journal of neural engineering, 19(3), p.036018. (link)
J10. Yang, Y.*, Qiao, S.*, Sani, O.G., Sedillo J.I., Ferrentino, B., Pesaran, B., and Shanechi, M.M., 2021, Modelling and prediction of the dynamic responses of large-scale brain networks during direct electrical stimulation. Nature Biomedical Engineering, 1-22. (* equal contribution) (link).
– Selected as journal cover article.
– Selected Media Highlights: UCF Today, NBME News, USC News
J9. Yang, Y.*, Ahmadipour, P.*, and Shanechi, M.M., 2021. Adaptive latent state modeling of brain network dynamics with real-time learning rate optimization. Journal of neural engineering, 18(3), p.036013. (* equal contribution)
J8. Ahmadipour, P.*, Yang, Y.*, Chang, E.F. and Shanechi, M.M., 2021. Adaptive tracking of human ECoG network dynamics. Journal of neural engineering, 18(1), p.016011. (* equal contribution)
J7. Sani, O.*, Yang, Y*., Lee, M., Sellers, K., Dawes, H., Chang, E. and Shanechi, M., 2020. Neural Decoding and Control of Mood to Treat Neuropsychiatric Disorders. Biological Psychiatry, 87(9), pp.S95-S96. (* equal contribution)
J6. Yang, Y., Lee, J.T., Guidera, J.A., Vlasov, K.Y., Pei, J., Brown, E.N., Solt, K. and Shanechi, M.M., 2019. Developing a personalized closed-loop controller of medically-induced coma in a rodent model. Journal of neural engineering, 16(3), p.036022.
J5. Yang, Y.*, Sani, O.G.*, Chang, E.F. and Shanechi, M.M., 2019. Dynamic network modeling and dimensionality reduction for human ECoG activity. Journal of neural engineering, 16(5), p.056014. (* equal contribution)
J4. Sani, O.G.*, Yang, Y.*, Lee, M.B., Dawes, H.E., Chang, E.F. and Shanechi, M.M., 2018. Mood variations decoded from multi-site intracranial human brain activity. Nature Biotechnology, 36(10), p.954. (* equal contribution)
– Selected as journal cover article.
– Selected Media Highlights: The Wall Street Journal, New Scientist, Science News, New Atlas, IEEE Spectrum.
J3. Yang, Y., Connolly, A.T. and Shanechi, M.M., 2018. A control-theoretic system identification framework and a real-time closed-loop clinical simulation testbed for electrical brain stimulation. Journal of neural engineering, 15(6), p.066007.
– Selected Media Highlights: Science News, IEEE Spectrum.
J2. Rao, V.R., Sellers, K.K., Wallace, D.L., Lee, M.B., Bijanzadeh, M., Sani, O.G., Yang, Y., Shanechi, M.M., Dawes, H.E. and Chang, E.F., 2018. Direct electrical stimulation of lateral orbitofrontal cortex acutely improves mood in individuals with symptoms of depression. Current Biology, 28(24), pp.3893-3902.
J1. Yang, Y. and Shanechi, M.M., 2016. An adaptive and generalizable closed-loop system for control of medically induced coma and other states of anesthesia. Journal of neural engineering, 13(6), p.066019.
JOURNAL MANUSCRIPTS IN SUBMISSION
J-S1. Fang, H. and Yang, Y.#, 2022. Designing and Validating a Robust Adaptive Brain-Machine Interface Algorithm for Closed-Loop Control of Brain States. (In review， # corresponding author)
J-S2. Yang, Y., Kristin, S.K., Sani, O.G., Bijanzadeh, M., Chang, E.F. and Shanechi, M.M., 2022. Dynamic Prediction of Multi-site Human ECoG Activity in Response to Electrical Brain Stimulation. (In submission)
CONFERENCE PROCEEDINGS
C7. Fang, H. and Yang, Y.#, 2021, November. A Robust and Adaptive Control Algorithm for Closed-Loop Brain Stimulation. In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 6049-6052). IEEE. (# corresponding author)
C6. CAhmadipour, P., Yang, Y. and Shanechi, M.M., 2019, March. Investigating the effect of forgetting factor on tracking non-stationary neural dynamics. In 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) (pp. 291-294). IEEE.
C5. Yang, Y., Chang, E.F. and Shanechi, M.M., 2017, July. Dynamic tracking of non-stationarity in human ECoG activity. In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 1660-1663). IEEE.
C4. Yang, Y. and Shanechi, M.M., 2016, August. Generalized binary noise stimulation enables time-efficient identification of input-output brain network dynamics. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 1766-1769). IEEE.
C3. Yang, Y. and Shanechi, M.M., 2015, August. A framework for identification of brain network dynamics using a novel binary noise modulated electrical stimulation pattern. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 2087-2090). IEEE.
— Top three winners of 2015 EMBS Student Paper Competition.
C2. Yang, Y. and Shanechi, M.M., 2015, August. A generalizable adaptive brain-machine interface design for control of anesthesia. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 1099-1102). IEEE.
C1. Yang, Y. and Shanechi, M.M., 2014, August. An adaptive brain-machine interface algorithm for control of burst suppression in medical coma. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 1638-1641). IEEE.
BOOK CHAPTERS
B3. Yang, Y.,* Sani, O.G.*, Lee, M.B., Dawes, H.E., Chang, E.F. and Shanechi, M.M., 2021, Developing a Closed-Loop Brain-Computer Interface for Treatment of Neuropsychiatric Disorders Using Electrical Brain Stimulation. Brain-Computer Interface Research: A State-of-the-Art Summary 9, p.103. Eds. Guger C., Mrachacz-Kersting N., Allison B. Springer, Cham. (* equal contribution)
B2. Sani, O.G.*, Yang, Y.* and Shanechi, M.M., 2021, Closed-Loop BCI for the Treatment of Neuropsychiatric Disorders. Brain-Computer Interface Research: A State-of-the-Art Summary 9, Springer, Cham. (* equal contribution)
B1. Sani, O.G.*, Yang, Y.* and Shanechi, M.M., 2021, Brain-Machine Interfaces for Closed-Loop Electrical Brain Stimulation in Neuropsychiatric Disorders. Handbook of Neuroengineering, Springer, Singapore. (* equal contribution)
CONFERENCE ABSTRACTS AND PRESENTATIONS
A12. Fang, H., Berman, S., and Yang, Y.#, 2021. Design and validation of a robust and adaptive brain-machine interface algorithm for control of brain states. Annual Meeting, Society for Neuroscience (SfN), Chicago, IL.
A11. Yang, Y.*, Qiao, S.*, Sani, O.G., Sedillo J.I., Ferrentino, B., Pesaran, B., and Shanechi, M.M., 2019. Accurate prediction of large-scale LFP network dynamics in response to electrical stimulation. Annual Meeting, Society for Neuroscience (SfN), Chicago, IL.
A10. Yang, Y.*, Ahmadipour, P.*, and Shanechi, M.M., 2019. Adaptive modeling of neural network dynamics with optimized learning rate. Annual Meeting, Society for Neuroscience (SfN), Chicago, IL.
A9. Yang, Y., Lee, J.T., Guidera, J.A., Vlasov, K.Y., Pei, J., Brown, E.N., Solt, K. and Shanechi, M.M., 2019. A Personalized Closed-Loop System for Control of EEG under Medically-Induced Coma. Annual Meeting, Society for Neuroscience (SfN), San Diego, CA.
A8. Yang, Y., Sani, O.G., Kristin, S.K., Chang, E.F. and Shanechi, M.M., 2018. A novel framework for dynamic modeling of brain-network response to electrical stimulation. Annual Computational and Systems Neuroscience (Cosyne) Meeting, Denver, CO
A7. Sani, O.G., Yang, Y., Lee, M.B., Dawes, H.E., Chang, E.F. and Shanechi, M.M., 2018. Decoding mood state from multisite ECoG activity in human subjects, Annual Computational and Systems Neuroscience (Cosyne) Meeting, Denver, CO
A6. Yang, Y., Sani, O.G., Kristin, S.K., Chang, E.F. and Shanechi, M.M., 2017. Modeling dynamic brain-network responses to electrical stimulation. Annual Meeting, Society for Neuroscience (SfN), Washington, D.C.
A5. Sani, O.G., Yang, Y., Chang, E.F. and Shanechi, M.M., 2017. Real-time decoding of mood from human large-scale ECoG activity. Annual Meeting, Society for Neuroscience (SfN), Washington, D.C.
A4. Yang, Y., Chang, E.F. and Shanechi, M.M., 2016. Adaptive identification of high-dimensional brain network dynamics to track nonstationarity and plasticity. Annual Meeting, Society for Neuroscience (SfN), San Diego, CA.
A3. Yang, Y., Connolly, A.T. and Shanechi, M.M., 2015. A novel binary noise modulated electrical stimulation pattern for identification of brain network dynamics. Annual Meeting, Society for Neuroscience (SfN), Chicago, IL.
A2. Connolly, A.T., Yang, Y., Chang, E.F. and Shanechi, M.M., 2015. Modeling brain network dynamics underlying mood disorders. Annual Meeting, Society for Neuroscience (SfN), Chicago, IL.
A1. Yang, Y. and Shanechi, M.M., 2015. An adaptive and robust brain-machine interface architecture for closed-loop control of anesthesia. Annual International Anesthesia Research Society (IARS) meeting, Honolulu, HI.