2024
Oganesian, L., Sani, O. G., Shanechi M. M., “Spectral learning of shared dynamics between generalized-linear processes”, Neural Information Processing Systems (NeurIPS), Dec. 2024 (pdf).
Herron J., Kullmann A., Denison T., Goodman W. K., Gunduz A., Neumann W-J., Provenza N. R., Shanechi M. M., Sheth S. A., Starr P. A., Widge A. S., “Challenges and opportunities of acquiring cortical recordings for chronic adaptive deep brain stimulation”, Nature Biomedical Engineering, Dec. 2024 (link).
Robinson J. T., Norman S. L., Angle M. R., Constandinou T. G., Denison T., Donoghue J. P., Field R. M., Forsland A., Kouider S., Millan Jd. R., Michaels J. A., Orsborn A. L., Pandarinath C., Pruszynski J. A., Rozell C. J., Shah N. P., Shanechi M. M., Shoaran M., Sheth S. A., Stavisky S. D., Trautmann E., Vachicouras N., Xie C., “An application-based taxonomy for brain–computer interfaces”, Nature Biomedical Engineering, Dec. 2024 (link).
Sani, O. G., Pesaran B., Shanechi, M. M., “Dissociative and prioritized modeling of behaviorally relevant neural dynamics using recurrent neural networks”, Nature Neuroscience, Sep. 2024. (link)
USC Viterbi News | Psychology Today | Selected Journal Cover
Oganesian, L., Shanechi M. M., “Brain-computer interfaces for neuropsychiatric disorders”, Nature Reviews Bioengineering, Jun. 2024. (link)
Sadras N., Pesaran B., Shanechi M. M., “Event detection and classification from multimodal time series with application to neural data”, Journal of Neural Engineering, 21 (2), 026049, May 2024. (link) (preprint)
Ahmadipour P., Sani O. G., Pesaran B., Shanechi M. M., “Multimodal subspace identification for modeling discrete-continuous spiking and field potential population activity”, Journal of Neural Engineering,, 21 (2), 026001, Mar. 2024. (link)
Vahidi P.*, Sani O.*, Shanechi M. M., “Modeling and dissociation of intrinsic and input-driven neural population dynamics underlying behavior”, Proceedings of the National Academy of Sciences (PNAS), 121 (7), e2212887121, Feb. 2024. (link)
Abbaspourazad H.*, Erturk E.*, Pesaran B., Shanechi M. M., “Dynamical flexible inference of nonlinear latent factors and structures in neural population activity”, Nature Biomedical Engineering, 8 (1), 85–108, Jan. 2024. (link) (preprint)
USC Viterbi News | Nature Behind the Paper Story | Nature Research Briefing | Selected Journal Cover
2023
Song C. Y., Shanechi M. M., “Unsupervised learning of stationary and switching dynamical system models from Poisson observations”, Journal of Neural Engineering, 20 (6), 066029, Dec. 2023. (link)
Sadras N., Sani O. G., Ahmadipour P., Shanechi M. M., “Post-stimulus encoding of decision confidence in EEG: toward a brain-computer interface for decision making”, Journal of Neural Engineering, 20 (5), 056012, Sep. 2023. (link)
Shirvalkar P., Prosky J., Chin G., Ahmadipour P., Sani O. G., Desai M., Manning A., Dawes H., Shanechi M. M., Starr P., Chang E. F., “First-in-human prediction of chronic pain state using intracranial neural biomarkers”, Nature Neuroscience, 26, 1090–1099, May 2023. (link)
Vahidi P.*, Sani O.*, Shanechi M. M., “Modeling and dissociation of intrinsic and input-driven neural population dynamics underlying behavior”, bioRxiv, Mar. 2023. (link)
2022
Sadras N., Sani O., Ahmadipour P., Shanechi M. M., “Post-stimulus encoding of decision confidence in EEG: toward a brain-computer interface for decision making”, bioRxiv, Nov. 2022 (link).
Song C., Hsieh, H., Pesaran B., Shanechi M. M., “Modeling and Inference Methods for Switching Regime-Dependent Dynamical Systems with Multiscale Neural Observations”, Journal of Neural Engineering, Oct. 2022 (link).
Wang C., Pesaran B., Shanechi M.M., “Modeling multiscale causal interactions between spiking and field potential signals during behavior”. Journal of Neural Engineering, Jan. 2022. (link)
2021
Sani, O. G., Shanechi, M. M., “Sensory feedback can give rise to neural rotations”. eLife, Dec. 2021 (link)
Sani, O. G., Pesaran B., Shanechi, M. M., “Where is all the nonlinearity: flexible nonlinear modeling of behaviorally relevant neural dynamics using recurrent neural networks”, bioRxiv, Sep. 2021 (link)
Yang Y.*, Qiao S.*, Sani O. G., Sedillo I. J., Ferrentino B., Pesaran B., Shanechi M. M., “Modelling and prediction of the dynamic responses of large-scale brain networks during direct electrical stimulation”. Nature Biomedical Engineering, Feb. 2021. (link)
USC News | Nature Behind the Paper Story | Nature News & Views | Nature Editorial | Selected as Journal Cover
Abbaspourazad H., Choudhary M., Wong Y.T., Pesaran B., Shanechi M. M., “Multiscale low-dimensional motor cortical state dynamics predict naturalistic reach-and-grasp behavior”. Nature Communications, Jan. 2021. (link) | USC News
2020
Sani O. G., Abbaspourazad H., Wong Y.T., Pesaran B., Shanechi M. M., “Modeling behaviorally relevant neural dynamics enabled by preferential subspace identification”, Nature Neuroscience, Nov. 2020 (link)
Yang Y., Ahmadipour P., Shanechi M. M., “Adaptive latent state modeling of brain network dynamics with real-time learning rate optimization” Journal of Neural Engineering, Nov. 2020. (link)
Ahmadipour P., Yang Y., Chang E. F., Shanechi M. M., “Adaptive tracking of human ECoG network dynamics”. Journal of Neural Engineering, Aug. 2020 (link)
Abbaspourazad H., Choudhary M., Wong Y. T., Pesaran B., Shanechi M. M., “Multiscale low-dimensional neural dynamics explain naturalistic 3D movements”, Computational and Systems Neuroscience (COSYNE), Feb. 27–Mar. 1, 2020, Denver, CO. (link)
Sani O., Pesaran B., Shanechi M. M., “Modeling behaviorally relevant neural dynamics with a novel preferential subspace identification (PSID)”, Computational and Systems Neuroscience (COSYNE), Feb. 27–Mar. 1, 2020, Denver, CO. (link)
Yang Y., Qiao S., Sani O., Sedillo I., Ferrentino B., Pesaran B., Shanechi M. M., “Modeling large-scale brain network dynamics in response to electrical stimulation”, Computational and Systems Neuroscience (COSYNE), Feb. 27–Mar. 1, 2020, Denver, CO. (link)
2019
Sani, O. G., Pesaran B., Shanechi, M. M., “Modeling behaviorally relevant neural dynamics enabled by preferential subspace identification (PSID)”, bioRxiv, Oct. 2019 (link)
Shanechi M. M., “Brain-machine interfaces from motor to mood”, Nature Neuroscience, Sep. 2019 (link)
Focus on Learning and Memory Collection | Nature Editorial | USC News
Sadras N., Pesaran B., Shanechi M. M., “A point-process matched filter for event detection and decoding from population spike trains”, Journal of Neural Engineering, Aug. 2019 (link)
Yang Y.*, Sani O. G.*, Chang E. F., Shanechi M. M., “Dynamic network modeling and dimensionality reduction for human ECoG activity” Journal of Neural Engineering, May 2019 (link).
Bighamian R., Wong Y., Pesaran B., Shanechi M. M., “Sparse model-based estimation of functional dependence in high-dimensional field and spike multiscale networks”, Journal of Neural Engineering, May 2019 (link).
Abbaspourazad H., Hsieh H., Shanechi M. M., “A Multiscale Dynamical Modeling and Identification Framework for Spike-Field Activity”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Apr. 2019 (link)
Wang C., Shanechi M. M., “Estimating Multiscale Direct Causality Graphs in Neural Spike-Field Networks”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Mar. 2019 (link)
Yang Y., Guidera J., Vlasov K., Pei J., Brown E.N., Solt K., Shanechi M. M., “Developing a personalized closed-loop controller of medically-induced coma in a rodent model” Journal of Neural Engineering, Mar. 2019 (link)
Song C., Hsieh H., Shanechi M. M., “Decoder for switching state-space models with spike-field observations”, International IEEE EMBS Conference On Neural Engineering (NER), 20–23 Mar. 2019, San Francisco, CA. (link)
Ahmadipouranari P., Yang Y., Shanechi M. M., “Investigating the effect of forgetting factor on tracking non-stationary neural dynamics”, International IEEE EMBS Conference On Neural Engineering (NER), 20–23 Mar. 2019, San Francisco, CA. (link)
2018
Papers
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., Chang E.F., “Direct Electrical Stimulation of Lateral Orbitofrontal Cortex Acutely Improves Mood in Individuals with Symptoms of Depression”, Current Biology, Nov. 2018 (link).
Hsieh H, Wong Y, Pesaran B, Shanechi M.M., “Multiscale Modeling and Decoding Algorithms for Spike-Field Activity”, Journal of Neural Engineering, Oct. 2018 (link)
Sani O. G.*, Yang Y.*, Lee M. B., Dawes H. E., Chang E.F., Shanechi M. M., “Mood variations decoded from multi-site intracranial human brain activity”, Nature Biotechnology, Sep. 2018 (link)
USC News | Nature Behind the Paper Story | Select Media Excerpts: NewScientist, The Wall Street Journal, New Atlas, IEEE Spectrum | Selected as Journal Cover
Yang Y., Connolly A. T., Shanechi M. M., “A control-theoretic system identification framework and a real-time closed-loop clinical simulation testbed for electrical brain stimulation.” Journal of Neural Engineering 15:066007, Sep. 2018 (link)
Select Media: Science News, IEEE Spectrum
Hsieh H., Shanechi M. M., “Optimizing the Learning Rate for Adaptive Estimation of Neural Encoding Models”, PLoS Computational Biology 14(5): e1006168, May 2018 (link)
Abbaspourazad H., Wong Y., Pesaran B., Shanechi M. M., “Identifying Multiscale Hidden States to Decode Behavior”, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Honolulu, HI, 2018.
Bighamian R., Shanechi M. M., “Estimation of Functional Dependence in High-Dimensional Spike-Field Activity”, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Honolulu, HI, 2018.
Sadras, N., Shanechi M. M., “Decoding Spike Trains from Neurons with Spatio-Temporal Receptive Fields”, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Honolulu, HI, 2018.
Wang C., Shanechi M.M., “An Information-Theoretic Measure of Multiscale Causality for Spike-Field Activity”, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Honolulu, HI, 2018.
Abstracts
Hsieh, H., Wong Y.T., Pesaran B., Shanechi M. M., “Multiscale modeling and decoding of spike-field activity during a naturalistic reach-to-grasp task”, Computational and Systems Neuroscience (Cosyne), 1–4 Mar. 2018, Denver, CO.
Yang Y., Sani O., Sellers K.K., Chang E. F., Shanechi M. M., “A novel framework for dynamic modeling of brain-network response to electrical stimulation”, Computational and Systems Neuroscience (Cosyne), 1–4 Mar. 2018, Denver, CO.
Sani O., Yang Y., Lee M., Dawes H., Chang E. F., Shanechi M. M., “Decoding mood state from multisite ECoG activity in human subjects”, Computational and Systems Neuroscience (Cosyne), 1–4 Mar. 2018, Denver, CO.
2017
Book Chapter
Shanechi M. M., “Brain-machine interfaces”, Dynamic Neuroscience, Ed. S. Sarma, Ed. Z. Chen, Springer International Publishing.
Papers
Shanechi M.M., Orsborn A.L., Moorman H., Gowda S., Dangi S, Carmena J.M., “Rapid control and feedback rates enhance neuroprosthetic control”, Nature Communications, 8:13825, Jan. 2017 (link)
Shanechi M.M., “Brain-machine interface control algorithms”, IEEE Transactions on Neural Systems and Rehabilitation Engineering 25(10):1725 – 1734, 2017 (link)
Abbaspourazad H., Shanechi M. M., “Multiscale modeling of dependencies between spikes and fields”, in Proceedings of Asilomar Conference on Signals, Systems, and Computers, 29–31 Oct. 2017, Pacific Grove, CA. (link)
Yang Y., Chang E.F., Shanechi M.M., “Dynamic tracking of non-stationarity in human ECoG activity”, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Jeju Island, Korea, 2017 (link)
Hsieh H., Wong Y.T., Pesaran B., Shanechi M.M., “Multiscale decoding for reliable brain-machine interface performance over time”, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Jeju Island, Korea, 2017 (link)
Abbaspourazad H., Shanechi M.M., “An unsupervised learning algorithm for multiscale neural activity”, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Jeju Island, Korea, 2017 (link)
Abstracts
Hsieh, H., Wong Y.T., Pesaran B., Shanechi M. M., “Multiscale decoding of spike-field activity to improve brain-machine interface robustness and longevity”, Annual Meeting, Society for Neuroscience (SFN), 11–15 Nov. 2017, Washington, DC.
Abbaspourazad H., Shanechi M. M., “Learning the dependencies between spikes and fields in multiscale modeling”, Annual Meeting, Society for Neuroscience (SFN), 11–15 Nov. 2017, Washington, DC.
Yang Y., Sellers K.K., Chang E. F., Shanechi M. M., “Modeling dynamic brain network responses to electrical stimulation”, Annual Meeting, Society for Neuroscience (SFN), 11–15 Nov. 2017, Washington, DC.
Sani O., Yang Y., Chang E. F., Shanechi M. M., “Real-time decoding of mood from human large-scale ECoG activity”, Annual Meeting, Society for Neuroscience (SFN), 11–15 Nov. 2017, Washington, DC.
2016
Papers
Yang Y., Shanechi M.M., “An adaptive and generalizable closed-loop system for control of medically-induced coma and other states of anesthesia”, Journal of Neural Engineering, 13(6):066019, Nov. 2016 (link)
Shanechi M.M., Orsborn A.L., Carmena J.M., “Robust brain-machine interface design using optimal feedback control modeling and adaptive point process filtering”, PLoS Computational Biology 12(4): e1004730, Apr. 2016. (link).
Yang Y., Shanechi M.M., “Time-Efficient Identification of Input-Output Brain Dynamics“, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Orlando, FL, 2016 (link)
Hsieh H., Shanechi M.M, “Multiscale Brain-Machine Interface Decoders“, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Orlando, FL, 2016 (link)
Abstracts
Abbaspourazad H., Shanechi M.M., “A new modeling framework for multiscale neural activity underlying behavior”, Society for Neuroscience (SFN), San Diego, CA, 2016,
Hsieh, H., Shanechi M.M., “Adaptive multiscale brain-machine interface decoders”, Society for Neuroscience (SFN), San Diego, CA, 2016
Yang Y., Shanechi M.M., “Adaptive identification of high-dimensional brain network dynamics to track non-stationarity and plasticity”, Society for Neuroscience (SFN), San Diego, CA, 2016
2015
Papers
Yang Y., Shanechi M.M., “A framework for identification of brain network dynamics using a novel binary noise modulated electrical stimulation pattern”, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Milan, Italy, 2015 (link)
– Top three winners of the IEEE EMBC student paper competition (link)
Hsieh H., Shanechi M.M, “Optimal calibration of the learning rate in closed-loop adaptive brain-machine interfaces”, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Milan, Italy, 2015 (link)
Yang Y., Shanechi M.M., “A generalizable adaptive brain-machine interface architecture for closed-loop control of anesthesia”, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Milan, Italy, 2015 (link)
Abstracts
Connolly A., Yang Y., Chang E.F., Shanechi M.M., “Modeling brain network dynamics underlying mood disorders”, Society for Neuroscience (SFN), Chicago, Il., 2015
Yang Y., Connolly A., Shanechi M.M., “A novel binary noise modulated electrical stimulation pattern for identification of brain network dynamics”, Society for Neuroscience (SFN), Chicago, Il., 2015
Hsieh, H., Shanechi M.M., “A general framework for optimal selection of the learning rate in closed-loop brain-machine interfaces”, Society for Neuroscience (SFN), Chicago, Il., 2015
Shanechi M.M., Orsborn A.L., Moorman H., Gowda S., Dangi S, Carmena J.M., “Rapid sensorimotor control and feedback rates enhance neuroprosthetic control”, Cell Symposia: Engineering the Brain, Chicago, Il., 2015
Yang Y., Shanechi M.M., “An adaptive and robust brain-machine interface architecture for closed-loop control of anesthesia”, International Anesthesia Research Society (IARS) meeting, Honolulu, HI, 2015.
2014
Papers
Orsborn A. L., Mooreman H. G., Overduin S. A., Shanechi M. M., Dimitrov D. F., Carmena J. M., “Closed-loop decoder adaptation shapes neural plasticity for skillful neuroprosthetic control”, Neuron 82(6), Jun. 2014. (link)
Dangi S., Gowda S., Moorman H.G., Orsborn A.L., So K., Shanechi M. M., Carmena J.M., “Continuous closed-loop decoder adaptation with a recursive maximum likelihood algorithm allows for rapid performance acquisition in brain-machine interfaces”, Neural Computation, 26:9, Sep. 2014. (link)
Shanechi M. M., Hu R., Williams, Z.M., “A cortical-spinal prosthesis for targeted limb movement in paralyzed primate avatars”, Nature Communications, 5:3237, Feb. 2014 (pdf) (link)
-Select Media Highlights: Cornell Chronicle, BBC News, Le Monde
Yang Y., Shanechi M.M., “An adaptive brain-machine interface algorithm for control of burst suppression in medical coma”, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Chicago, Il, 2014 (link)
Shanechi M.M., Orsborn A.L., Moorman H., Gowda S., Carmena J.M., “High-performance brain-machine interface enabled by an adaptive optimal feedback-controlled point process decoder”, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Chicago, Il., 2014 (link)
Chang Y. H., Chen M., Shanechi M. M., Carmena J. M., Tomlin C., “A design of neural decoder by reducing discrepancy between manual control and brain control”, in Proceedings of European Control Conference (ECC), Strasbourg, France, 2014 (link)
Abstracts
Shanechi M.M., Orsborn A.L., Moorman H., Gowda S., Dangi S., Carmena J.M., “Spike-by-spike control using an adaptive optimal feedback-controlled point process decoder improves BMI performance”, Society for Neuroscience (SFN), Washington DC, 2014
Shanechi M. M., Chemali J., Liberman M., Solt K., Brown E. N., “Control of burst-suppression in a rodent model of medical coma using a brain-machine interface”, International Anesthesia Research Society (IARS) meeting, Montreal, Canada, 2014.
-Best paper award in Technology, Computation, and Simulation
2013
Papers
Shanechi M. M., Chemali J., Liberman M., Solt K., Brown E. N. “A brain-machine interface for control of medically-induced coma”, PLOS Computational Biology, 9(10), Oct. 2013 (pdf) (link)
-Select Media Highlights: Cornell Chronicle, MIT News, NBC News
Shanechi M. M., Williams Z. M., Wornell G. W., Hu R. C., Powers M., Brown E. N. “A real-time brain-machine interface combining motor target and trajectory intent using an optimal feedback control design”, PLOS ONE 8 (4), Apr. 2013. (pdf) (link)
Shanechi M. M., Carmena J. M. “Optimal feedback-controlled point process decoder for adaptation and assisted training in brain-machine interfaces”, in Proceedings of IEEE international conference on neural engineering (NER), San Diego, CA, 2013 (link)
Shanechi M. M., Orsborn A., Gowda S., Carmena J. M. “Proficient BMI control enabled by closed-loop adaptation of an optimal feedback-controlled point process decoder”, in Translational and Computational Motor Control (TCMC) Meeting, San Diego, CA, 2013
Shanechi M. M., Chemali J., Liberman M., Solt K., Brown E. N. “A brain-machine interface for control of burst suppression in medical coma”, in Proceedings of IEEE Engineering in Medicine and Biology Society (EMBC) Conference, Osaka, Japan, 2013 (link)
Abstracts
Shanechi M. M., Chemali J., Liberman M., Solt K., Brown E. N. “A brain-machine interface for control of medically-induced coma”, in Computational and Systems Neuroscience (COSYNE) Meeting, Salt Lake City, 2013.
Shanechi M. M., Chemali J., Liberman M., Solt K., Brown E. N. “A brain-machine interface for control of medically-induced coma”, Society for Neuroscience (SFN), San Diego, CA, 2013
2012
Papers
Shanechi M. M., Hu R., Powers M., Wornell G. W., Brown E. N., Williams Z. M. “Neural population partitioning and a concurrent brain-machine interface for sequential motor function”, Nature Neuroscience, 15 (12), Dec. 2012. (pdf) (link)
– Nature Research Highlight: “Brain–machine does the two-step”, Nature, 491 (305), Nov. 2012 (pdf) (link)
Shanechi M. M., Wornell G. W., Williams Z. M., Brown E. N. “Feedback-controlled parallel point process filter for estimation of goal-directed movements from neural signals”, IEEE Trans. on Neural Syst. Rehabil. Eng., Oct. 2012. (pdf) (link)
Abstracts
Shanechi M. M., Hu R., Powers M., Wornell G. W., Brown E. N., Williams Z. M. “A concurrent brain-machine interface for enhanced motor function”, in Computational and Systems Neuroscience (COSYNE), Salt Lake City, USA, 2012
2011 and earlier
Papers
Shanechi M. M., Porat R., Erez U. “Comparison of practical feedback algorithms for multiuser MIMO”, IEEE Transactions on Communications, 58 (8), Aug. 2010. (pdf) (link)
Shi G., Shanechi M. M., Aarabi, P. “On the importance of phase in human speech recognition”, IEEE Transactions on Audio, Speech and Language Processing, 14 (5), Sep. 2006. (pdf) (link)
Mavandadi S., Aarabi P., Mohajer K., Shanechi M. M. “Post recognition speech localization”, International Journal of Speech Technology, 8 (2), Jun. 2005.
Shanechi M. M., Wornell G. W., Williams Z. M., Brown E. N. “A parallel point-process filter for estimation of goal-directed movements from neural signals”, in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), (Dallas, USA, 2010) (pdf) (link)
Shanechi M. M., Porat R., Erez U. “Comparison of practical feedback algorithms for multiuser MIMO”, in Proceedings of IEEE Vehicular Technology Conference (VTC), (Barcelona, Spain, 2009) (pdf)
Shanechi M. M., Erez U., Wornell G. W. “Rateless codes for MIMO channels”, in Proceedings of IEEE Global Communications Conference (GLOBECOM), (New Orleans, USA, 2008) (pdf) (link)
Shanechi M. M., Erez U., Wornell G. W. “Time-invariant rateless codes for MIMO channels”, in Proceedings of IEEE International Symposium on Information Theory (ISIT), (Toronto, Canada, 2008) (pdf) (link)
Shanechi M. M., Erez U., Wornell G. W. “Universal coding for parallel Gaussian channels”, in Proceedings of IEEE International Zurich Seminar on Communications (ETH), (Zurich, Switzerland, 2008) (pdf) (link)
Shanechi M. M., Aarabi P.: “Structural analysis of multisensor arrays for speech separation applications”, in Proceedings of Sensor Fusion: Architectures, Algorithms, and Applications VII, (Orlando, USA, 2003)
Abstracts
Shanechi M. M., Hu R., Powers M., Wornell G. W., Brown E. N., Williams Z. M. “A real-time concurrent brain-machine interface for performing sequential movements”, in 41st Annual Meeting, Society for Neuroscience (SFN), Washington, USA, 2011
Shanechi M. M., Hu R., Powers M., Wornell G. W., Brown E. N., Williams Z. M. “A brain-machine interface combining target and trajectory information using optimal feedback control”, in Computational and Systems Neuroscience (COSYNE) Meeting, Salt Lake City, USA, 2011.
Shanechi M. M., Williams Z. M., Wornell G. W., Brown E. N. “Combining plan and peri-movement activities improves the performance of brain-machine interfaces”, in 40th Annual Meeting, Society for Neuroscience (SFN), San Diego, USA, 2010
Shanechi M. M., Williams Z. M., Wornell G. W., Brown E. N. “A real-time brain-machine interface combining plan and peri-movement activities”, in Research in Encoding And Decoding of Neural Ensembles Conference (AREADNE), Santorini, Greece, 2010
Thesis
Shanechi M. M. “Real-time brain-machine interface architectures: neural decoding from plan to movement”, PhD Dissertation, MIT, April 2011. (pdf)
Book
Aarabi P., Shi G., Shanechi M. M., Rabi S., “Phase-based speech processing”, World Scientific, 2006.