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pro vyhledávání: '"MILLER, LEE A."'
Each year, millions of individuals lose the ability to speak intelligibly due to causes such as neuromuscular disease, stroke, trauma, and head/neck cancer surgery (e.g. laryngectomy) or treatment (e.g. radiotherapy toxicity to the speech articulator
Externí odkaz:
http://arxiv.org/abs/2411.02591
Autor:
Gowda, Harshavardhana T., Kaul, Neha, Carrasco, Carlos, Battraw, Marcus A., Amer, Safa, Kotwal, Saniya, Lam, Selena, McNaughton, Zachary, Rahimi, Ferdous, Shehabi, Sana, Schofield, Jonathon S., Miller, Lee M.
Brain-body-computer interfaces aim to provide a fluid and natural way for humans to interact with technology. Among noninvasive interfaces, surface electromyogram (sEMG) signals have shown particular utility. However, much remains unknown about how s
Externí odkaz:
http://arxiv.org/abs/2409.19939
Publikováno v:
2024 J. Neural Eng. 21 036047
Decoding gestures from the upper limb using noninvasive surface electromyogram (sEMG) signals is of keen interest for the rehabilitation of amputees, artificial supernumerary limb augmentation, gestural control of computers, and virtual/augmented rea
Externí odkaz:
http://arxiv.org/abs/2311.08548
Energy scenarios and transition pathways need estimates of technical wind energy potentials. However, the standard policy-side approach uses observed wind speeds, thereby neglecting the effects of kinetic energy (KE) removal by the wind turbines that
Externí odkaz:
http://arxiv.org/abs/2211.01276
Decoding stimuli or behaviour from recorded neural activity is a common approach to interrogate brain function in research, and an essential part of brain-computer and brain-machine interfaces. Reliable decoding even from small neural populations is
Externí odkaz:
http://arxiv.org/abs/2205.09829
Neural population activity relating to behaviour is assumed to be inherently low-dimensional despite the observed high dimensionality of data recorded using multi-electrode arrays. Therefore, predicting behaviour from neural population recordings has
Externí odkaz:
http://arxiv.org/abs/2202.06159
Autor:
Hurwitz, Cole, Srivastava, Akash, Xu, Kai, Jude, Justin, Perich, Matthew G., Miller, Lee E., Hennig, Matthias H.
Latent dynamics models have emerged as powerful tools for modeling and interpreting neural population activity. Recently, there has been a focus on incorporating simultaneously measured behaviour into these models to further disentangle sources of ne
Externí odkaz:
http://arxiv.org/abs/2110.14853
Autor:
Pei, Felix, Ye, Joel, Zoltowski, David, Wu, Anqi, Chowdhury, Raeed H., Sohn, Hansem, O'Doherty, Joseph E., Shenoy, Krishna V., Kaufman, Matthew T., Churchland, Mark, Jazayeri, Mehrdad, Miller, Lee E., Pillow, Jonathan, Park, Il Memming, Dyer, Eva L., Pandarinath, Chethan
Advances in neural recording present increasing opportunities to study neural activity in unprecedented detail. Latent variable models (LVMs) are promising tools for analyzing this rich activity across diverse neural systems and behaviors, as LVMs do
Externí odkaz:
http://arxiv.org/abs/2109.04463
Autor:
Marin Vargas, Alessandro, Bisi, Axel, Chiappa, Alberto S., Versteeg, Chris, Miller, Lee E., Mathis, Alexander
Publikováno v:
In Cell 28 March 2024 187(7):1745-1761
Publikováno v:
In Neuropsychologia 15 February 2024 194