Artificial intelligence meets body sense: task-driven neural networks reveal computational principles of the proprioceptive pathway
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Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41392-024-01870-9.pdf
Reference5 articles.
1. Marin Vargas, A. et al. Task-driven neural network models predict neural dynamics of proprioception. Cell 187, 1745–1761.e19 (2024).
2. Sussillo, D., Churchland, M. M., Kaufman, M. T. & Shenoy, K. V. A neural network that finds a naturalistic solution for the production of muscle activity. Nat. Neurosci. 18, 1025–1033 (2015).
3. Yamins, D. L. & DiCarlo, J. J. Using goal-driven deep learning models to understand sensory cortex. Nat. Neurosci. 19, 356–365 (2016).
4. Kanwisher, N., Khosla, M. & Dobs, K. Using artificial neural networks to ask ‘why’ questions of minds and brains. Trends Neurosci. 46, 240–254 (2023).
5. Flesher, S. N. et al. A brain-computer interface that evokes tactile sensations improves robotic arm control. Science 372, 831–836 (2021).
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