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From a mechanistic understanding of neural systems to AI-driven neuromodulation | title | From a mechanistic understanding of neural systems to AI-driven neuromodulation |
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| start_date | 2025/06/30 |
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| schedule | 11h-12h |
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| online | no |
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| location_info | salle des Voûtes |
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| summary | Advances in nervous system interfacing present a promising venue for rehabilitation of individuals with different neurological disabilities. Subjects with pain, stroke, or diabetes frequently do not engage fully in everyday activities because they are afraid of falls. They also tend to have reduced mobility, which can induce a sedentary lifestyle that promotes disease development and hinders reinsertion into society, while the neuropathic pain is also common and poorly managed with current medications. Despite a wide range of possibilities for human-machine interfacing, the nature of the optimal human-machine interaction remains poorly understood. Knowledge gained from in-silico modelling of targeted neural structures can inform an optimized design of such interfacing, therefore we develop the exact models of different nerves, enabling for AI-based personalized treatments. We have pioneered a human-machine systems that translates artificial sensors’ read-outs into “language” understandable by the nervous system. The “smart orthosis” for diabetics “speaks” to their residual healthy nerves while diminishing pain. Their effects at the brain level were evaluated, observing important benefits. These studies not only provided clear evidence of the benefit of neuromodulation for neurologically disabled subjects but also provided insights into fundamental mechanisms of supraspinal integration of the restored sensory modalities. |
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| responsibles | Basques |
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Workflow history| from state (1) | to state | comment | date |
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| submitted | published | | 2025/06/20 08:35 UTC |
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