Haslacher David, Nasr Khaled, Soekadar Surjo R
Clinical Neurotechnology Laboratory, Neurowissenschaftliches Forschungszentrum (NWFZ), Department of Psychiatry and Psychotherapy (CCM), Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
Patterns (N Y). 2021 Jul 9;2(7):100304. doi: 10.1016/j.patter.2021.100304.
Implementation of effective brain or neural stimulation protocols for restoration of complex sensory perception, e.g., in the visual domain, is an unresolved challenge. By leveraging the capacity of deep learning to model the brain's visual system, optic nerve stimulation patterns could be derived that are predictive of neural responses of higher-level cortical visual areas . This novel approach could be generalized to optimize different types of neuroprosthetics or bidirectional brain-computer interfaces (BCIs).
实施有效的大脑或神经刺激方案以恢复复杂的感官知觉，例如在视觉领域，是一项尚未解决的挑战。通过利用深度学习对大脑视觉系统进行建模的能力，可以得出能够预测高级皮层视觉区域神经反应的视神经刺激模式。这种新方法可以推广到优化不同类型的神经假体或双向脑机接口（BCI）。
