Ministry of Education

A patient with chronic complete spinal cord injury improved from AIS A to AIS C and regained partial voluntary movement after one year of combined neuromodulation and conventional rehabilitation. The 53-year-old man had a T9 injury and received sequential spinal cord electrical stimulation, BCI training, motor cortex stimulation, and peripheral magnetic stimulation of both iliopsoas muscles, alongside 12 months of rehabilitation. His left lower limb motor score rose from 0 to 6, spontaneous defecation and penile erection returned, and his neuropathic pain score fell from 8 to 0. This uncontrolled case suggests a possible association with functional recovery but cannot distinguish the contributions of individual interventions or exclude spontaneous neurological recovery.

When a user looks at targets flickering at different frequencies, the visual cortex produces EEG responses at matching frequencies, known as steady-state visual evoked potentials (SSVEP), which a brain-computer interface can use to infer the intended target. Such systems usually need calibration data, and more data means more user fatigue. Researchers propose SCR-FTSDNN, a deep convolutional network that moves EEG into the frequency domain, then extracts temporal and spatial features with added spatial and channel reconstruction modules. Tested on the public Benchmark and BETA datasets, the authors report higher recognition accuracy and stability than several existing methods, especially with limited calibration data. The abstract gives no specific figures, and the results come from offline tests.

Researchers proposed EFS-Net, an end-to-end network that aligns fast EEG activity with slower fNIRS haemodynamic signals through temporal, spatial and cross-modal branches. In subject-specific leave-one-session-out validation, the model reached 77.71% accuracy on a word-generation dataset and 81.69% on a mental-arithmetic dataset.

8 Chinese ministries jointly issued a policy document explicitly promoting the integration of AI with brain-computer interface, AR, VR, and MR technologies.