Non-invasive neuromodulation techniques are widely utilized to study and improve cognitive function, with the aim of modulating different cognitive processes. For workers performing high-intensity mental and physical tasks, extreme fatigue may not only affect their working efficiency but may also lead to cognitive decline or cognitive impairment, which, in turn, poses a serious threat to their physical health. The use of non-invasive neuromodulation techniques has important research value for improving and enhancing cognitive function. In this paper, we review the research status, existing problems, and future prospects of transcranial direct current stimulation (tDCS), transcranial alternating current stimulation (tACS), transcranial magnetic stimulation (TMS), and transcutaneous acupoint stimulation (TAS), which are the most studied physical methods in non-invasive neuromodulation techniques to improve and enhance cognition. The findings presented in this paper will be of great reference value for the in-depth study of non-invasive neuromodulation techniques in the field of cognition.

Open-vocabulary object detection (OVD) requires detectors to align image regions with text-defined categories while remaining computationally practical. In existing systems, stronger cross-modal reasoning often improves recognition of rare or fine-grained categories, but typically increases inference cost. We present TG-OverLoCK, an OverLoCK-based extension for OVD that selectively concentrates language-conditioned refinement capacity in an overview-to-focus pathway, rather than inserting uniformly dense cross-modal fusion throughout the backbone. The model combines a lightweight overview stage with a deeper focus stage. The overview stage produces a prompt-conditioned spatial Context-Text Prior (CTP), which is propagated top-down and updated across focus blocks to guide selective refinement. Within the focus stage, multi-head cross-attention and ContMix-MLP provide text-conditioned feature adaptation and dynamic spatial mixing. TG-OverLoCK does not introduce a new vision-language pre-training objective or a trainable text encoder; instead, it isolates the architectural effect of coarse-to-fine text guidance under a standard frozen-CLIP OVD pipeline. On LVIS rare-to-novel and COCO OVD zero-shot evaluation, TG-OverLoCK-B achieves 38.2 AP and 29.0 Novel AP, respectively, while running at 35 FPS on a single RTX 4090 under our in-house timing protocol. Relative to the matched OverLoCK-B baseline, TG-OverLoCK-B improves LVIS AP from 35.9 to 38.2 while increasing end-to-end latency from 24.5 ms to 28.6 ms and peak VRAM from 4.8 GB to 6.2 GB, indicating an accuracy gain with moderate overhead rather than a free improvement.

In neurovascular interventional surgery, vascular visualization technology is crucial for doctors to diagnose and treat vascular diseases and reduce postoperative complications.^1,2 Traditional vascular visualization techniques, such as contact Doppler ultrasound and flow velocity measurement, have long been widely used in neurosurgery.