A soft electrode array with reconfigurable hydrogel interfaces for high-fidelity neurophysiological monitoring during craniotomy.

Achieving accurate monitoring of electrophysiological activity from the brain cortex is critical for preventing postoperative neurological deficits during craniotomy. However, current technologies face profound challenges in enabling consistent high-quality neural signal acquisition due to complex intracranial environments (e.g., wet/fragile brain surfaces and surgical instrument interference). Here, we develop a soft electrode array with reconfigurable hydrogel interfaces for sustainable high-fidelity monitoring of electrophysiological states from the functional brain cortex throughout neurosurgical procedures. Specifically, we propose a solution-triggered reconfiguration strategy to implement the repeated disassembly/replacement of hydrogel interface layers on electrodes, ensuring consistently superior recording and stimulation properties. Furthermore, through modification with cationic hydrogel microspheres, the hydrogel interface demonstrates strengthened wet adhesion and antiswelling performances, creating robust hydrogel/brain coupling to minimize motion artifacts. In craniotomy of animal models, the electrode array maintains low impedance and high signal-to-noise ratio during repeated repositioning tests through hydrogel interface reconfiguration. In traumatic brain injury models, the electrode array can record consistent high-quality somatosensory evoked potential with dynamic tracking of potential amplitude and latency changes in sensory areas. Quantitative assessments in nerve block experiments verify that the soft electrode array can efficiently elicit motor evoked potentials in motor areas with low stimulation currents. The proposed soft electrode array represents a promising platform for sustainable high-fidelity electrophysiological monitoring. The hydrogel interface design strategy provides an effective approach for developing reconfigurable devices in biomedical applications.