A Synergistic Noise Suppression Strategy for High-Fidelity in Vivo Photoelectrochemical Brain Sensing

This study addresses the challenge of noise interference in detecting weak photoelectrochemical (PEC) signals in the living brain. We propose a noise-reduction strategy that combines a resistive grounding shield with an optimized passive LC filter network. By analyzing the electrical properties of the brain tissue and its noise spectrum, a shielding circuit as well as tuned capacitor and inductor parameters were optimized to effectively suppress high-frequency interference. Experimental results demonstrate that this strategy achieves an exceptional signal-to-noise ratio (SNR) enhancement of 39.22 dB, representing a remarkable advancement in noise suppression for in vivo PEC sensing. Furthermore, a PEC microsensor based on polyselenophene-modified microelectrodes was developed for real-time monitoring of calcium ion levels in the living brain. This microsensor exhibits high sensitivity, with a detection limit of 1.49 μM, and a good linear response within the range of 9.9 μM to 4.77 mM, effectively distinguishing calcium ions from other interfering substances. In vivo experimental results confirm that the proposed noise-reduction strategy effectively enhances photopotential quality signals under realistic physiological conditions. This work provides a reliable, low-complexity, and implantable-compatible platform for high-fidelity neurochemical sensing in brain research.