Tunable Organic Active Neural Probe Enabling Near-Sensor Signal Processing

Neural recording systems have significantly progressed to provide an advanced understanding and treatment for neurological diseases. Flexible transistor-based active neural probes exhibit great potential in electrophysiology applications due to their intrinsic amplification capability and tissue-compliant nature. However, most current active neural probes exhibit bulky back-end connectivity since the output is current, and the development of an integrated circuit for voltage output is crucial for near-sensor signal processing at the abiotic/biotic interface. Here, inkjet-printed organic voltage amplifiers are presented by monolithically integrating organic electrochemical transistors and thin-film polymer resistors on a single, highly flexible substrate for in vivo brain activity recording. Additive inkjet printing enables the seamless integration of multiple active and passive components on the somatosensory cortex, leading to significant noise reduction over the externally connected typical configuration. It also facilitates fine-tuning of the voltage amplification and frequency properties. The organic voltage amplifiers are validated as electrocorticography devices in a rat in vivo model, showing their ability to record local field potentials in an experimental model of spontaneous and epileptiform activity. These results bring organic active neural probes to the forefront in applications where efficient sensory data processing is performed at sensor endpoints.

Automated summary

Neural recording systems continue to advance in order to better understand and treat neurological diseases. This study introduces inkjet-printed organic voltage amplifiers that integrate organic electrochemical transistors and thin-film polymer resistors on a flexible substrate for in vivo brain activity recording. These amplifiers reduce noise and allow for fine-tuning of voltage amplification and frequency properties. In a rat model, they successfully record local field potentials in spontaneous and epileptiform activity, making them promising for efficient sensory data processing at sensor endpoints.