Researchers from several prominent universities in China have developed a new neural stimulation chip designed to make neural modulation safer and more effective for treating neurological conditions. The team, led by Professor Biao Sun and Associate Professor Xu Liu, created a state-of-the-art, 8-channel device capable of delivering high-voltage stimulation with remarkable efficiency. The chip, which achieves 98% power efficiency and includes sophisticated charge-balancing mechanisms, could significantly improve treatments for conditions like Parkinson’s disease, epilepsy, and spinal injuries. It also has potential applications in brain-machine interfaces and advanced prosthetics.
Neural modulation, the use of electrical stimuli to alter nervous system activity, is an exciting area of research that holds promise for treating a variety of neurological disorders. By directly stimulating the brain or other nerve systems, these techniques can help alleviate symptoms of diseases like Parkinson’s or control epileptic seizures. However, one of the main challenges in this field is delivering the electrical stimulus to neurons in a way that is both effective and safe. Stimulating neurons requires precise control of the electrical charge to avoid damaging surrounding tissue, while also ensuring that the power consumption remains efficient.
To address this issue, Professor Sun and his collaborators designed a novel neural stimulation chip that delivers exponentially decaying currents. This type of current is more power-efficient than the traditional constant-current methods often used in neural modulation. By making the process safer and more efficient, the team’s innovation could significantly enhance current treatment options for patients and open up new possibilities for future brain-machine interface technologies.
The study was conducted through a collaborative effort between researchers from four institutions: Tianjin University, Beijing University of Technology, Tianjin University of Traditional Chinese Medicine, and the Southern University of Science and Technology. The core of their research was the development of an 8-channel neural stimulation chip. This chip, fabricated using 180-nanometer BCD CMOS technology, has a compact core area of just 13.25 square millimeters. It was designed to handle high-voltage outputs, up to 30 volts, which allows it to work with high-impedance electrodes often used in neural stimulation.
To test the chip’s performance, the researchers carried out a range of laboratory and animal experiments. First, they confirmed that the device could effectively trigger action potentials—electrical signals produced by neurons—and induce muscle contractions in test settings. Importantly, the team paid special attention to ensuring that the electrical stimulation did not leave any harmful residual charges, which could lead to ion imbalances and tissue damage over time.
To achieve this, each channel of the chip includes an active charge-balancing circuit and a dual-slope control system, which significantly reduces residual charges to less than 3 nanocoulombs per cycle. This level of precision ensures that the device can operate safely over many cycles without risking tissue damage, even when delivering high-voltage stimulation.
In animal experiments, the chip was tested on anesthetized rats, where it successfully stimulated both the vagus nerve and the sciatic nerve. These tests confirmed that the chip could induce motor responses in the rats without causing any observable tissue damage, validating its potential for use in biological settings.
The study’s key finding is the development of a neural stimulation chip that combines safety and high power efficiency, a combination that has been difficult to achieve in previous designs. The chip’s exponential waveform output was found to be particularly beneficial, as it allows for greater efficiency in charge transfer, which is a major challenge when working with high-impedance electrodes. These electrodes are commonly used in neural stimulation, but they create resistance that makes it harder to deliver enough charge without increasing the risk of tissue damage.
The chip’s ability to deliver stimulation efficiently at up to 30 volts while maintaining charge imbalance at less than 3 nanocoulombs is a major improvement over existing technologies. In laboratory tests, the researchers found that the chip operates at an efficiency rate of 98.1% at a 20-volt output, which is significantly higher than most existing devices.
(Credit: Biao Sun/Tianjin University, Hao Yu/ Southern University of Science and Technology, Xu Liu/Beijing University of Technology.)
In terms of real-world application, the researchers are optimistic that this chip could be used in a range of medical devices designed to treat neurological conditions. By improving the safety and efficiency of neural stimulation, the chip could lead to better treatment outcomes for patients with conditions like Parkinson’s disease and epilepsy, and may also enable more advanced brain-machine interface systems, which could allow paralyzed individuals to control prosthetic limbs or other devices with their thoughts.
While the study represents a significant advancement in neural modulation technology, the researchers acknowledged a few limitations in their work. First, although the chip performed well in the controlled laboratory and animal experiments, more extensive testing is needed to confirm its effectiveness and safety in humans. Neural tissue in humans is more complex than that of rats, and the electrode-tissue interface may behave differently in clinical applications.
Additionally, while the chip achieved impressive charge balance and power efficiency, further refinements could be made to better capture the complexity of neural interactions in more diverse biological settings. Future research could focus on improving the device’s ability to handle a wider range of stimulation protocols, especially in more intricate neural networks.
The study, “An 8-channel high-voltage neural stimulation IC design with exponential waveform output,” was authored by Xu Liu, Zeyu Lu, Juzhe Li, Xue Zhao, Lin Zheng, Weijian Chen, Gengchen Sun, Jiaqi Sun, Liuyang Zhang, Shenjun Wang, Biao Sun, and Hao Yu.
