A new paradigm for brain-machine interface electrodes: From static to dynamic, advancing toward embodied intelligence

Brain-machine interfaces (BMIs) are rapidly evolving as a transformative technology for neural decoding, prosthetic control, and neuromodulation. Traditional BMIs typically rely on rigid electrodes or passive flexible probes to record or stimulate neural activity. While such devices have enabled significant progress in neuroscience and neuroprosthetics, their static and fixed nature often limits long-term performance and adaptability. In contrast, soft and dynamic neural interfaces offer superior mechanical compatibility with brain tissue, enabling more intimate and stable coupling with the neural microenvironment. This compatibility minimizes chronic inflammation and signal degradation induced by mechanical mismatch, maintaining higher fidelity and biocompatibility over extended periods. However, most current BMI electrodes remain essentially "static," confined to localized regions with limited ability to adapt or reposition once implanted. This immobility constrains spatial coverage and often necessitates secondary surgeries for electrode adjustment.

Therefore, the next generation of BMIs must move beyond static recording architectures to realize dynamic and adaptive neural interfaces. Future BMIs will function not merely as "passive sensors" but as "active agents" capable of adjusting their position, configuration, and interaction with neural circuits in response to the evolving brain environment.1 Such systems could form closed-loop adaptive networks that continuously optimize recording, stimulation, and feedback to match neural plasticity and tissue remodeling. This transition will mark a critical step toward embodied intelligence in BMIs—systems that are integrated, responsive, and self-adaptive within the living brain.

From material design to intelligent neural interfacing

The foundation of intelligent BMIs lies in advanced materials and interface engineering. The design and fabrication of neural interfaces require a careful balance of flexibility, stability, and functional density. Excessive softness may compromise signal conduction or durability, while excessive rigidity can trigger immune responses. Moreover, the long-term interface between electrodes and neural tissue critically affects signal fidelity and device lifespan. The “three interfaces and one connection” framework, encompassing the conductive layer-tissue, conductive layer-substrate, and conductive layer-encapsulation interfaces, provides a conceptual basis for understanding and mitigating BMI failure modes. Here, “one connection” specifically refers to the interface between the implanted soft device and the external rigid data acquisition or communication module, which is particularly prone to mechanical strain accumulation and insulation or contact failure during long-term implantation. Although anti-inflammatory coatings and neurotrophic factors can temporarily alleviate immune response, fibrosis and encapsulation are inevitable over extended implantation periods. Therefore, a comprehensive understanding of all tissue-device interaction interfaces is essential for improving long-term BMI stability. Future BMIs may leverage high-resolution analytical techniques such as mass spectrometry imaging and single-cell sequencing to monitor interfacial immune dynamics in situ. Meanwhile, combining micro/nano-structural optimization with biochemical strategies will help establish neural interfaces with reduced immune response and enhanced long-term integration.