But creating a long-lasting electronic connection with the brain is complicated. Conventional microwire and silicon electrodes are much stiffer than soft brain tissue. Differences in mechanical properties can cause micromotion-related tissue damage, inflammation and glial scar formation. For this reason, researchers are moving from rigid electrodes toward flexible, biomimetic biohybrid interfaces. These newer approaches aspire to reduce the mechanical and biological mismatch between implanted devices and neural tissue while maintaining the ability to record and stimulate neural activity.
One of the most direct applications of ICMS is the creation of artificial sensory experiences. When electrodes stimulate the primary somatosensory cortex, people can perceive localized sensations such as touch or tingling. More recent approaches use multiple electrodes and carefully designed spatiotemporal stimulation patterns to provide richer information, including tactile edges, curvature and apparent motion. Human studies have shown that such patterned stimulation can improve the controllability and structure of artificial touch, although it still does not fully reproduce the complexity of natural tactile signals.
ICMS can also be used in the visual cortex. Stimulation of the primary visual cortex can produce phosphenes — perceived spots or lines of light — and carefully coordinated stimulation across multiple electrodes can create recognizable shapes and letters. Experiments in blind participants have demonstrated simple two-dimensional visual patterns and object-localization tasks.
These results suggest that ICMS is moving beyond producing a single artificial sensation toward constructing structured sensory information. However, the researchers note that current visual prosthesis studies remain limited to relatively simple shapes, letters and localization tasks. Predicting phosphene responses, determining effective electrode combinations and maintaining stable stimulation over long periods remain major challenges.
A further important insight from the review is that animals can learn to interpret artificial stimulation patterns and use them to guide behavior. This suggests that the brain may be able to learn the meaning of an artificial neural signal rather than requiring the signal to exactly mimic natural sensory activity. Such a strategy could provide greater flexibility for future bidirectional BCIs, where electronic systems continuously exchange information with the brain.
The review also examines a more ambitious possibility: using ICMS not simply to create an immediate sensation, but to change how neural circuits function over longer periods. Repeated or precisely timed stimulation can induce plasticity-like changes in cortical networks. The researchers discuss studies in which paired or activity-dependent stimulation altered functional connectivity between cortical regions. In one closed-loop paradigm, spontaneous neural activity in the motor cortex was used to trigger stimulation of the somatosensory cortex with a controlled delay. This temporally matched stimulation enhanced intercortical coupling and was associated with improved motor recovery in a rat model of brain injury.
However, the authors emphasize that these applications remain largely experimental. Reliable biomarkers, reproducible stimulation parameters, implantation safety and durable therapeutic benefits all require further validation before clinical translation.
The researchers also underscore a promising direction that could extend ICMS beyond artificial sensory feedback and circuit modulation: biohybrid neural interfaces (BNIs). Conventional neural electrodes are made from artificial materials that differ substantially from the soft biological tissue of the brain. Over time, this mismatch can contribute to tissue damage, inflammation and declining interface performance.
Flexible electrodes can reduce some of these problems, but they cannot completely overcome the biological barrier between implanted devices and living neural tissue.
BNIs take a further step by incorporating living biological components, such as neural stem cells, neural progenitor cells and other neural cells, into neural interfaces. These approaches aim to improve tissue integration and may enable living neural tissue to participate in signal transmission. More advanced designs can also guide axon growth, creating connections between biological tissue and electronic devices. The potential of BNIs may extend beyond improving electrode performance to repairing damaged neural circuits.
Together, these developments point toward a future in which neural interfaces could combine electronics, living cells and neural tissue to support long-term stimulation, neural integration and potentially neural repair. Despite rapid progress, the review emphasizes that ICMS has not been a plug-and-play technology. Long-term performance depends on the stability of implanted electrodes, while stimulation effects can vary between individuals and can change over time.
The researchers therefore call for coordinated advances in electrode design, stimulation encoding, closed-loop calibration and safety evaluation. Future studies should include longer follow-up, cross-species validation, standardized safety assessments and reproducible behavioral and neural-network outcomes.
Rather than replacing existing neuromodulation technologies, ICMS may ultimately become a complementary tool that offers much finer control over local neural populations. Its long-term potential could lie in bringing together several capabilities: delivering artificial sensory information, allowing the brain to learn new information channels, reshaping dysfunctional circuits and integrating electronic devices more naturally with living neural tissue.
As the review authors conclude, translating ICMS from experimental microstimulation into durable BCI systems will require progress not in a single technology, but across interface reliability, stimulation encoding, closed-loop control, safety and biohybrid integration.
Authors of the paper include Pengfei Hu, Chong Chen, Yunliang Zang, Xiaohong Li, and Dong Ming.
This work was supported by the National Key Research and Development Program of China (2023YFF1204200), the Major Program of the National Natural Science Foundation of China (T2596044), and the National Natural Science Foundation of China (82571593).
The paper, "Intracortical Microstimulation in Brain–Computer Interfaces: Evoking Perception and Plasticity" was published in the journal Cyborg and Bionic Systems on Sept 11, 2026, at https://doi.org/10.34133/cbsystems.0690.
