A framework for deep-brain single-neuron brain–computer interfaces informed by concept cells and clinical evidence

Deep-brain brain‒computer interfaces (BCI) are currently used in clinical neuromodulation but mostly rely on population-level signals that limit decoding precision and the ability to target high-level cognition, facing challenges of noninterpretability and limited temporal‒spatial specificity. This review, informed by the human single-neuron recording technique and new evidence of concept cells from Ruijin Hospital, proposes a closed-loop deep-brain single-neuron brain‒computer interface framework to address these limitations. We summarize the methodology enabling human single-neuron recordings via Behnke-Fried macromicro electrodes implanted for stereoelectroencephalography monitoring. To illustrate feasibility, we present single-unit data from four patients at Ruijin Hospital and describe the procedures for stimulus design, spike detection, and neuronal response identification. This evidence, together with current deep-brain BCI clinical applications, informs the proposed framework. Recordings from the hippocampus and amygdala revealed highly selective single-neuron responses to personally meaningful visual stimuli, demonstrating concept-specific firing patterns consistent with those previously described in the human medial temporal lobe. These findings confirm that concept cells can be reliably identified in clinical settings in China via the single-neuron recording technique. In parallel, current deep-brain BCIs that use local field potential signals have shown therapeutic value in epilepsy, Parkinson’s disease, depression, and memory modulation but remain limited by the use of coarse biomarkers and noninterpretability. By integrating these clinical advances with single-neuron recording, we outline two closed-loop strategies: (1) adaptive neural feedback systems that accelerate concept cell identification and (2) adaptive neuromodulation systems that adjust stimulation parameters on the basis of single-neuron biomarkers relevant to memory processing. Human single-neuron recordings provide a unique opportunity to link deep-brain neuronal activity with high-level cognitive representations. Our findings demonstrate that concept cells can be reliably identified in clinical settings and offer a powerful substrate for next-generation deep-brain BCIs. A closed-loop framework informed by a single-neuron response may enhance both cognitive research and therapeutic neuromodulation. Achieving clinical translation will require advances in long-term signal stability, decoding robustness, and scalable integration with existing deep-brain stimulation technologies.