Objectives: Brain‒computer interfaces (BCI) are currently used in clinical studies but mostly rely on population
level signals that limit their precision, facing challenges of interpretability and limited temporal‒spatial specificity. This review describes human single-neuron recordings and new evidence of concept cells from Ruijin Hospital, and proposes a framework to apply these recordings for closed-loop single-neuron brain‒computer interfaces.
Methods: We summarize the methodology enabling human single-neuron recordings using Behnke-Fried macro-micro electrodes implanted for monitoring epileptic patients with intracranial recordings. To illustrate feasibility, we present single-unit data from four patients at Ruijin Hospital and describe the procedures for paradigm design, spike detection and sorting, as well as neuronal response identification, and discuss this within the framework of current BCI clinical applications.
Results: Recordings from the human hippocampus and amygdala revealed highly selective single-neuron responses to personally meaningful visual stimuli, demonstrating 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 using single-neuron recordings. In parallel, current deep-brain BCIs that use local field potential signals have shown therapeutic value in epilepsy, Parkinson’s disease, de
pression, and memory modulation but their application remain limited due to the coarse precision of the signals. By integrating clinical advances with single-neuron recording, we outline two closed-loop strategies: (1) adaptive neural feedback systems that facilitates new studies with human single neuron recordings and particularly with concept cells and (2) adaptive neuromodulation systems that adjust stimulation parameters on the basis of single-neuron responses to study memory processing.
Conclusions: Human single-neuron recordings provide a unique opportunity to link deep-brain neuronal activity with high-level cognitive processes. 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 single-neuron responses may enhance both cognitive research and therapeutic interventions. Achieving clinical translation will require further studies of long-term signal stability, decoding robustness, and scalable integration with existing deep-brain stimulation technologies.
