Closed-loop Systems

Memory prosthetics — closed-loop brain-computer interfaces that decode hippocampal activity and deliver adaptive stimulation — are moving from animal proof-of-concept toward first-in-human trials, according to a review in iScience. The authors argue that chronically implantable systems require co-design of three subsystems that have been treated in isolation: biocompatible electrode interfaces, on-chip neuromorphic computation, and closed-loop control hardware. The review maps neuroscientific findings such as theta-phase tracking, theta-gamma coupling and sharp-wave ripple detection onto engineering specifications for latency, sampling and charge injection, and onto materials requirements for impedance, switching endurance and chronic stability. It also flags where small-cohort clinical results have been over-generalized.

A review in *Frontiers in Neuroscience* describes closed-loop BCIs as systems that detect motor imagery, motor attempts or sensorimotor rhythms and trigger contingent electrical stimulation, robotic assistance, virtual reality, multisensory feedback or neuromodulation. The authors argue that restoring the timing between intent, assisted movement and sensory feedback may promote activity-dependent plasticity, while stressing that outcomes vary with patient selection, signal quality, dose, feedback modality and trial design.

A mini-review places deep-brain stimulation, brain-computer interfaces and speech neuroprostheses within a shared closed-loop architecture of sensing, decoding, stimulation or output, power, telemetry and chronic validation. It identifies long-term stability, neural coding and equitable access as recurring constraints across all three fields and argues that governance must advance alongside engineering.

A PRISMA-guided review evaluates closed-loop EEG-based BCI and neurofeedback interventions for mental health, screening 1,101 records and including 25 studies.