Keywords
Artificial intelligence
Deep brain stimulation
Brain-computer interface
Brain stimulation techniques
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Abstract
Objective: To present and summarize the concept of intelligent, closed-loop neuromodulation devices, which aim to identify the specific neural signatures of chronic pain and selectively cancel them. Bibliographic review: This narrative review explores a revolutionary approach at the intersection of neuroscience and artificial intelligence, treating chronic pain as a neural circuit pathology. It discusses how machine learning algorithms can decode complex neural data to isolate pain signals in real-time, enabling the identification of an objective biomarker. Based on this decoding, targeted neurostimulation can deliver precise interventions to disrupt these pathological signals, operating in a closed-loop system (sense-decode-actuate) that is more effective and safer than conventional open-loop therapies. This approach represents the transition from systemic treatments to an adaptive and personalized therapy. Final considerations: It can be considered that this AI-driven paradigm holds promise for a fundamental shift in pain management. By offering a personalized and specific therapy, it represents a potential solution for intractable pain conditions, redefining the treatment for a condition that affects millions and transforming a symptom into a treatable biological signal.
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