EEG at the Edge: Signals, Selves, and Systems

Electroencephalography (EEG) is undergoing a profound transformation, from a passive diagnostic tool to an active interface for communication, intervention, and neuroadaptive control. This commentary explores the current state and future trajectories of EEG-based technologies, focusing on emerging paradigms that redefine the role of the brain within technological and therapeutic environments. We begin by examining the digital present: while EEG systems are now more portable, connected, and computationally empowered than ever before, technical limitations and interpretive bottlenecks persist. We then trace the rise of closed-loop neuromodulation, with clinical evidence supporting personalized, responsive stimulation in epilepsy and Parkinson’s disease. In parallel, multimodal EEG, particularly EEG-fMRI and EEG-fNIRS integration, is offering unprecedented insights into spatiotemporal brain dynamics, cognitive biomarkers, and neurovascular coupling. The development of brain-computer interfaces (BCIs) further illustrates EEG’s shift from monitoring to action, as neural signals become control inputs for communication, rehabilitation, and assistive technologies. Recent innovations in AI and machine learning are accelerating this trend, enabling real-time decoding, anomaly detection, and adaptive user-specific pipelines. At the frontier of this evolution lie brain-to-brain interfaces (B2BIs), experimental systems that challenge notions of agency, responsibility, and cognitive sovereignty by enabling direct neural communication between individuals. Across these domains, a central theme emerges: innovation must be accompanied by reflection. We argue that EEG is no longer just a measure of brain activity; it is becoming a medium of agency, and with it, a mirror for our evolving relationship with technology, autonomy, and selfhood. Building that future demands not only technical precision, but also ethical foresight and interdisciplinary collaboration.