We propose a novel dual-loop system that synergistically combines responsive neurostimulation (RNS) implants with artificial intelligence-driven wearable devices for treating post-traumatic stress disorder (PTSD) and enabling naturalistic brain research. In PTSD Therapy Mode, an implanted closed-loop neural device monitors amygdala activity and provides on-demand stimulation upon detecting pathological theta oscillations, while an ensemble of wearables (smart glasses, smartwatches, smartphones) uses multimodal large language model (LLM) analysis of sensory data to detect environmental or physiological PTSD triggers and deliver timely audiovisual interventions. Logged events from both the neural and wearable loops are analyzed to personalize trigger detection and progressively transition patients to non-invasive interventions. In Neuroscience Research Mode, the same platform is adapted for real-world brain activity capture. Wearable-LLM systems recognize naturalistic events (social interactions, emotional situations, compulsive behaviors, decision making) and signal implanted RNS devices (via wireless triggers) to record synchronized intracranial data during these moments. This approach builds on recent advances in mobile intracranial EEG recording and closed-loop neuromodulation in humans (BRAIN Initiative, 2023) (Mobbs et al., 2021). We discuss how our interdisciplinary system could revolutionize PTSD therapy and cognitive neuroscience by enabling 24/7 monitoring, context-aware intervention, and rich data collection outside traditional labs. The vision is a future where AI-enhanced devices continuously collaborate with the human brain, offering therapeutic support and deep insights into neural function, with the resulting real-world context rich neural data, in turn, accelerating the development of more biologically-grounded and human-centric AI.
Our system consists of three primary subsystems: sensing, analysis, and stimulation/intervention, orchestrated by a cloud-connected software pipeline. The patient is equipped with an implanted neural device, wearable sensors including smart glasses and a smartwatch, and a smartphone that serves as a local hub.
Figure 1: Overview of the closed-loop system architecture showing the integration of neural implants, wearable sensors, and LLM agents.
Our system provides rapid intervention when a PTSD trigger is detected. The timeline below illustrates a typical sequence during an episode: a trigger appears, biometrics deviate, the LLM confirms the trigger, and interventions are delivered to prevent a full-blown panic attack.
Figure 2: Timeline of system response to a PTSD trigger, showing detection and intervention sequence.
Consider a veteran with PTSD in a grocery store. A loud noise (crate dropping) triggers increased heart rate and hypervigilance. The system detects these changes, delivers neural stimulation, and provides visual/audio cues through smart glasses to help the patient remain calm and avoid a full episode.
Visualization of the case study scenario showing trigger detection and system response.
Our framework can be generalized to other neuropsychiatric and neurological conditions that benefit from closed-loop intervention, including:
@article{wang2025neuroai,
title={The Neuro-AI Revolution: Closed-Loop Systems, LLM Agents, and the Future of Neural Science},
author={Wang, Edward Hong and Wen, Cynthia Xin and Hoffer, John},
journal={arXiv preprint arXiv:XXXX.XXXXX},
year={2025}
}