MindGap: A Conversational AI Framework for Upstream Neuroplastic Intervention in Post-Traumatic Stress Disorder
Eranga Bandara, Ross Gore, Asanga Gunaratna, Ravi Mukkamala, Nihal Siriwardanagea, Sachini Rajapakse, Isurunima Kularathna, Pramoda Karunarathna, Wathsala Herath, Chalani Rajapakse, Sachin Shetty, Anita H. Clayton, Christopher K. Rhea, Ng Wee Keong, Kasun De Zoysa, Amin Hass

TL;DR
MindGap is a privacy-preserving conversational AI framework designed to facilitate upstream neuroplastic changes in PTSD patients by guiding them through structured mindfulness practices at the feeling tone gap.
Contribution
It introduces a novel on-device AI system that delivers structured neuroplastic rehabilitation for PTSD based on dependent origination, enabling upstream neural pathway dissolution.
Findings
Enables upstream neural pathway weakening through guided practices.
Operates entirely on-device, ensuring privacy and suitability for sensitive contexts.
Facilitates daily neuroplastic training with a lightweight language model.
Abstract
Post-Traumatic Stress Disorder (PTSD) is fundamentally a neuroplastic problem traumatic contact events encode over-reactive neural pathways through Hebbian long-term potentiation, producing hair-triggered amygdala-HPA stress cascades that fire before conscious awareness can intercept them. Existing therapeutic approaches, prolonged exposure, EMDR, cognitive behavioural therapy, operate predominantly downstream of the reactive cascade, teaching patients to tolerate or reframe distress after it has arisen. While clinically valuable, these suppression-based approaches do not produce the upstream pathway dissolution that constitutes lasting structural neural reorganisation. This paper proposes MindGap, a privacy-preserving on-device conversational AI framework that delivers structured neuroplastic rehabilitation for PTSD through the practice of dependent origination, a Buddhist…
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