Secure Research Access.

Psynaptix is an independent graduate research project authored by James "Rusty" Haner as original thesis work. It is not a registered company, commercial product, or service provider, and it is not affiliated with, endorsed by, or sponsored by any of the platforms listed above. Third-party names and marks (including MoFaCTS, Canvas, Qualtrics, and Anki) are the property of their respective owners and are used for identification and interoperability purposes only. This is the author's personal scholarly work, developed outside any university job duties and without university funding. Intellectual-property ownership is determined under University of Memphis policy (RE7004); disclosure to the university is in progress, so any ownership, licensing, or IP statements on this page remain subject to the University of Memphis's intellectual-property and institutional review policies. Nothing on this page constitutes an endorsement, approval, or authorization by the University of Memphis or the Institute for Intelligent Systems.

Psynaptix is intended solely for research and educational purposes. The data collected through the platform is used exclusively for research conducted under an approved IRB protocol, and is never sold or used for commercial purposes.

Psynaptix stores no personally identifiable information (PII) or protected health information (PHI) by default: sessions are identified only by opaque identifiers, and names, emails, and direct identifiers are not transmitted into the platform by design. Where learner data could be PHI-capable, the platform applies HIPAA-grade controls as the ceiling (encryption at rest and in transit, token-gated access, audit logging, and data-retention and deletion controls). Research involving human participants is conducted under institutional review board (IRB) approval and applicable research-ethics guidelines, including APA ethical standards. Participants should receive study-specific consent information from the study's principal investigator.

Where the EU General Data Protection Regulation (GDPR) or similar data protection laws apply, individuals may have rights regarding their personal data, including the rights of access, rectification, erasure, restriction of processing, data portability, and objection. Any personal data processed in connection with this research project is handled in accordance with the applicable institutional research and data-protection policies, is minimized to what is necessary for the research, and is retained or deleted in line with the study's documented retention and erasure procedures. Requests relating to these rights should be directed to the study's principal investigator.

This application and certain of its features may use large language models (LLMs) to assist with analysis and reporting, including generated study reports and interpretive text. AI-generated output is provided for research assistance only, may contain errors or inaccuracies, and must be verified against the underlying data before use. AI-assisted output does not constitute medical, psychological, or clinical assessment, advice, or diagnosis.

Authorship. © 2026 James "Rusty" Haner. All rights reserved. Psynaptix is the original thesis work of James "Rusty" Haner, a senior research software developer with over 20 years of software experience, built with robust testing (unit, integration, and end-to-end). More about the author: rustyhaner.com. This project, including this website and its source code, was authored with the assistance of large language models (LLMs), with all LLM-generated content supervised, reviewed, and tested by a human (the author) before inclusion. The license for the underlying source code has not yet been determined and is reserved pending thesis completion and university IP disclosure. This page is the author's personal scholarly work; nothing here transfers or waives the author's rights in the work. This project is the author's personal work, developed outside the author's university job duties and without university funding. Intellectual-property ownership is determined under University of Memphis policy (RE7004); disclosure to the university is in progress. Any ownership, licensing, or IP statements on this page remain subject to the University of Memphis's intellectual-property and institutional review policies.

Acknowledgments. Thesis advising: Dr. Phil Pavlik. Institute leadership: Dr. Leah Windsor and Dr. Alistair Windsor. The project was conducted at the University of Memphis Institute for Intelligent Systems and integrates with the MoFaCTS learning platform.