RT-Cloud: A cloud-based software framework to simplify and standardize real-time fMRI

Area of Science:

• Neuroscience
• Computational Psychiatry
• Medical Imaging

Background:

• Real-time fMRI (RT-fMRI) neurofeedback shows promise for neuropsychiatric disorders.
• Current limitations include high computing demands, complex setup, and lack of standardization.

Purpose of the Study:

• To introduce RT-Cloud, a flexible, cloud-based, open-source Python package for RT-fMRI experiments.
• To address barriers hindering the widespread adoption of RT-fMRI.

Main Methods:

• Developed RT-Cloud, a Python software package utilizing cloud computing.
• Integrated RT-Cloud with open standards like Brain Imaging Data Structure (BIDS) and OpenNeuro.
• Leveraged cloud computing to automate installation, configuration, and remote maintenance.

Main Results:

• RT-Cloud facilitates standardized data formats and adaptable processing streams.
• Cloud computing eliminates the need for on-premise high-performance computing.
• Scalability of cloud computing enables real-time deployment of complex analyses.

Conclusions:

• RT-Cloud enhances open science in RT-fMRI research and applications.
• The software simplifies RT-fMRI experiment execution, promoting wider accessibility.
• Future development aims to further deploy RT-Cloud in research and clinical settings.