PyNoetic: Towards No Code Development of
Brain-Computer Interfaces

Brain-Computer Interfaces (BCIs), have emerged as a transformative technology with applications spanning virtual reality (VR), robotics, entertainment, medicine and rehabilitation. However, existing BCI toolboxes/ frameworks suffer from critical limitations, including a lack of "stage-wise" flexibility crucial for experimental research, elevated costs stemming from reliance on proprietary software (SW), and a lack of all-inclusive features leading to reliance on multiple external tools, affecting research outcomes. To address these limitations, we present PyNoetic, an end-to-end comprehensive Python framework designed to address the diverse needs of BCI research. PyNoetic offers a wide range of functionality, including stimuli presentation, data acquisition, channel selection, filtering, feature extraction and artifact removal. Moreover, it encompasses a rich array of analytical tools including, brain-connectivity measures, machine learning (ML) models, data visualization methods, systematic testing functionalities via simulation, and evaluation methods of novel paradigms. For experienced users, PyNoetic facilitates the integration of custom functionality and novel algorithms at each stage of BCI system development, with minimal lines of code, ensuring adaptability and innovation. One of PyNoetic's key strengths lies in its versatility for both offline analysis and real-time BCI development. By catering to both programmers and non-programmers alike, it streamlines the experiment design process, enabling researchers to focus on more intricate facets of BCI development, and accelerating research endeavors.