This paper presents a real-time brain-computer interface (BCI) system that moves beyond passive data sonification to prioritize intentional musical control. Developed as a collaborative dialogue between a student researcher and a legacy practitioner, the system maps EEG data from a Muse S Athena headband to melodic and harmonic parameters within Csound. While many BCI systems focus on autonomous generation, our contribution lies in a hybrid control model that uses a sample-and-hold mechanism to 'tame' physiological 'jitter' into a stable, SATB harmonic framework. We demonstrate that this 'Bio-Interactive' approach allows the performer to balance spontaneous internal states with traditional musical intentionality. Through a series of performances - including multi-generational duets - we illustrate how 'Open Source Pedagogy' and mapping transparency can transform raw brainwave data into a deeply personal and expressive musical instrument.