We don't just generate data; we audit it. By integrating Captum directly into our reasoning pipeline, we ensure every voxel respects physiological laws.
When a standard GAN generates a brain image, it cannot tell you why it lit up the Amygdala. Did it see a sleep spindle? Or did the patient just grind their teeth (EMG artifact)?
This lack of reasoning is unacceptable in medicine. Our Audit Layer solves this by backpropagating gradients from the output image back to the input EEG. If the model says "Amygdala Activity," we can prove it came from "Delta Waves" and not "Jaw Clenching."
A dual-stage pipeline ensuring high fidelity and high compliance.
Raw EEG Data
(Unfiltered)
cGAN Prediction
Captum Checks
(Pass/Fail)
Article 13 requires "High-Risk AI Systems" to be sufficiently transparent for users to interpret outputs.
Our architecture satisfies this by generating a Physiological Attribution Map for every fMRI frame. Clinicians don't just get a scan; they get a reason. "This activation is 95% attributed to Sleep Spindle activity in Channel C4."