StoopwenpueNq/jackie-fmri-sim

Digital twin of the canine subject “Jackie” (Canis lupus familiaris) Reconstructed from multi-session functional MRI, simultaneous EEG, physiological telemetry and behavioural annotation. jackie-brain-twin is a modular Python framework that reconstructs the real-time emotional and regional brain state of a single dog (Jackie) from actual neuroimaging and physiological recordings. The system ingests: From these data the model continuously updates a six-dimensional emotional vector (joy, curiosity, calm, excitement, anxiety, affection) and a 25-region activation map. The resulting digital twin can be queried with arbitrary textual stimuli and returns an interpretable state vector together with the most probable behavioural phenotype. Dogs possess an expanded olfactory system and a well-developed social brain network. The present reconstruction focuses on three key nodes repeatedly implicated in canine social neuroscience: Additional regions (cingulate, temporal pole, superior temporal gyrus, prefrontal areas, etc.) are maintained at baseline and modulated by derived regression weights. All numeric values in scandata.py are…