Abstract—The integration of biophysically grounded neural
simulations with Artificial Intelligence (AI) has the potential to
transform clinical neurodiagnostics by overcoming the inherent
challenges of limited pathological EEG datasets. We present a
novel AI-driven framework that leverages a Distributed-Delay
Neural Mass Model (DD-NMM) to generate synthetic EEG
signals replicating both...
Introduction: Deep Brain Stimulation (DBS) is a successful symptom-relieving treatment for Parkinson’s disease (PD). However, the introduction of advanced directional DBS electrodes significantly expands the programming parameter space, rendering the traditional trial-and-error approach for DBS optimization impractical and demonstrating the need for computational tools. Our recently developed...
Background: Postmortem MRI has opened-up avenues to study brain structure at sub-millimeter ultra high-resolution revealing details not possible to observe with in vivo MRI. Here, we present a novel package (purple-mri) which performs segmentation, parcellation and registration of postmortem MRI. Additionally, we provide a framework to perform one-of-its-kind vertex-wise group-level studies...
Introduction: Accurate co-registration of high-resolution histology data to multimodal MRI provides complementary benefits for validation of imaging biomarkers from healthy brain and its alterations. While BigBrain [1] and Julich-Brain atlas [2] provide multi-level probability maps for cell distribution and morphology, BigMac [3] extends these efforts to co-registration of multi-contrast...
Understanding the emergence of cognitive operations from the brain's topographical organization is a fundamental goal in neuroscience. However, the roles and interactions of functional, structural and chemical brain features in shaping cognitive structure have remained poorly characterized. This study aims to investigate these multimodal contributions to cognitive structure from a spatial...
