Taylor Newton

BraiNN is a framework for fast, personalized whole-brain network modeling using neural mass models, achieving rapid parameter fitting on consumer GPUs for clinical applications.

The paper introduces o2S2PARC, an open-source platform for computational modeling and analysis, highlighting its features, applications, and adoption.

This paper introduces SpIC3D, a 3D imaging method for high-resolution visualization of spinal structures, enabling quantification of neuronal density and volumetric reconstruction for computational modeling.

The paper proposes frequency-dependent safety thresholds for temporal interference stimulation (TIS) by comparing it to established brain stimulation methods using biophysical simulations.

The paper develops an in silico model of voltage-sensitive dye imaging to show that VSDI signals reflect inhibitory responses to ongoing excitatory dynamics in rodent neocortical circuits.