Daniel Trotter

The paper investigates how intrinsic plasticity influences neural network heterogeneity by analyzing input statistics and their effects on cell-to-cell excitability and network dynamics.

The paper investigates how neuronal morphology affects the specificity of electric field stimulation at the single-cell level using computational models of mouse neurons.

This study investigates how tACS modulates synaptic plasticity in heterogeneous neural networks by exploiting differences in neuronal timescales.

The paper introduces a linear-nonlinear model to capture synaptic dynamics, showing it is more adaptable than previous models and can efficiently characterize synaptic processing.

The paper develops a computational method to estimate quantal parameters at single synapses using iGluSnFR imaging and statistical algorithms.