Daniel Bullock

TL;DR: A real-time neural network model, called the vector-integration-to-endpoint (VITE) model is developed and used to simulate quantitatively behavioral and neural data about planned and passive arm movements to demonstrate invariant properties of arm movements.

TL;DR: Evidence is found that oscillatory synchronization of local field potentials formed neural ensembles representing the rules: there were rule-specific increases in synchrony at "beta" and "alpha" frequencies between electrodes, which suggests that beta-frequency synchrony selects the relevant rule ensemble, while alpha- frequency synchrony deselects a stronger, but currently irrelevant, ensemble.

TL;DR: A self-organizing neural model for eye-hand coordination that embodies a solution of the classical motor equivalence problem is described, which is capable of controlling reaching movements of the arm to prescribed spatial targets using many different combinations of joints.

TL;DR: A Neural model of dopaminergic cells in the substantia nigra pars compacta provides a biologically predictive alternative to temporal difference conditioning models and explains substantially more data than alternative models.

TL;DR: A new model, called TELOS, is proposed to explain how laminar circuitry of the frontal cortex interacts with the BG, thalamus, superior colliculus, and inferotemporal and parietal cortices to learn and perform reactive and planned eye movements.