My research career began with an opto-electronic recording experiment demonstrating that there exist vital differences between open- and closed-loop reaching under constant lighting conditions. I proceeded to carry out several functional Magnetic Resonance Imaging (fMRI) studies that demonstrated that the frontal cortex takes on the majority of the processing load for early movement planning. As a postdoc, I again characterised preparatory movement signals in parietal and frontal cortices and then learned neuroanatomy, employing a highly novel g-deleted rabies virus to show the feedback projections in the early visual brain (area 19 is more connected more to the ventral stream and area 18 to the dorsal stream).
As a Principal Investigator, I have demonstrated, for example, that parietal-based spatial reference frames are modulated by the position of the eyes in the orbits (fMRI), that non-obstructing 3D depth cues modulate behavioural kinematic profiles and that visuospatial attention is coded in the parietal cortex (fMRI). My current research focus concerns demonstrating the efficacy of dry- and mobile-Electroencephalography (or EEG) for Brain-Computer Interfaces (or BCI). I now carry out research that integrates Machine Learning Convolutional Neural Networks with EEG for Brain-Computer Interfaces and Neuro-Robotic control (or Brain-Robot interaction).