We investigate the computational principles and mechanisms that underlie neuromechanical control and motor learning. Our work uses a blend of experimental, theoretical and computational approaches. We focus primarily on the human arm as a system that demonstrates many of the features that make motor control a difficult problem (Franklin and Wolpert, 2011, Neuron). We use robotic interfaces and virtual reality systems in order to control precisely the sensory inputs to the subjects.

                                                                                                                                            Photo: Ulrich Benz

Our research focus is primarily within five different topics:

Motor memory formation: How do humans learn models of the external world and use these to adapt our movements to new experiences? We have shown that there is a critical time before and after movements in which the active motor memory can be accessed and modulated (Howard et al., 2012, J Neurosci; Howard et al., 2015, Curr Biol) and that motor planning is more critical than execution (Sheahan et al., 2016, Neuron).

Motor memory representation: In what manner are these motor memories represented within the brain? We have shown that motor memories are represented in a mixed co-ordinate system that includes Cartesian, joint and object-based coordinates (Berniker et al., 2013, J Neurophysiol; Franklin et al, 2016, eNeuro).

Feedback modulation: We have developed novel techniques to measure the visuomotor feedback gains and shown how they are modulated according to the environment (Franklin and Wolpert, 2008, J Neurosci; Franklin et al., 2012, J Neurophysiol)

Visuomotor Control: We use visuomotor feedback gains in order to probe the computations underlying visual control of reaching movements (Dimitriou et al., 2013, J Neurosci; Reichenbach et al., 2014, Curr Biol; Franklin et al., 2016, J Neurosci).

Neuromechanics: We have shown that the nervous system can modulate the limb stiffness independently of endpoint force, tuning it directionally to instability in the environment (Burdet et al., 2001, Nature; Franklin et al., 2007, J Neurosci; Selen et al., 2009, J Neurosci).