Correlates of hand synergies in motor cortical areas. An application of multivariate techniques to functional MRI data

One of the most fascinating fields of research in neuroscience regards how the human brain controls the hand in a way that allows to switch flexibly between different tasks while maintaining stable postural configurations. Among the many theories that have been proposed to explain hand control, a recent account suggests that sets of muscles and joints may be simultaneously recruited as functional modules, called synergies. However, despite a synergy-based organization is suggested by many studies in animals as well as recordings of postural or muscle activity, the existence of direct correlates of those motor modules in brain activity remains debated. In this work, kinematic, electromyography, and functional MRI measures are collected in separate sessions while subjects performed a variety of movements towards virtual objects. Later, multivariate methods are applied to the analysis of fMRI data to assess the direct encoding of kinematic synergies in the cortical areas devoted to hand motor control, comparing the synergy-based description to alternative somatotopic or muscle-based models. The results show that kinematic synergies successfully discriminate individual grasping movements, and significantly outperform somatotopic or muscle descriptions. Moreover, the synergy-based model has the best goodness-of-fit with brain activity patterns in primary motor areas and can allow for a reliable decoding of hand postures from brain patterns. These findings support a novel cortical organization for hand movement control and open potential applications for brain-computer interfaces and neuroprostheses.