A re-evaluation of effector specificity as an organizational principle of cortical movement planning

Abstract

Pressing a light switch with an elbow or picking up a lost sock with a foot are actions we easily perform. In the past, the cortical control of goal-directed actions with different effectors has been studied by comparing activity preceding eye and hand movements. Posterior parietal cortex (PPC) was found to contribute to movement plans of these effectors. Similar to primary motor cortex, different sub-regions seem to be dedicated to different effectors. A major drawback of this approach, however, is the fact that saccades cannot directly interact with the environment. For instance, we are unable to pick up objects using our eyes. Thus, a comparison of hand and eye movements may be inadequate given the functional differences between the two effector systems. This methodological problem can be overcome by comparing the hand to another limb. A comparison of hand and foot movement planning using fMRI revealed overlapping activity for the two effectors in PPC, shedding doubt on its presumed effector-specific organization. If the same cortical area represents both hand and foot movements, the question arises which other mechanism will ultimately distinguish between the two limbs. Thus, the primary aim of this dissertation project was to re-evaluate the presumed effector-specific organization of PPC by assessing foot, hand, and eye movements while recording the EEG. In the first study (chapter 2), we showed that both hand and foot movements follow Fitts’ law. That is, movements with either limb share the same behavioral and motoric principles. In the second study (chapter 3), we identified event-related potentials that code for different parameters of a movement plan. While the CNV encoded the to-be-used effector, a posterior waveform reflected movement difficulty. In the third study (chapter 4), we found effector-specific modulations of the gamma-band. Here, foot movements were selectively encoded in the range from 60 to 80 Hz at central electrodes. In the final study (chapter 5), we advanced this finding by controlling for potential covert movement plans using a dissociation task. In sum, we show that movements with different effectors are flexibly encoded in the EEG signal.