Abstract
In daily life, prehension is typically not the end goal of hand-object interactions but a precursor for manipulation. Nevertheless, functional MRI (fMRI) studies investigating manual manipulation have primarily relied on prehension as the end goal of an action. Here, we used slow event-related fMRI to investigate differences in neural activation patterns between prehension in isolation and prehension for object manipulation. Sixteen (seven males and nine females) participants were instructed either to simply grasp the handle of a rotatable dial (isolated prehension) or to grasp and turn it (prehension for object manipulation). We used representational similarity analysis (RSA) to investigate whether the experimental conditions could be discriminated from each other based on differences in task-related brain activation patterns. We also used temporal multivoxel pattern analysis (tMVPA) to examine the evolution of regional activation patterns over time. Importantly, we were able to differentiate isolated prehension and prehension for manipulation from activation patterns in the early visual cortex, the caudal intraparietal sulcus (cIPS), and the superior parietal lobule (SPL). Our findings indicate that object manipulation extends beyond the putative cortical grasping network (anterior intraparietal sulcus, premotor and motor cortices) to include the superior parietal lobule and early visual cortex.SIGNIFICANCE STATEMENT A simple act such as turning an oven dial requires not only that the CNS encode the initial state (starting dial orientation) of the object but also the appropriate posture to grasp it to achieve the desired end state (final dial orientation) and the motor commands to achieve that state. Using advanced temporal neuroimaging analysis techniques, we reveal how such actions unfold over time and how they differ between object manipulation (turning a dial) versus grasping alone. We find that a combination of brain areas implicated in visual processing and sensorimotor integration can distinguish between the complex and simple tasks during planning, with neural patterns that approximate those during the actual execution of the action.