AUTHOR=Torres Elizabeth B., Quian Quiroga Rodrigo , Cui He , Buneo Christopher 

TITLE=Neural correlates of learning and trajectory planning in the posterior parietal cortex

JOURNAL=Frontiers in Integrative Neuroscience

VOLUME=Volume 7 - 2013

YEAR=2013

URL=https://www.frontiersin.org/journals/integrative-neuroscience/articles/10.3389/fnint.2013.00039

DOI=10.3389/fnint.2013.00039

ISSN=1662-5145

ABSTRACT=The posterior parietal cortex (PPC) is thought to play an important role in the planning of visually-guided reaching movements. However, the relative roles of the various subdivisions of the PPC in this function are still poorly understood. For example, studies of dorsal area 5 point to a representation of reaches in both extrinsic (endpoint) and intrinsic (joint or muscle) coordinates, as evidenced by partial changes in preferred directions and positional discharge with changes in arm posture. In contrast, recent findings suggest that the adjacent medial intraparietal area (MIP) is involved in more abstract representations, e.g. in converting target and hand position signals in visual coordinates into desired ‘displacement vectors’.  Such a representation is suitable for planning reach trajectories involving straight paths to targets. However, it is currently unclear how MIP contributes to the planning of reaches requiring highly curved trajectories and moreover, whether these trajectories are represented purely in extrinsic coordinates or in intrinsic ones as well.  Here we investigated the role of the PPC in these processes during an obstacle avoidance task that required the planning of curved trajectories that recruited different postural paths for which the animals had not been explicitly trained. We found that PPC planning activity was predictive of both the spatial and temporal aspects of upcoming trajectories. Moreover, activity of the same PPC neurons predicted the upcoming trajectory in both endpoint and joint coordinates. The predictive power of these neurons remained stable and accurate despite concomitant learning related changes in planning activity across task conditions. These findings suggest the role of the PPC can be extended from specifying abstract movement plans to expressing these plans as corresponding trajectories in both endpoint and joint coordinates. The PPC appears to contribute to reach planning at multiple levels of representation.