Functional heterogeneity of medial posterior parietal cortex of macaque monkey

The posterior parietal cortex (PPC) of primates represents a remarkable platform that has evolved over time to solve some of the computational challenges that we face in the everyday life, such as sensorimotor integration, spatial attention, and motor planning. With the aim of further investigating the multifaceted functional characteristics of medial PPC, we conducted three studies to explore the visuomotor, somatic, visual, and attention-related properties of two PPC areas: V6A, a visuomotor area part of the dorsomedial visual stream, and PE, an area strongly dominated by somatomotor input, residing mainly on the exposed surface of the superior parietal lobule. In the first study, we tested the impact of visual feedback on V6A grasp-related activity during arm movements towards objects of different shapes. Our results demonstrate that V6A is modulated by both grip type and visual information during grasping preparation and execution, with a predominance of cells influenced by grip type. In the second study, we explored the influence of depth and direction information on reach-related activity of neurons in the so far largely neglected medial part of area PE. We observed a remarkable trend in medial PPC, going from the joint coding of depth and direction signals caudally, in area V6A, to a largely segregated processing of the two signals rostrally, in area PE. In the third study, we used a combined fMRI-electrophysiology experiment to investigate the neuronal mechanisms underlying covert shift of attention processes in area V6A. Our preliminary results reveal that half of the cells showed shift-selective activity when the monkey covertly shifted its attention towards the receptive field. All together these findings highlight the role of the medial PPC in integrating information coming from different sources (vision, somatosensory and motor) and emphasize the involvement of action-related regions of the dorsomedial visual stream in higher level cognitive functions.

Neural states in parietal areas during arm reaching

Since the first subdivisions of the brain into macro regions, it has always been thought a priori that, given the heterogeneity of neurons, different areas host specific functions and process unique information in order to generate a behaviour. Moreover, the various sensory inputs coming from different sources (eye, skin, proprioception) flow from one macro area to another, being constantly computed and updated. Therefore, especially for non-contiguous cortical areas, it is not expected to find the same information. From this point of view, it would be inconceivable that the motor and the parietal cortices, diversified by the information encoded and by the anatomical position in the brain, could show very similar neural dynamics. With the present thesis, by analyzing the population activity of parietal areas V6A and PEc with machine learning methods, we argue that a simplified view of the brain organization do not reflect the actual neural processes. We reliably detected a number of neural states that were tightly linked to distinct periods of the task sequence, i.e. the planning and execution of movement and the holding of target as already observed in motor cortices. The states before and after the movement could be further segmented into two states related to different stages of movement planning and arm posture processing. Rather unexpectedly, we found that activity during the movement could be parsed into two states of equal duration temporally linked to the acceleration and deceleration phases of the arm. Our findings suggest that, at least during arm reaching in 3D space, the posterior parietal cortex (PPC) shows low-level population neural dynamics remarkably similar to those found in the motor cortices. In addition, the present findings suggest that computational processes in PPC could be better understood if studied using a dynamical system approach rather than studying a mosaic of single units.