An Integrative Framework for Sensory, Motor, and Cognitive Functions of the Posterior Parietal Cortex

Abstract

Throughout the history of modern neuroscience, the parietal cortex has been associated with a wide array of sensory, motor, and cognitive functions. The use of non-human primates as a model organism has been instrumental in our current understanding of how areas in the posterior parietal cortex (PPC) modulate our perception and influence our behavior. In this Perspective, we highlight a series of influential studies over the last five decades examining the role of the PPC in visual perception and motor planning. We also integrate long-standing views of PPC functions with more recent evidence to propose a more general model framework to explain integrative sensory, motor, and cognitive functions of the PPC.

Building the bodily self‐awareness: Evidence for the convergence between interoceptive and exteroceptive information in a multilevel kernel density analysis study

“…In particular, during the RHI paradigm, being the real hand position remapped onto a prosthetic hand, such remapping associated with activity in the posterior parietal cortex closely reflects changes in the position sense of the arm (Brozzoli et al, ). Furthermore, the SMG is a part of the neuronal network integrating visuotactile input applied to the hand (Gentile et al, ), and other findings indicate that this region also receives proprioceptive inputs (Berlucchi & Vallar, ; Freedman & Ibos, ; Paulesu, Frackowiak, & Bottini, ; Whitlock, ).…”

The role of putative human anterior intraparietal sulcus area in observed manipulative action discrimination

“…Additionally, longer reaction times may also reflect difference in the time needed for processing the features. Ibos and Freedman () reported that neurons in lateral intraparietal sulcus (LIP), an area adjacent to AIP in the monkey intraparietal sulcus, respond to coloured stimuli with latencies close to 50 ms, while AIP neurons respond to OMAs with latencies closer to 100 ms (Lanzillotto et al., ); Also the readout of the neuronal population activity seems faster in LIP for colour than in AIP for OMAs: the ROC of the LIP population reached its maximum in about 100 ms (Freedman & Ibos, ), while maximum decoding accuracy for OMAs was reached around 280 ms after video onset. Finally, additional delays may be introduced into the decision processes as evidence may accumulate at a slower rate for one of the two features for reasons completely unrelated to difficulty, such as strength of anatomical connections.…”

“…The studies of Freedman and Ibos () suggest that LIP is involved in building a sensory representation that allows subjects to decide between two alternatives (red and yellow dots moving in different directions) and signal their decision by a saccade. An inference that has been little appreciated is that this finding implies that representations for perception and for reporting perceptual events by a motor response, in discrimination and in many other tasks, are distinct, a conclusion also supported by an earlier colour‐discrimination imaging study (Claeys et al., ).…”

Prominent Inhibitory Projections Guide Sensorimotor Computation: An Invertebrate Perspective

“…[38][39][40] In C. elegans, the behavior of the nematode in the absence of food will change the navigational state from "searching" to "dispersal," each of which requires a distinct set of sensory neurons. [50][51][52][53] [41] Consequently, even animals with simple nervous systems are capable of a rapid response to the ongoing changes in the environment, and over time, they adapt to the new sensory state of their surroundings.…”

“…[110] Aquatic vertebrates, such as tadpoles and lampreys, also display the same bilateral action of CNs as observed in mammals. As sensorimotor networks evolve, interneurons allow computation of multimodal sensory integration, as evidenced in the nematode, [68,77,114,115] while in the fly, [79,80,100,101,116] rodent, [117] and mammalian brain, [50][51][52][53][118][119][120][121] the presence of layers of network structures demonstrates a hierarchical organization. Sensorimotor control loops are observed in the fly, where navigation is achieved via a combination of path integration (tracking position relative to a reference point) and known visual landmarks.…”