Temporal Analysis of Reference Frames in Parietal Cortex Area 5d during Reach Planning

Abstract

The neural encoding of spatial and postural reference frames in posterior parietal cortex has traditionally been studied during fixed epochs, but the temporal evolution of these representations (or lack thereof) can provide insight into the underlying computations and functions of this region. Here we present single-unit data recorded from two rhesus macaques during a reach planning task. We found that area 5d coded the position of the hand relative to gaze before presentation of the reach target, but switched to coding the target location relative to hand position soon after target presentation. In the pretarget period the most relevant information for success in the task is the position of the hand relative to gaze; however, after target onset, the most task-relevant spatial relationship is the location of the target relative to the hand. The switch in coding suggests that population activity in area 5d may represent postural and spatial information in the reference frame that is most pertinent at each stage of the task. Moreover, although targetϪhand coding was dominant from soon after the reach target onset, this representation was not static but built in strength as movement onset approached, which we speculate could reflect a role for this region in building an accurate state estimate for the limb. We conclude that representations in area 5d are more flexible and dynamic than previously reported.

Organization and evolution of parieto-frontal processing streams in macaque monkeys and humans

“…This can expand the number of potential assemblies available for sensory-motor transformations within cortical networks, by contrasting synchronous vs asynchronous neuronal pools in ways analogous to what was suggested by work in the visual cortex of the ferret (Carmeli et al, 2007). This network dynamics might favor the simultaneous representation of plans for eye and hand movement within different reference frame (see Battaglia-Mayer et al, 2003;McGuire and Sabes, 2009;Sabes, 2010;Crawford et al, 2011;Bremner and Andersen, 2014) by multiplying at the projection area the number of local neuronal assemblies for parieto-frontal signaling. Such assemblies can be selected by the temporal structure and functional composition of their input.…”

Flexible egocentric and allocentric representations of heading signals in parietal cortex

“…In a reach planning task to targets defined by visual or somatosensory stimuli, fMRI activation reflecting the motor goal in reach-coding areas was encoded in gaze-centered coordinates when targets were defined visually, but in body-centered coordinates when targets were defined by unseen proprioceptive cues (47). Furthermore, when monkeys did a similar reaching task, area 5d neurons coded the position of the hand relative to gaze before presentation of the reach target, but switched to coding target location relative to hand position soon after target presentation (48). This result suggested that area 5d may represent postural and spatial information in the reference frame that is most pertinent at each stage of the task.…”

Spatial coordinate transforms linking the allocentric hippocampal and egocentric parietal primate brain systems for memory, action in space, and navigation

“…In line with empirical evidence on some of the spatial coordinate frameworks present in the primate dorsal visual system and related parietal cortex areas (Andersen & Cui, 2009;Bremmer et al, 2002;Bremner & Andersen, 2014;Byrne et al, 2007;Duhamel et al, 1997;Epstein, 2008;Galletti & Fattori, 2018;Snyder, Grieve, Brotchie, & Andersen, 1998;Vann et al, 2009;Vedder et al, 2017;Whitlock, 2017), and the primate hippocampus (Feigenbaum & Rolls, 1991;Georges-François et al, 1999;Robertson et al, 1998Robertson et al, , 1999Rolls et al, 1998Rolls, Robertson, & Georges-François, 1997;Rolls & Wirth, 2018;Wirth et al, 2017), the following set of spatial coordinate transforms are considered here, and are specifically investigated in the three-layer model of successive coordinate transforms described below and illustrated in Figure 2. Each layer in the model corresponds to a different cortical processing area.…”