Head direction signal was also marginal in PPC ( Figure 2, column 2), with 4 of 98 cells expressing mean vector lengths for firing rate as a function of head direction that exceeded the 99th percentile of the shuffled distribution (summarized in Figure S3). Thus, unlike farther caudal areas of posterior cortex ( Chen et al., 1994b), head direction signal at more rostral locations in this study and at even farther rostral locations (as in Nitz, 2006) selleck chemicals llc appears weak. Work in the 1980s showed that cells in the rat parietal region are sensitive to movement types ranging from limb displacements during treadmill running (Chapin and Woodward, 1986) to discrete

modes of locomotion in a radial maze (McNaughton et al., 1989). Recent work has also established that representations of movement in PPC can scale to match different epochs in labyrinthian mazes (Nitz, 2006). It remains to be determined, however, how PPC cells respond during autonomous, spontaneous movement

through open space. A serious hindrance to detecting neural correlates of movement selleck chemical in freely behaving animals is that they move abruptly and at inconsistent locations, which would obscure behavioral correlates in a time-averaged rate map. Indeed, the PPC cells in the open field show poor spatial structure, coherence and stability. We therefore constructed firing rate maps based on moment-to-moment changes in an animals’ state of motion instead of world-based coordinates used in traditional spatial maps (method illustrated in Figure S4; see also Chen et al., [1994a]). Self-motion based firing rate maps failed to reveal consistent firing patterns for most grid cells, though a subset of cells preferred higher

running speeds (as reported in Sargolini et al., 2006). To determine what percentage Oxymatrine of the population showed tuning beyond chance levels we compared self-motion rate maps from grid cells against maps generated from shuffled data (randomized as described in Figure S2), and found that a modest but significant proportion of cells expressed maps that were more coherent (8 of 53 cells [15.1%], Z = 14.0, p < 0.001) and more stable (6 of 53 cells [11.3%], Z = 10.2, p < 0.001; Figure 3B) than the 99th percentile of the distribution of shuffled data. To determine whether grid cells were sensitive to acceleration we next constructed rate maps based on changes in instantaneous speed and direction and found that a small fraction of cells showed acceleration tuning beyond chance levels (3 of 53 cells had an acceleration based rate map that exceeded the 99th percentile of the distribution of shuffled data for coherence, Z = 4.64, p < 0.001; three different cells passed the same criterion for stability, Z = 4.64, p < 0.001; Figure 3C).