Motor control, motor learning, self-recognition, and spatial perception all critically depend on the comparison of motor intention to the actually executed movement. Despite our knowledge that the brainstem-cerebellum plays an important role in motor error detection and motor learning, the involvement of neocortex remains largely unclear. Here, we report the neuronal computation and representation of saccadic error in macaque posterior parietal cortex (PPC). Neurons with persistent pre- and post-saccadic response (PPS) represent the intended end-position of saccade; neurons with late post-saccadic response (LPS) represent the actual end-position of saccade. Remarkably, after the arrival of the LPS signal, the PPS neurons' activity becomes highly correlated with the discrepancy between intended and actual end-position, and with the probability of making secondary (corrective) saccades. Thus, this neuronal computation might underlie the formation of saccadic error signals in PPC for speeding up saccadic learning and leading the occurrence of secondary saccade.
Animal experimentation: Two male rhesus monkeys (6-8 kg, 6-7 years old) were involved in the present study. They were housed in separate cages in a large room with 12 hours light/dark cycle. The horizontal and vertical eye positions signals were recorded using the scleral eye coil technique (Crist Instrument Sclera), and data were sampled at 1 kHz. Before training, each monkey was surgically implanted with a head post and two eye coils. After training in three oculomotor tasks, a recording chamber was implanted above the posterior parietal cortex of the right hemisphere for chronic electrophysiological recording. All experimental and surgical procedures were standard and approved by the Animal Care Committee of Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences (Project number ER-SIBS-221112P); Animal Care and Ethics Committee of Beijing Normal University. (Project number IACUC (BNU) - NKLCNL 2013-09)
- Wolfram Schultz, University of Cambridge, United Kingdom
© 2016, Zhou et al.
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