FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2834714594> ?p ?o ?g. }

• W2834714594 endingPage "2262.e3" @default.
• W2834714594 startingPage "2250" @default.
• W2834714594 abstract "•Parietal neurons in Brodmann areas 5 and 7 encoded motor error in reaching•Area 7 neurons encoded target error as well, but area 5 neurons did not•Stimulation to area 5 induced adaptation to compensate for motor errors•Stimulation to area 7 induced adaptation to compensate for target errors Errors in reaching drive trial-by-trial adaptation to compensate for the error. Parietal association areas are implicated in error coding, but whether the parietal error signals directly drive adaptation remains unknown. We first examined the activity of neurons in areas 5 and 7 while two monkeys performed rapid target reaching to clarify whether and how the parietal error signals drive adaptation in reaching. We introduced random errors using a motor-driven prism device to augment random motor errors in reaching. Neurons in both regions encoded information on the target position prior to reaching and information on the motor error after reaching. However, post-movement microstimulation caused trial-by-trial adaptation to cancel the motor error only when it was delivered to area 5. By contrast, stimulation to area 7 caused trial-by-trial adaptation so that the reaching endpoint was adjusted toward the target position. We further hypothesized that area 7 would encode target error that is caused by a target jump during the reach, and our results support this hypothesis. Area 7 neurons encoded target error information, but area 5 neurons did not encode this information. These results suggest that area 5 provides signals for adapting to motor errors and that area 7 provides signals to adapt to target errors. Errors in reaching drive trial-by-trial adaptation to compensate for the error. Parietal association areas are implicated in error coding, but whether the parietal error signals directly drive adaptation remains unknown. We first examined the activity of neurons in areas 5 and 7 while two monkeys performed rapid target reaching to clarify whether and how the parietal error signals drive adaptation in reaching. We introduced random errors using a motor-driven prism device to augment random motor errors in reaching. Neurons in both regions encoded information on the target position prior to reaching and information on the motor error after reaching. However, post-movement microstimulation caused trial-by-trial adaptation to cancel the motor error only when it was delivered to area 5. By contrast, stimulation to area 7 caused trial-by-trial adaptation so that the reaching endpoint was adjusted toward the target position. We further hypothesized that area 7 would encode target error that is caused by a target jump during the reach, and our results support this hypothesis. Area 7 neurons encoded target error information, but area 5 neurons did not encode this information. These results suggest that area 5 provides signals for adapting to motor errors and that area 7 provides signals to adapt to target errors. Errors in reaching drive trial-by-trial adaptation to compensate for the error [1Bastian A.J. Understanding sensorimotor adaptation and learning for rehabilitation.Curr. Opin. Neurol. 2008; 21: 628-633Crossref PubMed Scopus (299) Google Scholar, 2Thoroughman K.A. Shadmehr R. Learning of action through adaptive combination of motor primitives.Nature. 2000; 407: 742-747Crossref PubMed Scopus (688) Google Scholar, 3Kitazawa S. Kohno T. Uka T. Effects of delayed visual information on the rate and amount of prism adaptation in the human.J. Neurosci. 1995; 15: 7644-7652Crossref PubMed Google Scholar]. Our recent study demonstrated that the motor cortical circuits of the primary motor and the premotor cortices provide error signals that drive trial-by-trial adaptation in reaching movements. In addition to representing the error signals, post-movement microstimulation to the motor cortices induced trial-by-trial shifts in the reaching endpoint in a direction that cancels the motor error [4Inoue M. Uchimura M. Kitazawa S. Error signals in motor cortices drive adaptation in reaching.Neuron. 2016; 90: 1114-1126Abstract Full Text Full Text PDF PubMed Scopus (32) Google Scholar]. On the other hand, human imaging studies reported that reaching errors were encoded in the parietal association areas that extended over Brodmann areas 5 and 7 [5Diedrichsen J. Hashambhoy Y. Rane T. Shadmehr R. Neural correlates of reach errors.J. Neurosci. 2005; 25: 9919-9931Crossref PubMed Scopus (455) Google Scholar, 6Luauté J. Schwartz S. Rossetti Y. Spiridon M. Rode G. Boisson D. Vuilleumier P. Dynamic changes in brain activity during prism adaptation.J. Neurosci. 2009; 29: 169-178Crossref PubMed Scopus (177) Google Scholar]. However, whether error signals in these parietal association areas actually drive adaptation in reaching is not known. We ask this question because the motor cortices of the monkey are mutually interconnected to parietal area 5 but much less to parietal area 7 [7Wise S.P. Boussaoud D. Johnson P.B. Caminiti R. Premotor and parietal cortex: corticocortical connectivity and combinatorial computations.Annu. Rev. Neurosci. 1997; 20: 25-42Crossref PubMed Scopus (763) Google Scholar]. Error signals in area 5 may drive adaptation to cancel the motor error in reaching via rich connections with the motor cortices, but error signals in area 7 would exhibit a functionality that is distinct from canceling the motor error. To test this hypothesis, we recorded the neuronal activities of the posterior parietal areas (areas 5 and 7) while two monkeys performed rapid reaching movements toward a visual target that appeared at a random location on a tangent screen. The first experiment introduced random visual displacements by using a motor-driven prism device to augment endpoint errors (prism condition). We expected that the augmented errors would be interpreted as errors in the motor commands (motor error) by the brain. Under this prism condition, we examined whether neuronal activities in areas 5 and 7 encoded information on the endpoint “motor” error. As a control, we also examined whether these regions encoded information on the target position. We then delivered electrical microstimulation after touching by using the same electrode to examine whether any causal relationship existed between the error signals, target positions, and adaptation. Here, we show that neurons in areas 5 and 7 encoded motor error in addition to target position, but post-movement microstimulation caused adaptation to cancel motor error only when it was delivered to area 5. By contrast, stimulation of area 7 produced trial-by-trial adaptation so that the reaching endpoint was adjusted toward the target position. Based on the results, we further hypothesized that area 7 would encode target error that is caused by a movement of the target. In the second experiment, we examined whether areas 5 and 7 encoded the target error by introducing a target jump during the reach (target jump condition). Our results supported this hypothesis. Area 7 neurons encoded target error information, but area 5 neurons did not encode this information. We discuss the distinct roles of area 5 and 7 in driving adaptation in reaching. Monkeys made rapid arm reaching movements toward a visual target that appeared at a random location within a 40 × 40 mm2 square on a tangent screen placed in front of them (Figure 1A). It is worth noting that the vision of the hand and the target was blocked by a pair of liquid-crystal shutters that was opened again for 300 ms upon touching (end of movement). When there was no perturbation, both monkeys achieved fairly small endpoint errors that we regarded as motor errors: 5.2 ± 2.9 mm (mean ± SD) for monkey A and 4.3 ± 2.5 mm for monkey O. Perturbation was introduced by either shifting the visual field by motor-driven wedge prisms before target presentation (prism condition; Figures 1A and 1B, experiment 1) or by shifting the target position during movement (target-jump condition; Figures 1A and 1C, experiment 2). The size of the visual displacement in either condition was randomly chosen from 81 displacements that covered a 40 × 40 mm2 square with an inter-grid interval of 5 mm (Figure 1D, displacement). In the prism condition, the 40 × 40 mm2 target zone was shifted in the direction opposite to the visual displacement (target zone) to stabilize the virtual target zone in the straight ahead direction (virtual target zone). Thus, the monkey was never able to predict the size or the direction of displacement in either condition before touching the screen. In the prism condition, the monkey erred the target toward the direction of prism displacement in addition to the self-generated motor error (Figure 1B). That is, the observed visual apparent error, an error vector from the virtual target position to the virtual touch position (red dots in Figure 2A), is broken down into the sum of the motor error (blue dots in Figure 2A) and the prism displacement (Figure 1B, right). The time series of the motor and the apparent errors appeared to be random, as exemplified in Figure 2C. However, when a discrete model of adaptation (Equations 1 and 2 in STAR Methods) was fitted to the data, the model explained 19% of the total variance (coefficient of determination [d.c.] = 0.19; p = 5.5 × 10−11) with a learning rate of 0.09 (B). The effect of adaptation became clear when large apparent errors occurred in succession (e.g., hatched period in Figure 2C). The model fitting was significant in most blocks we analyzed (23/24; Bonferroni corrected at 0.05; prism in Figure 2E, above a dotted line). The median-estimated learning rates were significantly greater than zero (p = 0.000036; sign test) with median of 0.062 (B; Figure 2F). The results show that each apparent error due to prisms drove a significant adaptation of approximately 6%. These results were consistent with our previous reports [4Inoue M. Uchimura M. Kitazawa S. Error signals in motor cortices drive adaptation in reaching.Neuron. 2016; 90: 1114-1126Abstract Full Text Full Text PDF PubMed Scopus (32) Google Scholar]. In the target-jump condition, a visual apparent error at the end of each movement was broken down into the sum of the inverted vector of each target jump and the motor error (Figure 1C, right). When the same discrete model was applied to the data, the model fitting was significant in some blocks (e.g., Figure 2D; 11/16) but generally with much smaller learning rates, such as 0.023 (B; Figure 2D). The median of the estimated learning rates was positive (0.010) but was not significantly greater than zero (p = 0.21; sign test; Figure 2F). The results show that an apparent error due to the target jump had a much smaller drive for adaptation (∼1%) than the errors in the prism condition (∼6%). These results were also in accord with previous reports [5Diedrichsen J. Hashambhoy Y. Rane T. Shadmehr R. Neural correlates of reach errors.J. Neurosci. 2005; 25: 9919-9931Crossref PubMed Scopus (455) Google Scholar, 8Inoue M. Harada H. Fujisawa M. Uchimura M. Kitazawa S. Modulation of prism adaptation by a shift of background in the monkey.Behav. Brain Res. 2016; 297: 59-66Crossref PubMed Scopus (6) Google Scholar]. It is worth noting that the 40 × 40 mm2 target zone was consistently fixed to the cranial coordinate in the straight-ahead direction in all conditions (Figure 1D, virtual target zone). Thus, the monkeys generally looked around the center of the screen when a target appeared, made a single saccade toward the target during reach, and remained fixated on the target in the prism condition (red crosses in Figure 2I) or on the touch position in the target-jump condition (blue circles in Figure 2J) during the post-movement exposure period when the shutters were re-opened. The probability of observing a saccade during the exposure period was 0.21 in the prism condition (hatched green in Figure 2G) and 0.18 in the target-jump condition (Figure 2H). The eye movements were similar to those reported elsewhere [8Inoue M. Harada H. Fujisawa M. Uchimura M. Kitazawa S. Modulation of prism adaptation by a shift of background in the monkey.Behav. Brain Res. 2016; 297: 59-66Crossref PubMed Scopus (6) Google Scholar]. Stable recordings were obtained from 278 parietal neurons (area 5: n = 161; area 7: n = 117) for more than 60 trials in the prism condition. The mean population activity of area 5 neurons gradually increased over the pre-movement, movement, and post-movement periods (Figure 3B, area 5), which was similar to the activities in the primary motor cortex (M1) and the premotor cortex (PM) reported in our previous study [4Inoue M. Uchimura M. Kitazawa S. Error signals in motor cortices drive adaptation in reaching.Neuron. 2016; 90: 1114-1126Abstract Full Text Full Text PDF PubMed Scopus (32) Google Scholar]. By contrast, the population activity in area 7 was biphasic: there were two distinct responses after target presentation (pre-movement) and after touching when the shutter was opened again (post-movement). We then classified the neuronal activities of all 278 neurons into four groups by applying a cluster analysis (Figure 3B). Each cluster was characterized by activation before the onset of movement (no. 1; pre-movement cells); activation during movement, which peaked around the touch (no. 2; movement cells); major activation after touching (no. 3; post-movement cells); and inhibition during movement (no. 4; movement inhibition cells). It is again apparent that the area 5 neurons were similar to those in PM and M1 in that movement (cluster no. 2) and post-movement neurons (cluster no. 3) were the majorities (Figure 3C), whereas the area 7 neurons were unique in that the proportion of the pre-movement neurons (cluster no. 1) was the largest (40%). We first examined whether the area 5 neurons encoded apparent error information in the prism condition (Figure 4). Here, we take one area 5 neuron with its peak activity after touching as an example (Figure 4A; a cluster no. 3 neuron). Over a 100-ms time window, between 100 and 200 ms after touching (a blue stripe in Figure 4A), we observed 235 spikes in the prism condition. These discharges were not evenly distributed across the apparent errors between the touch and target positions (Figure 4C; virtual touch − virtual tgt) but much less so in the third quadrant. This discrepancy was found to be significant (p = 0.00018; χ2 = 19.9; degrees of freedom [d.f.] = 3) and yielded 0.090 bits of information on the quadrant on which an apparent error fell. By moving the 100-ms time window over the peri-movement time axis, the area 5 neuron was shown to encode significant information on the apparent error over the post-movement period (solid blue line in Figure 4D; 50–900 ms), but not during the pre-movement or movement period. The area 5 neurons encoded information on the target position during the movement period (a red stripe in Figure 4A): the neuron yielded many more spikes when the target appeared in the first quadrant (74; Figure 4B) than when it appeared elsewhere (21, 4, and 28 in the 2nd, 3rd, and 4th quadrants). The neuron yielded significant information on target position during the entire movement period (red trace in Figure 4D). Forty-three percent of the area 5 neurons (69/161) encoded significant information on the apparent error after touching: accumulated information reached the half maximum at 120 ms, peaked at 210 ms, and decreased to the half maximum approximately 490 ms after the touch (Figure 4E, blue traces). Fifty-nine percent of the area 5 neurons (95/161) encoded information on the target position (Figure 4E, red traces), and 32% (52/161) encoded both as well (Figure 4E). For the neurons that encoded both types of information, the preferred direction regarding the target position (e.g., a green arrow in Figure 4B; 56°) generally coincided with the preferred direction regarding the apparent error (e.g., a green arrow in Figure 4C; 74°). The difference was distributed around zero, but some neurons showed greater discrepancies, as indicated by the polar plots in Figure 4E (n = 52). Figure 4F shows an example of a neuron in area 7 that was activated before and after the reaching movement (cluster no. 1). This area 7 neuron encoded information on the apparent error during the post-movement period (Figure 4H; blue trace in Figure 4I) as well as information on the target position during the pre-movement period (Figure 4G; red trace in Figure 4I). A total of 117 area 7 neurons were examined in the prism condition: 53% of the area 7 neurons (62/117) encoded significant information on the apparent error after touching with a peak at 250 ms (blue traces, Figure 4J). Seventy-four percent of them (86/117) encoded significant information on the target position with its peak at around the timing of the button release (red traces, Figure 4J). In 57 neurons that encoded both types of information, two preferred directions were generally consistent with each other (polar plot in Figure 4J). Taken together, both area 5 and 7 neurons generally encoded information on the target position during the movement but encoded error information after the touch. To test whether there is a causal relationship between the error signals and adaptation, we examined the effects of intracortical microstimulation delivered immediately after the end of each reaching movement. If the stimulation was interpreted as an error in reaching, the interpreted error would be canceled. As a result, the actual endpoint error should increase trial by trial in the direction opposite to the preferred error direction. Figure 5A shows the result of post-movement stimulation to a location in area 5, in which a recorded neuron encoded apparent error information. During the pre-test period, when we set the prism displacement to zero, the error was distributed around the target location (black dots, Figures 5A and 5B). We then delivered electrical stimulations (80 μA; 66 200-μs pulses over 200 ms) over 30 successive trials, immediately after each movement was completed, from the touch until 200 ms after the touch. Repetitive pairing of reaching movements with post-movement stimulation produced a gradual increase in the endpoint error in the lower right direction (red dots, Figures 5A and 5B), in the direction opposite to the preferred direction of the apparent error (green arrow, Yae). The rate of increase was 0.11 mm per trial (Figure 5B, top), as indicated by the negative slope of the regression line. When the stimulation was discontinued (post-test period), the error decreased trial by trial in an exponential manner (open circles, Figure 5B) with a correction rate of 0.14 (solid curve). The error did not increase in the orthogonal direction (Figure 5B, bottom). We delivered electrical stimulation to 24 locations in area 5. In 17 of these locations, the neuron showed significant apparent error information. When the apparent errors were averaged across the 17 locations, the mean error still increased in the anti-preferred direction during the stimulation block with a slope of −0.11 ± 0.031 mm/trial (Figure 5C; 95% confidence interval; p < 0.0001). The estimated aftereffect was 2.0 ± 0.73 mm (p < 0.0001), which subsided with an estimated correction rate of 0.096 (Figure 5C). When the data were analyzed separately for each location, the slope was significantly less than zero in 13 locations (filled circles in Figure 5D). In the 13 cases when the stimulus caused significant increases in the error, the median of the aftereffect was 4.2 mm in the anti-preferred direction (p < 0.0005; n = 13; Wilcoxon rank sum test; Figure 5E) with a median correction rate of 0.10 (p < 0.0005; n = 13; Wilcoxon rank sum test; Figure 5E). In 13 of the 24 locations, area 5 neurons encoded significant information on the target position. We applied the same analyses after decomposing the apparent error in the preferred direction of the target (Ytgt) and its orthogonal (Xtgt). Interestingly, the mean error averaged across the 13 cases did not show any significant increase in error during the stimulation period or any significant aftereffect in the post-test period (Figure 5F). The slopes during the stimulation period were significant in only 3 of the 13 locations (Figure 5G), and the yielded slopes were not only negative but also positive in one case. This finding may seem contradictory because the preferred direction of the apparent error generally agreed with the preferred direction of the target when an area 5 neuron encoded both types of information (polar plot in Figure 4E). However, the match was by no means perfect. In the 24 locations, we found 11 area 5 neurons that encoded significant information on the target location in addition to significant information on the apparent error. The differences between the two preferred directions were smaller than 45° in the majority (6 out of 11) but were greater than 100° in four of them. The results show that post-movement microstimulation in area 5 modified reaching movements such that the apparent error in the preferred direction would be decreased in the next trial but was uncorrelated with the target location as an ensemble average across many area 5 neurons. In marked contrast to the area 5 stimulation, stimulation to the area 7 resulted in a gradual increase toward the preferred direction of the target (Figure 6, Ytgt). In a typical location of an area 7 neuron that encoded target information (preferred direction = 132°; Figure 6A, inset), post-movement stimulation produced a gradual increase in error toward the preferred target direction (red dots, Figures 6A and 6B): the rate of increase was significant (0.12 ± 0.11 mm/trial; 95% confidence interval; p < 0.05). When the stimulation was discontinued (post-test period), the error decreased trial by trial in an exponential manner (post-test period) with a correction rate of 0.11 (solid curve; Figure 6B, upper panel). In 15 of the 21 locations of stimulus, area 7 neurons encoded significant information on the target location. When the apparent error was averaged across the 15 locations (Figure 6C), the mean error again increased in the preferred target direction, with a slope of 0.03 ± 0.029 mm/trial (Figure 6C; 95% confidence interval; p < 0.05). The estimated aftereffect was 0.16 ± 0.32 mm, which subsided with an estimated correction rate of 0.012. When the data were analyzed for each location, the slope was significantly greater than zero in 11 locations (filled circles in Figure 6D). The median of the aftereffect was 3.5 mm in the anti-preferred direction (p < 0.0005; n = 11; Wilcoxon rank sum test; Figure 6E), with a median correction rate of 0.10 (p < 0.0005; n = 11; Wilcoxon rank sum test; Figure 6E). By contrast, stimulation to area 7 was neutral on average with respect to the error measured in the preferred direction of the apparent error (Figure 6F). Of the 15 locations where the area 7 neurons encoded significant information on the apparent error, significant effects were found in only four of them (red dots, Figure 6G) and were distributed not only in the top (slope in Xae > 0) but also in the bottom (slope in Xae < 0) hemi-planes. For the 4 locations with a significant increase in errors, the median of the aftereffect was 3.6 mm in the anti-preferred direction (p > 0.05; n = 4; Wilcoxon rank sum test; Figure 6H), with a median correction rate of 0.07 (p > 0.05; n = 4; Wilcoxon rank sum test; Figure 6H). Neurons in areas 5 and 7 encoded information on the target position and endpoint error. However, the effects of microstimulation exhibited a marked contrast. Stimulation of area 5 compensated for the error, but stimulation of area 7 induced adaptation toward a target location. We considered the utility of this new type of adaptation toward a target location and inferred that area 7 encoded information on the target error caused by target movement and contributed to compensating for the target error. We performed an additional experiment (experiment 2) to examine whether area 5 and 7 neurons encoded error information in the target-jump condition (Figure 7). Notably, the same area 5 neuron that encoded apparent error information under the prism condition (Figures 4C and 4D) no longer encoded apparent error information under the target-jump condition (Figure 7C; blue trace in Figure 7D). The neuron fired, but it lost its sensitivity to the apparent error. The lack of error information under the target-jump condition was a general finding across 11 area 5 neurons (Figure 7E). By contrast, the same area 7 neuron that encoded apparent error information under the prism condition (Figures 4H and 4I) encoded apparent error information under the target jump condition as well (Figures 7I and 7J). Six of the 11 area 7 neurons (55%) encoded significant information on the apparent error after a target jump, with a peak at 300 ms (blue traces, Figure 7K). Eight of the 11 area 7 neurons (73%) encoded significant information on the target position with its peak at around the timing of the button release (red traces, Figure 7K). The two preferred directions were generally opposite to each other in six neurons that encoded both types of information (polar plot in Figure 7K). We integrated the error information during the post-movement period from 0 to 500 ms for each neuron (Figure 7M). Two-way mixed-model ANOVA, with the area (area 5/area 7) as a between-subject factor and the condition (prism/target jump) as a within-subject factor, revealed that the main factor of condition (F1,20 = 6.1; p = 0.022) and their interaction (F1,20 = 4.6; p = 0.046) was significant. Post hoc tests (Ryan’s method) [9Day R.W. Quinn G.P. Comparisons of treatments after an analysis of variance in ecology.Ecol. Monogr. 1989; 59: 433-463Crossref Scopus (1694) Google Scholar] revealed that the mean apparent error information under the target-jump condition was significantly smaller in area 5 (mean ± SEM = 0.0083 ± 0.0047 bits) than in area 7 (0.32 ± 0.12 bits; F1,40 = 5.4; p = 0.026), and the mean error information in area 5 was significantly smaller under the target-jump condition (0.0083 ± 0.0047 bits) than under the prism condition (0.19 ± 0.07 bits; F1,20 = 10.6; p = 0.0039). These results demonstrated that area 7 neurons, but not area 5 neurons, encoded target error information. The present study demonstrated that both neurons in areas 5 and 7 encoded information on motor errors. However, post-movement microstimulation produced adaptation as if it canceled the motor error only when it was delivered to area 5. By contrast, stimulation of area 7 produced adaptation as if it followed a target direction. We further demonstrated that area 7 neurons encoded an error due to a target jump (target error), but area 5 did not encode this type of error. These results highlight the importance of area 5 in providing signals for adapting to motor errors and suggest a distinctive role of area 7 in providing signals for adapting to target errors. We introduced random apparent errors in reaching. Although the distributions of the apparent errors were identical in both the prism and target-jump conditions, the model analyses revealed that the animals adapted a few times more efficiently in the prism condition (median learning rates: B = 0.062; Figure 2F) than in the target-jump condition (median B = 0.010; Figure 2F). The magnitudes of the learning rates were comparable to those reported in the monkey [8Inoue M. Harada H. Fujisawa M. Uchimura M. Kitazawa S. Modulation of prism adaptation by a shift of background in the monkey.Behav. Brain Res. 2016; 297: 59-66Crossref PubMed Scopus (6) Google Scholar, 10Kitazawa S. Yin P.-B. Prism adaptation with delayed visual error signals in the monkey.Exp. Brain Res. 2002; 144: 258-261Crossref PubMed Scopus (23) Google Scholar]. In humans, it was also reported that the learning rate for a target jump (0–0.05) was much smaller than those for visual rotation or curl force field perturbation (0.1–0.15) [5Diedrichsen J. Hashambhoy Y. Rane T. Shadmehr R. Neural correlates of reach errors.J. Neurosci. 2005; 25: 9919-9931Crossref PubMed Scopus (455) Google Scholar]. The behavioral results obtained in the present study confirmed that the brain adapts differently to the same-sized errors, depending on whether the hand appeared at an unexpected location (prism condition; blue circles in Figure 2I) or the target jumped to an unexpected location (target-jump condition; red crosses in Figure 2J). Nearly half of the area 5 neurons encoded information on apparent error, a discrepancy between the target and the hand, in the prism condition (Figure 4E). The result agrees with a long-held view that the posterior parietal regions, including area 5, represent a discrepancy between a target and hand position in space [11Buneo C.A. Andersen R.A. The posterior parietal cortex: sensorimotor interface for the planning and online control of visually guided movements.Neuropsychologia. 2006; 44: 2594-2606Crossref PubMed Scopus (417) Google Scholar]. However, it is worth noting that the area 5 neurons did not encode the same target-hand discrepancy when it was caused by a jump during movement (Figure 7E). The results clearly show that the area 5 neurons were not automatically computing the discrepancy between the target and the hand positions per se. Rather, we propose that the area 5 neurons represent the discrepancy between the planned hand position and the achieved hand position, which can be regarded as a true motor error. The functional significance of the motor error information in area 5 was confirmed by stimulation experiments. Post-movement microstimulation caused gradual increases in errors in the direction opposite to the preferred direction of apparent errors (Figure 5). This result indicates that a motor error represented by activation of a group of a" @default.
• W2834714594 created "2018-07-19" @default.
• W2834714594 creator A5013335631 @default.
• W2834714594 creator A5087193833 @default.
• W2834714594 date "2018-07-01" @default.
• W2834714594 modified "2023-09-25" @default.
• W2834714594 title "Motor Error in Parietal Area 5 and Target Error in Area 7 Drive Distinctive Adaptation in Reaching" @default.
• W2834714594 cites W1492478739 @default.
• W2834714594 cites W158266941 @default.
• W2834714594 cites W1635674943 @default.
• W2834714594 cites W1654752245 @default.
• W2834714594 cites W1818028123 @default.
• W2834714594 cites W1949456525 @default.
• W2834714594 cites W1963911933 @default.
• W2834714594 cites W1986111981 @default.
• W2834714594 cites W1989256505 @default.
• W2834714594 cites W1990656973 @default.
• W2834714594 cites W2000667835 @default.
• W2834714594 cites W2001594506 @default.
• W2834714594 cites W2009635803 @default.
• W2834714594 cites W2015499500 @default.
• W2834714594 cites W2020030874 @default.
• W2834714594 cites W2028612696 @default.
• W2834714594 cites W2038321648 @default.
• W2834714594 cites W2039619955 @default.
• W2834714594 cites W2076058358 @default.
• W2834714594 cites W2085238148 @default.
• W2834714594 cites W2085427933 @default.
• W2834714594 cites W2094828131 @default.
• W2834714594 cites W2096184857 @default.
• W2834714594 cites W2118015362 @default.
• W2834714594 cites W2127907018 @default.
• W2834714594 cites W2134585097 @default.
• W2834714594 cites W2144985470 @default.
• W2834714594 cites W2158750745 @default.
• W2834714594 cites W2166114707 @default.
• W2834714594 cites W2170172094 @default.
• W2834714594 cites W2280025248 @default.
• W2834714594 cites W2338981564 @default.
• W2834714594 cites W2347595076 @default.
• W2834714594 cites W2770121988 @default.
• W2834714594 cites W2797892668 @default.
• W2834714594 cites W4253055352 @default.
• W2834714594 doi "https://doi.org/10.1016/j.cub.2018.05.056" @default.
• W2834714594 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29983313" @default.
• W2834714594 hasPublicationYear "2018" @default.
• W2834714594 type Work @default.
• W2834714594 sameAs 2834714594 @default.
• W2834714594 citedByCount "22" @default.
• W2834714594 countsByYear W28347145942018 @default.
• W2834714594 countsByYear W28347145942019 @default.
• W2834714594 countsByYear W28347145942020 @default.
• W2834714594 countsByYear W28347145942021 @default.
• W2834714594 countsByYear W28347145942022 @default.
• W2834714594 countsByYear W28347145942023 @default.
• W2834714594 crossrefType "journal-article" @default.
• W2834714594 hasAuthorship W2834714594A5013335631 @default.
• W2834714594 hasAuthorship W2834714594A5087193833 @default.
• W2834714594 hasBestOaLocation W28347145941 @default.
• W2834714594 hasConcept C139807058 @default.
• W2834714594 hasConcept C15744967 @default.
• W2834714594 hasConcept C169760540 @default.
• W2834714594 hasConcept C180747234 @default.
• W2834714594 hasConcept C86803240 @default.
• W2834714594 hasConceptScore W2834714594C139807058 @default.
• W2834714594 hasConceptScore W2834714594C15744967 @default.
• W2834714594 hasConceptScore W2834714594C169760540 @default.
• W2834714594 hasConceptScore W2834714594C180747234 @default.
• W2834714594 hasConceptScore W2834714594C86803240 @default.
• W2834714594 hasIssue "14" @default.
• W2834714594 hasLocation W28347145941 @default.
• W2834714594 hasLocation W28347145942 @default.
• W2834714594 hasOpenAccess W2834714594 @default.
• W2834714594 hasPrimaryLocation W28347145941 @default.
• W2834714594 hasRelatedWork W2032288610 @default.
• W2834714594 hasRelatedWork W2093140091 @default.
• W2834714594 hasRelatedWork W2099966111 @default.
• W2834714594 hasRelatedWork W2121588077 @default.
• W2834714594 hasRelatedWork W2886908538 @default.
• W2834714594 hasRelatedWork W2944732678 @default.
• W2834714594 hasRelatedWork W4232340583 @default.
• W2834714594 hasRelatedWork W4240392230 @default.
• W2834714594 hasRelatedWork W4244378786 @default.
• W2834714594 hasRelatedWork W4245780361 @default.
• W2834714594 hasVolume "28" @default.
• W2834714594 isParatext "false" @default.
• W2834714594 isRetracted "false" @default.
• W2834714594 magId "2834714594" @default.
• W2834714594 workType "article" @default.