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In motor tasks with redundancy neuromotor noise can lead to variations in execution while achieving relative invariance in the result. The present study examined whether humans find solutions that are tolerant to intrinsic noise. Using a throwing task in a virtual set-up where an infinite set of angle and velocity combinations at ball release yield throwing accuracy, our computational approach permitted quantitative predictions about solution strategies that are tolerant to noise. Based on a mathematical model of the task expected results were computed and provided predictions about error-tolerant strategies (Hypothesis 1). As strategies can take on a large range of velocities, a second hypothesis was that subjects select strategies that minimize velocity at release to avoid costs associated with signal- or velocity-dependent noise or higher energy demands (Hypothesis 2). Two experiments with different target constellations tested these two hypotheses. Results of Experiment 1 showed that subjects chose solutions with high error-tolerance, although these solutions also had relatively low velocity. These two benefits seemed to outweigh that for many subjects these solutions were close to a high-penalty area, i.e. they were risky. Experiment 2 dissociated the two hypotheses. Results showed that individuals were consistent with Hypothesis 1 although their solutions were distributed over a range of velocities. Additional analyses revealed that a velocity-dependent increase in variability was absent, probably due to the presence of a solution manifold that channeled variability in a task-specific manner. Hence, the general acceptance of signal-dependent noise may need some qualification. These findings have significance for the fundamental understanding of how the central nervous system deals with its inherent neuromotor noise.

The annual survey of the Japanese Society for Dialysis Therapy Renal Data Registry (JRDR) was conducted for 4413 dialysis facilities at the end of 2017; among which 4360 facilities (98.8%) responded to the facility questionnaire, and 4188 (94.9%) responded to the patient questionnaire. The response rate of the 2017 survey was comparable with the past, even though it was the third year after the new anonymization method. The number of chronic dialysis patients in Japan continues to increase every year; it has reached 334,505 at the end of 2017. The mean age was 68.43 years. The prevalence rate was 2640 patients per million population. Diabetic nephropathy was the most common primary disease among the prevalent dialysis patients (39.0%), followed by chronic glomerulonephritis (27.8%) and nephrosclerosis (10.3%). The rate of diabetic nephropathy and nephrosclerosis has been increasing year by year, whereas that of chronic glomerulonephritis was declining. The number of incident dialysis patients during 2017 was 40,959; it has remained stable since 2008. The average age was 69.68 years and diabetic nephropathy (42.5%) was the most common cause in the incident dialysis patients. These patients caused by diabetes did not change in number for recent several years. Further, 32,532 patients died in 2017; the crude mortality rate was 9.8%. The patients treated by hemodiafiltration (HDF) have been increasing rapidly from the revision of medical reimbursement for HDF therapy in 2012. It has attained 95,140 patients at the end of 2017, which were 18,304 greater than that in 2016. The number of peritoneal dialysis (PD) patients was 9090 in 2017, which had been slightly decreasing since 2014. Further, 19.4% of PD patients treated in the combination of hemodialysis (HD) or HDF therapy (hybrid therapy). And 984 patients were treated by home HD therapy at the end of 2017; it increased by 49 from 2016. Trial registration: JRDR was approved by the ethical committee of JSDT (approval number 1-3) and has been registered in "University hospital Medical Information Network (UMIN) Clinical Trials Registry" as a clinical trial ID of UMIN000018641 at 8th August 2015. https://upload.umin.ac.jp/cgi-bin/ctr/ctr_view_reg.cgi?recptno=R000021578 (Accessed 31 July 2019).

Direct evidence supporting the contribution of upper limb motion on the generation of locomotive motor output in humans is still limited. Here, we aimed to examine the effect of upper limb motion on locomotor-like muscle activities in the lower limb in persons with spinal cord injury (SCI). By imposing passive locomotion-like leg movements, all cervical incomplete (n = 7) and thoracic complete SCI subjects (n = 5) exhibited locomotor-like muscle activity in their paralyzed soleus muscles. Upper limb movements in thoracic complete SCI subjects did not affect the electromyographic (EMG) pattern of the muscle activities. This is quite natural since neural connections in the spinal cord between regions controlling upper and lower limbs were completely lost in these subjects. On the other hand, in cervical incomplete SCI subjects, in whom such neural connections were at least partially preserved, the locomotor-like muscle activity was significantly affected by passively imposed upper limb movements. Specifically, the upper limb movements generally increased the soleus EMG activity during the backward swing phase, which corresponds to the stance phase in normal gait. Although some subjects showed a reduction of the EMG magnitude when arm motion was imposed, this was still consistent with locomotor-like motor output because the reduction of the EMG occurred during the forward swing phase corresponding to the swing phase. The present results indicate that the neural signal induced by the upper limb movements contributes not merely to enhance but also to shape the lower limb locomotive motor output, possibly through interlimb neural pathways. Such neural interaction between upper and lower limb motions could be an underlying neural mechanism of human bipedal locomotion.

Observable structure of variability presents a window into the underlying processes of skill acquisition, especially when the task affords a manifold of solutions to the desired task result. This study examined skill acquisition by analyzing variability in both its distributional and temporal structure. Using a virtual throwing task, data distributions were analyzed by the Tolerance, Noise, Covariation-method (TNC); the temporal structure was quantified by autocorrelation and detrended fluctuation analysis (DFA). We tested four hypotheses: (1) Tolerance and Covariation, not Noise, are major factors underlying long-term performance improvement. (2) Trial-to-trial dynamics in execution space exhibits preferred directions. (3) The direction-dependent organization of variability becomes more pronounced with practice. (4) The anisotropy is in directions orthogonal and parallel to the solution manifold. Results from 13 subjects practicing for 6 days revealed that performance improvement correlated with increasing Tolerance and Covariation; Noise remained relatively constant. Temporal fluctuations and their directional modulation were identified by a novel rotation method that was a priori ignorant about orthogonality. Results showed a modulation of time-dependent characteristics that became enhanced with practice. However, this directionality was not coincident with orthogonal and parallel directions of the solution manifold. A state-space model with two sources of noise replicated not only the observed temporal structure but also its deviations from orthogonality. Simulations suggested that practice-induced changes were associated with an increase in the feedback gain and a subtle weighting of the two noise sources. The directionality in the structure of variability depended on the scaling of the coordinates, a result that highlights that analysis of variability sensitively depends on the chosen coordinates.