Sensorimotor adaptation is influenced by both the size and variance of error information. In the present study, we varied visual uncertainty and error size in a factorial manner and evaluated their joint effect on adaptation, using a feedback method that avoids inherent limitations with standard visuomotor tasks. Uncertainty attenuated adaptation, but only when the error was small. This striking interaction highlights a novel constraint for models of sensorimotor adaptation. Sensorimotor adaptation is driven by sensory prediction errors, the difference between the predicted and actual feedback. When the position of the feedback is made uncertain, motor adaptation is attenuated. This effect, in the context of optimal sensory integration models, has been attributed to the motor system discounting noisy feedback and thus reducing the learning rate. In its simplest form, optimal integration predicts that uncertainty would result in reduced learning for all error sizes. However, these predictions remain untested since manipulations of error size in standard visuomotor tasks introduce confounds in the degree to which performance is influenced by other learning processes such as strategy use. Here, we used a novel visuomotor task that isolates the contribution of implicit adaptation, independent of error size. In two experiments, we varied feedback uncertainty and error size in a factorial manner. At odds with the basic predictions derived from the optimal integration theory, the results show that uncertainty attenuated learning only when the error size was small but had no effect when the error size was large. We discuss possible mechanisms that may account for this interaction, considering how uncertainty may interact with the relevance assigned to the error signal or how the output of the adaptation system in terms of recalibrating the sensorimotor map may be modified by uncertainty. Sensorimotor adaptation is influenced by both the size and variance of error information. In the present study, we varied visual uncertainty and error size in a factorial manner and evaluated their joint effect on adaptation, using a feedback method that avoids inherent limitations with standard visuomotor tasks. Uncertainty attenuated adaptation but only when the error was small. This striking interaction highlights a novel constraint for models of sensorimotor adaptation.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087384 | PMC |
http://dx.doi.org/10.1152/jn.00493.2020 | DOI Listing |
Br J Radiol
January 2025
Royal United Hospital, Combe Park, Bath, Avon, BA1 3NG, UK.
Objectives: Artificial intelligence (AI) software including Brainomix "e-CTA" which detect large vessel occlusions (LVO) have clinical potential. We hypothesised that in real world use where prevalence is low, its clinical utility may be overstated.
Methods: In this single centre retrospective service evaluation project, data sent to Brainomix from a medium size acute National Health Service (NHS) Trust hospital between 1/3/2022-1/3/2023 was reviewed.
Optom Vis Sci
January 2025
School of Optometry, Indiana University, Bloomington, Indiana.
Significance: Visual acuity (VA) depends on many factors. When the goal is to assess retinal health rather than performance, then using a 3-mm pupil reduces unwanted wavefront aberrations. The axis of astigmatism can still potentially change with age.
View Article and Find Full Text PDFTher Deliv
January 2025
Institute of Pharmaceutical Research, GLA University, Mathura, India.
Aim: Development and optimization of raloxifene hydrochloride loaded lipid nanocapsule hydrogel for transdermal delivery.
Method: A 3 Box-Behnken Design and numerical optimization was performed to obtain the optimized formulation. Subsequently, the optimized raloxifene hydrochloride loaded lipid nanocapsule was developed using phase inversion temperature and characterized for physicochemical properties.
iScience
January 2025
Crop Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou 730000, China.
Flax, as a functional crop with rich essential fatty acids and nutrients, is important in nutrition and industrial applications. However, the current process of flax seed detection relies mainly on manual operation, which is not only inefficient but also prone to error. The development of computer vision and deep learning techniques offers a new way to solve this problem.
View Article and Find Full Text PDFMetasurface holograms offer advantages, such as a wide viewing angle, compact size, and high resolution. However, projecting a full-color movie using a single hologram without polarization dependence has remained challenging. Here, we report a full-color dielectric metasurface holographic movie with a resolution of 512 × 512.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!