Sensorimotor adaptation occurs when there is a discrepancy between the expected and actual sensory consequences of a movement. This learning can be precisely measured, but its source has been hard to pin down because standard adaptation tasks introduce two potential learning signals: task performance errors and sensory prediction errors. Here we employed a new method that induces sensory prediction errors without task performance errors. This method combines the use of clamped visual feedback that is angularly offset from the target and independent of the direction of motion, along with instructions to ignore this feedback while reaching to targets. Despite these instructions, participants unknowingly showed robust adaptation of their movements. This adaptation was similar to that observed with standard methods, showing sign dependence, local generalization, and cerebellar dependency. Surprisingly, adaptation rate and magnitude were invariant across a large range of offsets. Collectively, our results challenge current models of adaptation and demonstrate that behavior observed in many studies of adaptation reflect the composite effects of task performance and sensory prediction errors.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5505262 | PMC |
http://dx.doi.org/10.1162/jocn_a_01108 | DOI Listing |
Sci Adv
January 2025
Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA.
Through selective breeding, humans have driven exceptional morphological diversity in domestic dogs, creating more than 200 recognized breeds developed for specialized functional tasks such as herding, protection, and hunting. Here, we use three-dimensional reconstructions of dog skulls to ask whether these function-oriented kennel-club groups reflect differences in morphology that correspond to those functions. We analyzed 117 canid skulls, representing 40 domestic dog breeds and 18 wild subspecies, using geometric morphometric techniques and -means clustering.
View Article and Find Full Text PDFErgonomics
January 2025
Department of Industrial Engineering, Tsinghua University, Beijing, China.
This study investigated whether bidirectional transparency, compared to agent-to-human transparency, improved human-agent collaboration. Additionally, we examined the optimal transparency levels for both humans and agents. We assessed the impact of transparency direction and level on various metrics of a human-agent team, including performance, trust, satisfaction, perceived agent's teaming skills, and mental workload.
View Article and Find Full Text PDFEur J Nucl Med Mol Imaging
January 2025
Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Spitalgasse 23, Vienna, 1090, Austria.
Purpose: Advancements of deep learning in medical imaging are often constrained by the limited availability of large, annotated datasets, resulting in underperforming models when deployed under real-world conditions. This study investigated a generative artificial intelligence (AI) approach to create synthetic medical images taking the example of bone scintigraphy scans, to increase the data diversity of small-scale datasets for more effective model training and improved generalization.
Methods: We trained a generative model on Tc-bone scintigraphy scans from 9,170 patients in one center to generate high-quality and fully anonymized annotated scans of patients representing two distinct disease patterns: abnormal uptake indicative of (i) bone metastases and (ii) cardiac uptake indicative of cardiac amyloidosis.
Exp Brain Res
January 2025
Joseph J. Zilber College of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.
Age-related hand motor impairments may critically depend on visual information though few studies have examined eye movements during tasks of hand function in older adults. The purpose of this study was to assess eye movements and their association with performance while tracing on a touchscreen in young and older adults. Eye movements of 21 young (age 20-38 years; 12 females, 9 males) and 20 older (65-85 years; 10 females, 10 males) adults were recorded while performing an Archimedes spiral tracing task, a common clinical assessment sensitive to age-associated impairments in hand function.
View Article and Find Full Text PDFMed Phys
January 2025
School of Computer Science and Engineering, Beihang University, Beijing, China.
Background: Computed tomography angiography (CTA) is used to screen for coronary artery calcification. As the coronary artery has complicated structure and tiny lumen, manual screening is a time-consuming task. Recently, many deep learning methods have been proposed for the segmentation (SEG) of coronary artery and calcification, however, they often neglect leveraging related anatomical prior knowledge, resulting in low accuracy and instability.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!