Experts' cognitive abilities adapt in response to the challenges they face in order to produce elite-level performance. Expert athletes, in particular, must integrate their motor capabilities with their cognitive and perceptual processes. Indoor rock climbers are particularly unique athletes in that much of the challenge they face is to accurately perceive and consolidate multiple movements into manageable action plans. In the current study, we investigated how climbers' level of expertise influenced their perception of action capabilities, visual memory of holds, and memory of planned and performed motor sequences. In Experiment 1, climbers judged their perceived capability to perform single climbing moves and then attempted each movement. Skilled climbers were less confident, but perceived their action capabilities more accurately than less skilled climbers. In Experiment 2, climbers recalled holds on a route, as well as predicted and recalled move sequences before and after climbing, respectively. Expertise was positively associated with visual memory performance as well as planned and recalled motor sequence accuracy. Together, these findings contribute to our knowledge of motor expertise and suggest that motor expert's ability to accurately estimate their action capabilities may underlie complex cognitive processes in their domain of expertise.

Download full-text PDF

Source
http://dx.doi.org/10.3758/s13421-019-00985-7DOI Listing

Publication Analysis

Top Keywords

action capabilities
12
indoor rock
8
visual memory
8
experiment climbers
8
skilled climbers
8
expertise
5
motor
5
climbers
5
expertise effects
4
effects perceptual
4

Similar Publications

The expansion of single-cell analytical techniques has empowered the exploration of diverse biological questions at the individual cells. Droplet-based single-cell RNA sequencing (scRNA-seq) methods have been particularly widely used due to their high-throughput capabilities and small reaction volumes. While commercial systems have contributed to the widespread adoption of droplet-based scRNA-seq, their relatively high cost limits the ability to profile large numbers of cells and samples.

View Article and Find Full Text PDF

Presently, the in vitro recording of intracellular neuronal signals on microelectrode arrays (MEAs) requires complex 3D nanostructures or invasive and approaches such as electroporation. Here, it is shown that laser poration enables intracellular coupling on planar electrodes without damaging neurons or altering their spontaneous electrophysiological activity, allowing the process to be repeated multiple times on the same cells. This capability distinguishes laser-based neuron poration from more invasive methods like electroporation, which typically serve as endpoint measurement for cells.

View Article and Find Full Text PDF

Recognizing the action of plastic bag taking from CCTV video footage represents a highly specialized and niche challenge within the broader domain of action video classification. To address this challenge, our paper introduces a novel benchmark video dataset specifically curated for the task of identifying the action of grabbing a plastic bag. Additionally, we propose and evaluate three distinct baseline approaches.

View Article and Find Full Text PDF

Autonomous driving has demonstrated impressive driving capabilities, with behavior decision-making playing a crucial role as a bridge between perception and control. Imitation Learning (IL) and Reinforcement Learning (RL) have introduced innovative approaches to behavior decision-making in autonomous driving, but challenges remain. On one hand, RL's policy networks often lack sufficient reasoning ability to make optimal decisions in highly complex and stochastic environments.

View Article and Find Full Text PDF

This study presents a comprehensive workflow for developing and deploying Multi-Layer Perceptron (MLP)-based soft sensors on embedded FPGAs, addressing diverse deployment objectives. The proposed workflow extends our prior research by introducing greater model adaptability. It supports various configurations-spanning layer counts, neuron counts, and quantization bitwidths-to accommodate the constraints and capabilities of different FPGA platforms.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!