Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Predicting the outcome of observed actions is fundamental for efficient interpersonal interactions. This is evident in interceptive sports, where predicting the future ball trajectory could make apart success and fail. We quantitatively assessed the predictive abilities of non-trained adults intercepting thrown balls in immersive virtual reality. Participants performed better when they could see the complete throwing action in addition to the ball flight, and they were able to move toward the correct direction when the ball flight was occluded. In both cases, performance varies with the individual motor style of the thrower. These results prove that humans can effectively predict the unfolding of complex full-body actions, with no need to extensively practice them, and that such predictions are exploited online to optimize interactive motor performance. This suggests that humans hold a functional knowledge of how actions recurrent in the human motor repertoire map into the changes brought to the environment.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9574511 | PMC |
http://dx.doi.org/10.1016/j.isci.2022.105212 | DOI Listing |
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