Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Time-frequency representations of electroencephalographic signals lend themselves to a granular analysis of cognitive and psychological processes. Characterizing developmental trajectories of time-frequency measures can thus inform us about the development of the processes involved as well as correlated traits and behaviors. We decomposed electroencephalographic (EEG) activity in a large sample of individuals (N = 1692; 917 females), assessed at approximately 3-year intervals from the age of 11 to their mid-20s. Participants completed an oddball task that elicits a robust P3 response. Principal component analysis served to identify the primary dimensions of time-frequency energy. Component loadings were virtually identical across assessment waves. A common and stable set of time-frequency dynamics thus characterized EEG activity throughout this age range. Trajectories of changes in component scores suggest that aspects of brain development reflected in these components comprise two distinct phases, with marked decreases in component amplitude throughout much of adolescence followed by smaller yet significant rates of decreases into early adulthood. Although the structure of time-frequency activity was stable throughout adolescence and early adulthood, we observed subtle change in component loadings as well. Our findings suggest that striking developmental change in event-related potentials emerges through a gradual change in the magnitude and timing of a stable set of dimensions of time-frequency activity, illustrating the usefulness of time-frequency representations of EEG signals and longitudinal designs for understanding brain development. In addition, we provide proof of concept that trajectories of time-frequency activity can serve as potential endophenotypes for childhood externalizing psychopathology and alcohol use in adolescence and early adulthood.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9868093 | PMC |
http://dx.doi.org/10.1111/psyp.14200 | DOI Listing |