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
The neuronal selectivity observed in the avian song system for the Bird's Own Song progressively emerged as an extraordinary fruitful model to investigate the neural code underlying the recognition of complex stimuli and the occurrence of learned behaviors. In adult zebra finch, neurons from the HVC (used as a proper name) show very selective auditory responses, firing more to presentation of the Bird's Own Song (BOS) than to reverse BOS or other conspecific songs. However, as adult zebra finches always produce the same stereotyped song, the presence of such highly selective neurons in birds with larger repertoire still remains an open question. Data presented here show that neurons selective for the BOS can be found in adult canary, a seasonal breeding bird which display a large repertoire. More precisely, we found that a large proportion of neurons (29/36) exhibits higher responses to presentation of the forward than to the reverse BOS, and that 22% of the cells were identified as selective on the basis of the d' value. For a cell that was extensively studied, we evaluated to what extent temporal stimulus-related structure predicts the acoustic stimulus using linear or non-linear artificial neural networks (ANN). These analyses indicated that the temporal structure contained in spike trains characterizes more accurately the stimulus than the firing rate. The limitations of applying ANN analyses to electrophysiological data are discussed and potential solutions to increase the confidence in these analysis are proposed.
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Source |
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http://dx.doi.org/10.1016/j.jphysparis.2005.09.011 | DOI Listing |
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