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
It is well known that perception and cognition are systematically biased towards the recent past. That is, a decision about the current state of a perceptual feature (e.g. orientation) can be predicted based on a recent state of the same feature. Such serial dependencies have been demonstrated across perception, memory and cognition, and have been jointly attributed to an adaptive mechanism meant to promote stability in a constantly changing environment. Here, we argue that this adaptive mechanism prioritizes past information on the most basic structural level, such that the strength of the attractive bias is modulated by the amount of structural coherence in stimuli. We presented visual patterns of varied structural disorder (randomness) prior to a recognition memory decision that required discriminating between trained and novel visual patterns. Both highly generic geometrical shapes and completely random patterns failed to elicit an effect on decisional response times. By contrast, we found recognition memory decisions to be significantly faster in trials where the irrelevant probe pattern was 'optimally' random. This result suggests that decision-making is influenced by the past's informational worth. More importantly, it suggests an optimal amount of uncertainty to facilitate future decisions.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11557226 | PMC |
http://dx.doi.org/10.1098/rspb.2024.2154 | DOI Listing |
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