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Function: require_once
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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Function: _error_handler
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Function: require_once
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Filename: controllers/Detail.php
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Function: _error_handler
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Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
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Function: _error_handler
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Function: strpos
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Filename: controllers/Detail.php
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Function: _error_handler
File: /var/www/html/index.php
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Filename: helpers/my_audit_helper.php
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Are eye movements unconsciously guided towards target locations in familiar scenes? In a recent eyetracking study, Ramey, Yonelinas, and Henderson (2019) measured eye-movement efficiency (scanpath ratio) and memory judgments when participants searched for targets in repeated and novel scenes. When trials judged new with high confidence were selected, scanpath ratio was lower for old scenes (misses) than for new scenes (correct rejections). In addition, familiarity as measured by recognition confidence did not significantly predict scanpath ratio. Ramey et al. attributed these results to unconscious learning guiding eye movements. In a re-assessment of Ramey et al.'s data, we show that their findings can be accounted for by a single-system computational model in which eye movements and memory judgments are driven by a common latent memory representation. In particular, (a) the scanpath ratio difference between high-confidence misses and correct rejections is a consequence of regression to the mean, while (b) the null correlation between familiarity and scanpath ratio, partly a natural consequence of the low reliability of the scanpath ratio measure, is also reproduced by the model. Two pre-registered experiments confirm a novel prediction of the alternative single-system model. This work offers a parsimonious account of Ramey et al.'s findings without recourse to unconscious guidance of eye movements.
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http://dx.doi.org/10.1016/j.cognition.2023.105539 | DOI Listing |
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