Journal
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
Volume 285, Issue 1890, Pages -Publisher
ROYAL SOC
DOI: 10.1098/rspb.2018.1722
Keywords
serial dependence; Kalman filter; Bayesian; optimal behaviour; orientation
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Funding
- European Research Council under the European Union's Seventh Framework Programme (FPT/2007-2013) [338866]
- European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant [797603]
- Marie Curie Actions (MSCA) [797603] Funding Source: Marie Curie Actions (MSCA)
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The world tends to be stable from moment to moment, leading to strong serial correlations in natural scenes. As similar stimuli usually require similar behavioural responses, it is highly likely that the brain has developed strategies to leverage these regularities. A good deal of recent psychophysical evidence is beginning to show that the brain is sensitive to serial correlations, causing strong drifts in observer responses towards previously seen stimuli. However, it is still not clear that this tendency leads to a functional advantage. Here, we test a formal model of optimal serial dependence and show that as predicted, serial dependence in an orientation reproduction task is dependent on current stimulus reliability, with less precise stimuli, such as low spatial frequency oblique Gabors, exhibiting the strongest effects. We also show that serial dependence depends on the similarity between two successive stimuli, again consistent with the behaviour of an ideal observer aiming at minimizing reproduction errors. Lastly, we show that serial dependence leads to faster response times, indicating that the benefits of serial integration go beyond reproduction error. Overall our data show that serial dependence has a beneficial role at various levels of perception, consistent with the idea that the brain exploits the temporal redundancy of the visual scene as an optimization strategy.
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