TY  - JOUR
A1  - Kaiser, Daniel
A1  - Turini, Jacopo
A1  - Cichy, Radoslaw Martin
T1  - A neural mechanism for contextualizing fragmented inputs during naturalistic vision
T2  - eLife
N2  - With every glimpse of our eyes, we sample only a small and incomplete fragment of the visual world, which needs to be contextualized and integrated into a coherent scene representation. Here we show that the visual system achieves this contextualization by exploiting spatial schemata, that is our knowledge about the composition of natural scenes. We measured fMRI and EEG responses to incomplete scene fragments and used representational similarity analysis to reconstruct their cortical representations in space and time. We observed a sorting of representations according to the fragments' place within the scene schema, which occurred during perceptual analysis in the occipital place area and within the first 200 ms of vision. This schema-based coding operates flexibly across visual features (as measured by a deep neural network model) and different types of environments (indoor and outdoor scenes). This flexibility highlights the mechanism's ability to efficiently organize incoming information under dynamic real-world conditions.
KW  - deep neural network models
KW  - fMRI/EEG
KW  - human
KW  - multivariate pattern analysis
KW  - neuroscience
KW  - real-world structure
KW  - scene representation
KW  - visual perception
Y1  - 2019
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/54555
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-545557
N1  - Copyright Kaiser et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
VL  - 8
IS  - e48182
ER  -