title: Contextual Interactions in Grating Plaid Configurations Are Explained by Natural Image Statistics and Neural Modeling.
abstract: Processing natural scenes requires the visual system to integrate local features into global object descriptions. To achieve coherent representations, the human brain uses statistical dependencies to guide weighting of local feature conjunctions. Pairwise interactions among feature detectors in early visual areas may form the early substrate of these local feature bindings. To investigate local interaction structures in visual cortex, we combined psychophysical experiments with computational modeling and natural scene analysis. We first measured contrast thresholds for 2 × 2 grating patch arrangements (plaids), which differed in spatial frequency composition (low, high, or mixed), number of grating patch co-alignments (0, 1, or 2), and inter-patch distances (1° and 2° of visual angle). Contrast thresholds for the different configurations were compared to the prediction of probability summation (PS) among detector families tuned to the four retinal positions. For 1° distance the thresholds for all configurations were larger than predicted by PS, indicating inhibitory interactions. For 2° distance, thresholds were significantly lower compared to PS when the plaids were homogeneous in spatial frequency and orientation, but not when spatial frequencies were mixed or there was at least one misalignment. Next, we constructed a neural population model with horizontal laminar structure, which reproduced the detection thresholds after adaptation of connection weights. Consistent with prior work, contextual interactions were medium-range inhibition and long-range, orientation-specific excitation. However, inclusion of orientation-specific, inhibitory interactions between populations with different spatial frequency preferences were crucial for explaining detection thresholds. Finally, for all plaid configurations we computed their likelihood of occurrence in natural images. The likelihoods turned out to be inversely related to the detection thresholds obtained at larger inter-patch distances. However, likelihoods were almost independent of inter-patch distance, implying that natural image statistics could not explain the crowding-like results at short distances. This failure of natural image statistics to resolve the patch distance modulation of plaid visibility remains a challenge to the approach.
authors.affiliation: Computational Neuroscience Lab, Department of Physics, Institute for Theoretical Physics, University of Bremen Bremen, Germany.
authors.forename: Udo A
authors.initials: UA
authors.lastname: Ernst
authors.affiliation: Computational Neuroscience Lab, Department of Physics, Institute for Theoretical Physics, University of Bremen Bremen, Germany.
authors.forename: Alina
authors.initials: A
authors.lastname: Schiffer
authors.affiliation: Methods Section, Department of Psychology, Johannes Gutenberg University Mainz Mainz, Germany.
authors.forename: Malte
authors.initials: M
authors.lastname: Persike
authors.affiliation: Methods Section, Department of Psychology, Johannes Gutenberg University Mainz Mainz, Germany.
authors.forename: Günter
authors.initials: G
authors.lastname: Meinhardt
keywords: contextual interactions; feature integration; natural image statistics; network model; visual cortex; visual perception